Question: what are the mortality rates overall and in specific populations

Title: Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016. Content: BACKGROUND Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap between male and female life expectancy increased with progression to higher levels of SDI. Some countries with exceptional health performance in 1990 in terms of the difference in observed to expected life expectancy at birth had slower progress on the same measure in 2016. INTERPRETATION Globally, mortality rates have decreased across all age groups over the past five decades, with the largest improvements occurring among children younger than 5 years. However, at the national level, considerable heterogeneity remains in terms of both level and rate of changes in age-specific mortality; increases in mortality for certain age groups occurred in some locations. We found evidence that the absolute gap between countries in age-specific death rates has declined, although the relative gap for some age-sex groups increased. Countries that now lead in terms of having higher observed life expectancy than that expected on the basis of development alone, or locations that have either increased this advantage or rapidly decreased the deficit from expected levels, could provide insight into the means to accelerate progress in nations where progress has stalled. FUNDING Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.

Title: Global patterns of mortality in international migrants: a systematic review and meta-analysis. Content: BACKGROUND 258 million people reside outside their country of birth; however, to date no global systematic reviews or meta-analyses of mortality data for these international migrants have been done. We aimed to review and synthesise available mortality data on international migrants. METHODS In this systematic review and meta-analysis, we searched MEDLINE, Embase, the Cochrane Library, and Google Scholar databases for observational studies, systematic reviews, and randomised controlled trials published between Jan 1, 2001, and March 31, 2017, without language restrictions. We included studies reporting mortality outcomes for international migrants of any age residing outside their country of birth. Studies that recruited participants exclusively from intensive care or high dependency hospital units, with an existing health condition or status, or a particular health exposure were excluded. We also excluded studies limited to maternal or perinatal outcomes. We screened studies using systematic review software and extracted data from published reports. The main outcomes were all-cause and International Classification of Diseases, tenth revision (ICD-10) cause-specific standardised mortality ratios (SMRs) and absolute mortality rates. We calculated summary estimates using random-effects models. This study is registered with PROSPERO, number CRD42017073608. FINDINGS Of the 12 480 articles identified by our search, 96 studies were eligible for inclusion. The studies were geographically diverse and included data from all global regions and for 92 countries. 5464 mortality estimates for more than 15·2 million migrants were included, of which 5327 (97%) were from high-income countries, 115 (2%) were from middle-income countries, and 22 (<1%) were from low-income countries. Few studies included mortality estimates for refugees (110 estimates), asylum seekers (144 estimates), or labour migrants (six estimates). The summary estimate of all-cause SMR for international migrants was lower than one when compared with the general population in destination countries (0·70 [95% CI 0·65-0·76]; I2=99·8%). All-cause SMR was lower in both male migrants (0·72 [0·63-0·81]; I2=99·8%) and female migrants (0·75 [0·67-0·84]; I2=99·8%) compared with the general population. A mortality advantage was evident for refugees (SMR 0·50 [0·46-0·54]; I2=89·8%), but not for asylum seekers (1·05 [0·89-1·24]; I2=54·4%), although limited data was available on these groups. SMRs for all causes of death were lower in migrants compared with the general populations in the destination country across all 13 ICD-10 categories analysed, with the exception of infectious diseases and external causes. Heterogeneity was high across the majority of analyses. Point estimates of all-cause age-standardised mortality in migrants ranged from 420 to 874 per 100 000 population. INTERPRETATION Our study showed that international migrants have a mortality advantage compared with general populations, and that this advantage persisted across the majority of ICD-10 disease categories. The mortality advantage identified will be representative of international migrants in high-income countries who are studying, working, or have joined family members in these countries. However, our results might not reflect the health outcomes of more marginalised groups in low-income and middle-income countries because little data were available for these groups, highlighting an important gap in existing research. Our results present an opportunity to reframe the public discourse on international migration and health in high-income countries. FUNDING Wellcome Trust, National Institute for Health Research, Medical Research Council, Alliance for Health Policy and Systems Research, Department for International Development, Fogarty International Center, Grand Challenges Canada, International Development Research Centre Canada, Inter-American Institute for Global Change Research, National Cancer Institute, National Heart, Lung and Blood Institute, National Institute of Mental Health, Swiss National Science Foundation, World Diabetes Foundation, UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, and European Society for Clinical Microbiology and Infectious Diseases (ESCMID) Study Group Research Funding for the ESCMID Study Group for Infections in Travellers and Migrants.

Title: Motor vehicle-related death rates--United States, 1999-2005. Content: In 2005, the most recent year for which data are available, 45,520 deaths in the United States were related to motor vehicles. A Healthy People 2010 objective calls for reducing the rate of deaths related to motor vehicles to 9.2 per 100,000 population from a baseline of 15.6 in 1998. To assess progress toward the Healthy People objective and to examine characteristics of motor vehicle--related death rates, CDC analyzed data from the National Vital Statistics System (NVSS) for the period 1999--2005. This report summarizes the results of that analysis, which determined that, during 1999--2005, although annual age-adjusted motor vehicle--related death rates overall were nearly unchanged (range: 15.2--15.7 per 100,000 population), substantial differences were observed by state, U.S. Census region, sex, race, and age group. Among states, the average annual death rate ranged from 7.9 per 100,000 population in Massachusetts to 31.9 in Mississippi. Among regions, the rate ranged from 9.8 per 100,000 population in the Northeast to 19.5 in the South. The rate for men (21.7 per 100,000 population) was more than double the rate for women (9.4); the rate for American Indians/Alaska Natives (27.2) was nearly twice the rate for whites (15.7) and blacks (15.2), and the rate for persons aged 15--24 years (26.8) was 74% higher than the average annual rate overall (15.4). Additional analysis and research to determine the causes of geographic and demographic variations in motor vehicle--related deaths might result in more effective targeted interventions among the states, regions, and populations at greatest risk.

Title: Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns Content: For COVID-19 the Infection Fatality Rate or IFR - a crucial variable in epidemiological modeling - is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.

Title: Reassessing the Global Mortality Burden of the 1918 Influenza Pandemic Content: Mortality estimates of the 1918 influenza pandemic vary considerably, and recent estimates have suggested that there were 50 million to 100 million deaths worldwide. We investigated the global mortality burden using an indirect estimation approach and 2 publicly available data sets: the Human Mortality Database (13 countries) and data extracted from the records of the Statistical Abstract for British India. The all-cause Human Mortality Database was used to estimate mortality annually for 1916–1921 for detailed age groups. Three different calculation methods were applied to the data (low, medium, and high scenarios), and we used a multilevel regression model to control for distorting factors (e.g., war and the underlying time trend in mortality). Total pandemic mortality was an estimated 15 million deaths worldwide in 1918 (n = 2.5 million in 1919) after including the rates for British India and controlling for wars and the underlying mortality trend. According to our validity analysis, simulations of total number of deaths being greater than 25 million are not realistic based on the underlying mortality rates included in Human Mortality Database and in British India. Our results suggest the global death impact of the 1918 pandemic was important (n = 17.4 million) but not as severe as most frequently cited estimates.

Title: Why Do COVID-19 Fatality Rates Differ Across Countries? An Explorative Cross-country Study Based on Select Indicators Content: In this article, we analyse the factors that determine the fatality rates across 29 economies spread across both the developing and developed world. Recent emerging literature and expert opinions in popular media have indicated various factors that may explain cross-country difference in fatality rates. These factors range from access to public health infrastructure, BCG vaccination policies, demographic structure, restrictive policy interventions and the weather. In addition, articles are examining different kinds of fatality rates that can be explained. Progressing beyond fragmented databases and anecdotal evidence, we have developed a database for such factors, have explored various econometric models to test the explanatory power of these factors in explaining several kinds of fatality rates. Based on available data, our study reveals that factors such as public health system, population age structure, poverty level and BCG vaccination are powerful contributory factors in determining fatality rates. Interactions between factors such as poverty level and BCG vaccination provide interesting insights into the complex interplay of factors. Our analysis suggests that poor citizens’ access to the public healthcare system are worse in many countries irrespective of whether they are developed or developing countries.

Title: Trends in childhood cancer mortality--United States, 1990-2004. Content: Cancer is the fourth most common cause of death (after unintentional injury, homicide, and suicide) among persons aged 1-19 years in the United States. Because recent childhood cancer mortality has not been well characterized in terms of temporal, demographic, and geographic trends, CDC analyzed cancer death rates among children (defined as aged 0-14 years) and adolescents (defined as aged 15-19 years) for the period 1990-2004 by sex, age group, race, ethnicity, U.S. Census region, and primary cancer site/leading diagnosis, using the most recent data available from the National Vital Statistics System (NVSS). This report describes the results of that analysis, which indicated that, overall, age-adjusted childhood cancer death rates decreased significantly during 1990-2004 among both sexes, both age groups, all races (except American Indians/Alaska Natives [AI/ANs]), Hispanics, non-Hispanics, and all U.S. Census regions. However, decreases in death rates varied among U.S. Census regions and between Hispanics and non-Hispanics. Eliminating racial/ethnic health disparities is one of the overarching goals of Healthy People 2010. Further research is needed to understand geographic and ethnic disparities in childhood cancer death rates. Moreover, cancer prevention and intervention measures should be designed to reach populations that are underserved and at high risk.

Title: Excess mortality from seasonal influenza is negligible below the age of 50 in Israel: implications for vaccine policy Content: PURPOSE: Evaluation of the severity of pandemic influenza requires reliable estimates of mortality attributable to the seasonal influenza. METHODS: Excess age-specific mortality during periods of influenza activity was evaluated in Israel during the period 1999–2006 for three death categories. For each respiratory year, the lowest monthly moving average for the mortality rate was subtracted from each month in the period of influenza activity. Average mortality rates in years with minimal influenza activity were deducted from corresponding months to exclude winter mortality unrelated to influenza. The sums of these results were used as estimates of excess mortality rates. RESULTS: Overall excess mortality rates ranged from 7.7 to 36.1 per 100,000 for all causes, and from 4.4 to 24.4 per 100,000 for respiratory and circulatory causes. Influenza was associated with an average of 869 (range 280–1,516) deaths annually from respiratory and circulatory diseases during seasons with significant influenza activity. About 90% of the influenza-associated mortality from respiratory and circulatory diseases was in the age group 65+ years and about 1% in the age group <50 years. The age group <50 years accounted for an annual average of seven deaths from respiratory and circulatory diseases. CONCLUSION: Annual mortality associated with seasonal influenza is highly variable. Under the age of 50 years, there is minimal seasonal influenza associated mortality. This information provides an important baseline for evaluating the severity of the A(H1N1) 2009 influenza pandemic, where persons under 50 years of age were often disproportionately represented.

Title: Predicted COVID-19 fatality rates based on age, sex, comorbidities, and health system capacity Content: Early reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high- to lower-income regions. Accounting for differences in the distribution of age, sex, and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 0.95% for High Income Asia Pacific. However, these predictions must be treated as lower bounds, as they are grounded in fatality rates from countries with advanced health systems. In order to adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood influenza. This adjustment greatly diminishes, but does not entirely erase, the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.43% in Western Sub-Saharan Africa to 1.74% for Eastern Europe.

Title: Social Disparities in the Evolution of an Epidemiological Profile: Transition Processes in Mortality Between 1971 and 2008 in an Industrialized Middle Income Country: The Case of Hungary Content: The present paper seeks to understand the transformation of mortality patterns in Hungary, by which mortality inequalities by education began to appear in the early 1980s, continued to grow in the following 25 years, and now seem to be stabilising. The first part of this paper overviews the theoretical innovations of the last decades regarding the interpretation of cause-specific mortality dynamics, often referred to as epidemiological transition theories, and their relevance for the analysis of mortality inequalities. The paper then analyses the cause-specific trends of mortality for two educational classes between 1971 and 2008. The trends were corrected for changes in the coding system and divided into linear (stagnating, increasing or decreasing) periods. Causes of death were grouped according to the relationship between the sequences of these periods for the two educational classes. The 57 causes of death were finally clustered into six groups. One group, which is dominated by nutrition-related and cardiovascular diseases, is largely responsible for the onset of mortality inequalities in 1980. The results imply that the quality of nutrition has diverged for the educational classes since 1980, and this fact has left its footprint on the pattern of mortality. The history of food production and availability seems to be in line with nutrition-related mortality, and it is argued that nutrition transition theory provides a very plausible explanatory framework for the growth of mortality inequalities.

Title: The Contribution of Age Structure to the Number of Deaths from Covid-19 in the UK by Geographical Units Content: This study investigates the contribution of population age structure to mortality from Covid-19 in the UK by geographical units. We project death rates at various spatial scales by applying data on age-specific fatality rates to the area's population by age and sex. Our analysis shows a significant variation in the projected death rates between the constituent countries of the UK, between its regions and within regions. First, Scotland and Wales have higher projected fatality levels from Covid-19 than England, whereas Northern Ireland has lower rate. Second, the infection fatality rates are projected to be substantially higher in small towns and rural areas than those in large urban areas. Third, our analysis shows that within urban regions there are also 'pockets' of high projected death rates. Overall, the areas with high and low fatality rates tend to cluster because of the high residential separation of different population age-groups in the UK. Our analysis also reveals that the Welsh-, Gaelic- and Cornish-speaking communities with relatively old populations are likely to experience heavy population losses if the virus spreads widely across the UK.

Title: EXCESS MORTALITY FROM COVID-19. WEEKLY EXCESS DEATH RATES BY AGE AND SEX FOR SWEDEN. Content: Objectives: Mortality from Covid-19 is monitored in detail both within as well as between countries with different strategies against the virus. However, death counts and relative risks based on crude numbers can be misleading. Instead, age specific death rates should be used for comparability. Given the difficulty of ascertainment of Covid-19 specific deaths, excess all-cause mortality is currently more appropriate for comparisons. By estimating age- and sex-specific death rates we aim to get more accurate estimates of the excess mortality attributed to Covid-19, as well as the difference between men and women in Sweden. Design: We make use of Swedish register data about total weekly deaths, total population at risk, and estimate age- and sex-specific weekly death rates for 2020 and the 5 previous years. The data is provided by Statistics Sweden. Results: From the first week of April and onwards, the death rates at all ages above 60 are higher than those in previous years in Sweden. Persons above age 80 are dis-proportionally more affected, and men suffer higher levels of excess mortality than women at all ages with 75% higher death rates for males and 50% higher for females. Current excess mortality corresponds to a decline in remaining life expectancy of 3 years for men and 2 years for women. Conclusion: The Covid-19 pandemic has so far had a clear and consistent effect on total mortality in Sweden, with male death rates being comparably more affected. What consequences the pandemic will eventually have on mortality and life expectancy will depend on the progression of the pandemic, the extent that some of the deaths would have occurred in the absence of the pandemic, only somewhat later, the consequences for other health conditions, as well as the health care sector at large.

Title: Trends in maternal and neonatal mortality in South Africa: a systematic review. Content: BACKGROUND Measuring and monitoring progress towards Millennium Development Goals (MDG) 4 and 5 required valid and reliable estimates of maternal and child mortality. In South Africa, there are conflicting reports on the estimates of maternal and neonatal mortality, derived from both direct and indirect estimation techniques. This study aimed to systematically review the estimates made of maternal and neonatal mortality in the period from 1990 to 2015 in South Africa and determine trends over this period. METHODS Nationally-representative studies reporting on maternal and neonatal mortality in South Africa were included for synthesis. Literature search for eligible studies was conducted in five electronic databases: Medline, Africa-Wide Information, Scopus, Web of Science and CINAHL. Searches were restricted to articles written in English and presenting data covering the period between 1990 and 2015. Reference lists of retrieved articles were screened for additional publications, and grey literature was searched for relevant documents for the review. Three independent reviewers were involved in study selection, data extractions and achieving consensus. RESULTS In total, 969 studies were retrieved and 670 screened for eligibility yielding 25 studies reporting data on maternal mortality and 14 studies on neonatal mortality. Most of the studies had a low risk of bias. Estimates from the institutional reporting differed from the international metrics with wide uncertainty/confidence intervals. Moreover, modelled estimates were widely divergent from estimates obtained through empirical methods. In the last two decades, both maternal and neonatal mortality appear to have increased up to 2009, followed by a decrease, more pronounced in the care of maternal mortality. CONCLUSION Estimates from both global metrics and institutional reporting, although widely divergent, indicate South Africa has not achieved MDG 4a and 5a goals but made a significant progress in reducing maternal and neonatal mortality. To obtain more accurate estimates, there is a need for applying additional estimation techniques which utilise available multiple data sources to correct for underreporting of these outcomes, perhaps the capture-recapture method. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42016042769.

Title: The confounded crude case-fatality rates for COVID-19 hide more than they reveal - a comparison of age-specific and age-adjusted rates between six countries Content: Background The reported crude case-fatality rates (CFRs) vary widely between countries. The serious limitations of using crude rates for comparisons are sometimes overlooked. In this paper we examined to what extent the age distribution of the cases is responsible for the differences in CFRs between countries. Methods Data on COVID-19 were extracted from the reports of individual countries. Overall and age-specific CFRs were available for six countries. The CFRs by country were adjusted for age using the direct method, using the combined age-specific number of cases of all six countries as the standard population. Findings The age distribution of the cases varied widely between countries. The crude CFRs varied between 1.6% and 11%. The differences in the age-specific CFRs were much smaller and the age-adjusted rates were much closer than the crude rates. The ratio of the crude CFR for the country with the highest to that with the lowest, was reduced substantially from 7.4 to 2.3 for the age-adjusted rates. Conclusions The age structure of the cases dramatically impacts on the differences in the crude CFRs between countries. Adjusting for age substantially reduces this variation. Other factors such as the differences in the definition of the denominators, the definition of a case and the standard of healthcare are likely to account for much of the residual variation. It is misleading to compare the crude COVID-19 CFRs between countries and should be avoided. Comparisons should be based on age-specific and age-adjusted rates. Key words: COVID-19, case-fatality rates, age-specific rates, age-adjusted rates, confounding

Title: Mortality, morbidity and health in developed societies: a review of data sources Content: The purpose of this paper is to review the major sources of data on mortality, morbidity and health in Europe and in other developed regions in order to examine their potential for analysing mortality and morbidity levels and trends. The review is primarily focused on routinely collected information covering a whole country. No attempt is made to draw up an inventory of sources by country; the paper deals instead with the pros and cons of each source for mortality and morbidity studies in demography. While each source considered separately can already yield useful, though partial, results, record linkage among data sources can significantly improve the analysis. Record linkage can also lead to the detection of possible causal associations that could eventually be confirmed. More generally, Big Data can reveal changing mortality and morbidity trends and patterns that could lead to preventive measures being taken rather than more costly curative ones.

Title: Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. Content: BACKGROUND Inclusion health focuses on people in extremely poor health due to poverty, marginalisation, and multimorbidity. We aimed to review morbidity and mortality data on four overlapping populations who experience considerable social exclusion: homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals. METHODS For this systematic review and meta-analysis, we searched MEDLINE, Embase, and the Cochrane Library for studies published between Jan 1, 2005, and Oct 1, 2015. We included only systematic reviews, meta-analyses, interventional studies, and observational studies that had morbidity and mortality outcomes, were published in English, from high-income countries, and were done in populations with a history of homelessness, imprisonment, sex work, or substance use disorder (excluding cannabis and alcohol use). Studies with only perinatal outcomes and studies of individuals with a specific health condition or those recruited from intensive care or high dependency hospital units were excluded. We screened studies using systematic review software and extracted data from published reports. Primary outcomes were measures of morbidity (prevalence or incidence) and mortality (standardised mortality ratios [SMRs] and mortality rates). Summary estimates were calculated using a random effects model. FINDINGS Our search identified 7946 articles, of which 337 studies were included for analysis. All-cause standardised mortality ratios were significantly increased in 91 (99%) of 92 extracted datapoints and were 11·86 (95% CI 10·42-13·30; I2=94·1%) in female individuals and 7·88 (7·03-8·74; I2=99·1%) in men. Summary SMR estimates for the International Classification of Diseases disease categories with two or more included datapoints were highest for deaths due to injury, poisoning, and other external causes, in both men (7·89; 95% CI 6·40-9·37; I2=98·1%) and women (18·72; 13·73-23·71; I2=91·5%). Disease prevalence was consistently raised across the following categories: infections (eg, highest reported was 90% for hepatitis C, 67 [65%] of 103 individuals for hepatitis B, and 133 [51%] of 263 individuals for latent tuberculosis infection), mental health (eg, highest reported was 9 [4%] of 227 individuals for schizophrenia), cardiovascular conditions (eg, highest reported was 32 [13%] of 247 individuals for coronary heart disease), and respiratory conditions (eg, highest reported was 9 [26%] of 35 individuals for asthma). INTERPRETATION Our study shows that homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals experience extreme health inequities across a wide range of health conditions, with the relative effect of exclusion being greater in female individuals than male individuals. The high heterogeneity between studies should be explored further using improved data collection in population subgroups. The extreme health inequity identified demands intensive cross-sectoral policy and service action to prevent exclusion and improve health outcomes in individuals who are already marginalised. FUNDING Wellcome Trust, National Institute for Health Research, NHS England, NHS Research Scotland Scottish Senior Clinical Fellowship, Medical Research Council, Chief Scientist Office, and the Central and North West London NHS Trust.

Title: Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Content: BACKGROUND Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). METHODS We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. FINDINGS The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. INTERPRETATION At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. FUNDING Bill & Melinda Gates Foundation.

Title: Calibrating Gompertz in reverse: What is your longevity-risk-adjusted global age?() Content: This paper develops a computational framework for inverting Gompertz–Makeham mortality hazard rates, consistent with compensation laws of mortality for heterogeneous populations, to define a longevity-risk-adjusted global (L-RaG) age. To illustrate its salience and possible applications, the paper calibrates and presents L-RaG values using country data from the Human Mortality Database (HMD). Among other things, the author demonstrates that when properly benchmarked, the longevity-risk-adjusted global age of a 55-year-old Swedish male is 48, whereas a 55-year-old Russian male is closer in age to 67. The paper also discusses the connection between the proposed L-RaG age and the related concept of Biological age, from the medical and gerontology literature. Practically speaking, in a world of growing mortality heterogeneity, the L-RaG age could be used for pension and retirement policy. In the language of behavioral finance and economics, a salient metric that adjusts chronological age for longevity risk might help capture the public’s attention, educate them about lifetime uncertainty and induce many of them to take action — such as working longer and/or retiring later.

Title: Use of the prevented fraction for the population to determine deaths averted by existing prevalence of physical activity: a descriptive study Content: BACKGROUND: Disease and mortality burdens of unhealthy lifestyle behaviours are often reported. In contrast, the positive narrative around the burdens that an existing behaviour have averted is rarely acknowledged. We aimed to estimate the prevented fraction for the population (PFP) for premature mortality averted by physical activity on a global scale. METHODS: In this descriptive study, we obtained previously published data on physical activity prevalence (2001–16) and relative risks of all-cause mortality for 168 countries. We combined the data in Monte-Carlo simulations to estimate country-specific, mean PFP values, corresponding to percentage of mortality averted, and their 95% CIs. High prevented fractions indicated an increased proportion of deaths averted due to physical activity. Using mortality data for all people in a country aged 40–74 years, we estimated the number of premature deaths averted for all adults and by gender. We present the median and range of the prevented fractions globally, by WHO region, and by World Bank income classification. FINDINGS: The global median PFP was 15·0% (range 6·6–20·5), conservatively equating to 3·9 million (95% CI 2·5–5·6) premature deaths averted annually. The African region had the highest median prevented fraction (16·6% [range 12·1–20·5]) and the Americas had the lowest (13·1% [10·8–16·6]). Low-income countries tended to have higher prevented fractions (group median 17·9% [12·3–20·5]) than high-income countries (14·1% [6·6–17·8]). Globally, the median prevented fraction was higher for men (16·0% [7·8–20·7] than women (14·1% [5·0–20·4]). INTERPRETATION: Existing physical activity prevalence has contributed to averting premature mortality across all countries. PFP has utility as an advocacy tool to promote healthy lifestyle behaviours. By making the case of what has been achieved, the prevented fraction can show the value of current investment and services, which might be conducive to political support. FUNDING: UK Medical Research Council, British Heart Foundation, Cancer Research UK, Economic and Social Research Council, National Institute for Health Research, Wellcome Trust, Heart Foundation Australia.

Title: The potential effect of the African population age structure on COVID-19 mortality Content: Currently (mid May 2020), most active cases of COVID-19 are found in Europe and North America while it is still in the initial phases in Africa. As COVID-19 mortality occurs mainly in elderly and as Africa has a comparably young population, the death rates should be lower than on other continents. We calculated standardised mortality ratios (SMR) using age-specific case fatality rates for COVID-19 and the age structure of the population of Africa and of other continents. Compared to a European or Northern American population, the standardised mortality ratio was only 0.22 and 0.25, respectively, corresponding to reduction of deaths rates to a quarter. Compared to the Asian and Latin American & Caribbean population, the SMR was 0.43 and 0.44, respectively, corresponding to half the death rate for Africa. It is useful to quantify the isolated effect of the African age-structure on potential COVID-19 mortality for illustrative and communication purposes, keeping in mind the importance of public health measures that have been shown to be effective in reducing cases and deaths. The different aspect of age pyramids of a European and an African population are striking and the potential implications for the pandemic are often discussed but rarely quantified.

Title: Black, Asian and Minority Ethnic groups in England are at increased risk of death from COVID-19: indirect standardisation of NHS mortality data. Content: Background: International and UK data suggest that Black, Asian and Minority Ethnic (BAME) groups are at increased risk of infection and death from COVID-19. We aimed to explore the risk of death in minority ethnic groups in England using data reported by NHS England. Methods: We used NHS data on patients with a positive COVID-19 test who died in hospitals in England published on 28th April, with deaths by ethnicity available from 1st March 2020 up to 5pm on 21 April 2020. We undertook indirect standardisation of these data (using the whole population of England as the reference) to produce ethnic specific standardised mortality ratios (SMRs) adjusted for age and geographical region. Results: The largest total number of deaths in minority ethnic groups were Indian (492 deaths) and Black Caribbean (460 deaths) groups. Adjusting for region we found a lower risk of death for White Irish (SMR 0.52; 95%CIs 0.45-0.60) and White British ethnic groups (0.88; 95%CIs 0.86-0.0.89), but increased risk of death for Black African (3.24; 95%CIs 2.90-3.62), Black Caribbean (2.21; 95%CIs 2.02-2.41), Pakistani (3.29; 95%CIs 2.96-3.64), Bangladeshi (2.41; 95%CIs 1.98-2.91) and Indian (1.70; 95%CIs 1.56-1.85) minority ethnic groups. Conclusion: Our analysis adds to the evidence that BAME people are at increased risk of death from COVID-19 even after adjusting for geographical region, but was limited by the lack of data on deaths outside of NHS settings and ethnicity denominator data being based on the 2011 census. Despite these limitations, we believe there is an urgent need to take action to reduce the risk of death for BAME groups and better understand why some ethnic groups experience greater risk. Actions that are likely to reduce these inequities include ensuring adequate income protection, reducing occupational risks, reducing barriers in accessing healthcare and providing culturally and linguistically appropriate public health communications.

Title: Estimated inequities in COVID-19 infection fatality rates by ethnicity for Aotearoa New Zealand Content: There is limited evidence as to how COVID-19 infection fatality rates (IFR) may vary by ethnicity. We combine demographic and health data for ethnic groupings in Aotearoa New Zealand with international data on IFR for different age groups to estimate inequities in IFR by ethnicity. We find that, if age is the dominant factor determining IFR, estimated IFR for Māori is around 50% higher than non-Māori. If underlying health conditions are more important than age per se, then estimated IFR for Māori is more than 2.5 times that of New Zealand European, and estimated IFR for Pasifika is almost double that of New Zealand European. IFRs for Māori and Pasifika are likely to be increased above these estimates by racism within the healthcare system and other inequities not reflected in official data. IFR does not account for differences among ethnicities in COVID-19 incidence, which could be higher in Māori and Pasifika as a result of crowded housing and higher inter-generational contact rates. These factors should be included in future disease incidence modelling. The communities at the highest risk will be those with elderly populations, and Māori and Pasifika communities, where the compounded effects of underlying health conditions, socioeconomic disadvantage, and structural racism result in imbricated risk of contracting COVID-19, becoming unwell, and death.

Title: Influenza-associated Deaths in Tropical Singapore Content: We used a regression model to examine the impact of influenza on death rates in tropical Singapore for the period 1996–2003. Influenza A (H3N2) was the predominant circulating influenza virus subtype, with consistently significant and robust effect on mortality rates. Influenza was associated with an annual death rate from all causes, from underlying pneumonia and influenza, and from underlying circulatory and respiratory conditions of 14.8 (95% confidence interval 9.8–19.8), 2.9 (1.0–5.0), and 11.9 (8.3–15.7) per 100,000 person-years, respectively. These results are comparable with observations in the United States and subtropical Hong Kong. An estimated 6.5% of underlying pneumonia and influenza deaths were attributable to influenza. The proportion of influenza-associated deaths was 11.3 times higher in persons age >65 years than in the general population. Our findings support the need for influenza surveillance and annual influenza vaccination for at-risk populations in tropical countries.

Title: Improved measurement of racial/ethnic disparities in COVID-19 mortality in the United States Content: Different estimation methods produce diverging accounts of racial/ethnic disparities in COVID-19 mortality in the United States. The Center for Disease Control's decision to present the racial/ethnic distribution of COVID-19 deaths at the state level alongside the weighted racial/ethnic distribution of the counties within each state reporting those death -- in effect, a geographic adjustment -- makes it seem that Whites have the highest death rates. Age adjustment procedures used by others, including the New York City Department of Health and Mental Hygiene, lead to the opposite conclusion that Blacks and Hispanics are dying from COVID-19 at higher rates than Whites. In this paper, we use indirect standardization methods to adjust per capita death rates for both age and geography simultaneously, avoiding the one-sided adjustment procedures currently in use. Using CDC data, we find age-and-place-adjusted COVID-19 death rates are 80% higher for Blacks and over 50% higher for Hispanics, relative to Whites, on a national level. State-specific estimates show wide variation in mortality disparities. Comparison with nonepidemic mortality reveals potential roles for preexisting health disparities and differential rates of infection and care.

Title: Death, Demography and the Denominator:New Influenza-18 Mortality Estimates for Ireland Content: Using the Irish experience of the Spanish flu, we demonstrate that pandemic mortality statistics are sensitive to the demographic composition of a country. We build a new demographic database for Ireland's 32 counties with vital statistics on births, ageing, migration and deaths. We then show how age-at-death statistics in 1918 and 1919 should be reinterpreted in light of these data. Our new estimates suggest the very young were most impacted by the flu. New studies of the economic impact of Influenza-18 must better control for demographic factors if they are to yield useful policy-relevant results. Covid-19 mortality statistics must go through a similar procedure so policymakers can better target their public health interventions.

Title: The effects of environmental stressors on the mortality of the oldest old male population in Hong Kong, 1977-2006. Content: Although age-sex-specific mortality rates were decreasing over the years, such a trend was not observed for the male population aged 85 or above (the oldest old) in Hong Kong. Despite literature suggesting that environmental stressors were associated with higher mortality, the adverse effects of socioeconomic and political events were seldom included. Hence, this study explored the relationship between environmental stressors covering adverse weather conditions as well as key socioeconomic and political events and fluctuations in the oldest old mortality rates in Hong Kong during the period 1977 to 2006. The oldest old mortality rates in Hong Kong were observed to have a likelihood of being associated with these environmental stressors. Furthermore, men appeared to be more susceptible to these risk factors than did women. More care and attention should be given to the oldest old men, in particular, during periods of socioeconomic or political upheavals. A cohort study would be useful to study these stressors in greater detail.

Title: Evidence for ethnic inequalities in mortality related to COVID-19 infections: Findings from an ecological analysis of England and Wales Content: Background In the absence of direct data on ethnic inequalities in COVID-19 related mortality in the UK, we examine the relationship between ethnic composition of an area and rate of mortality in the area. Methods Ecological analysis using COVID-19 related mortality rates occurring by 24th April 2020, and ethnic composition of the population, across local authorities in England and Wales. Account is taken of age, population density, area deprivation and pollution. Results For every 1% rise in proportion of the population who are ethnic minority, COVID-19 related deaths increased by 5.10 (3.99 to 6.21) per million. This rise is present for each ethnic minority category examined. The size of this increase is a little reduced in a fully adjusted model, suggesting that some of the association results from ethnic minority people living in more densely populated, more polluted and more deprived areas. This estimate suggests that the average England and Wales COVID-19 related death rate would rise by 25% in a local authority with twice the average number of ethnic minority people. Discussion We find clear evidence that rates of COVID-19 related mortality within a local authority increase as the proportion of the population who are ethnic minority increases. We suggest that this is a consequence of social and economic inequalities, including among key workers, driven by entrenched structural and institutional racism and racial discrimination. We argue that these factors should be central to any investigation of ethnic inequalities in COVID-19 outcomes.

Title: Black, Asian and Minority Ethnic groups in England are at increased risk of death from COVID-19: indirect standardisation of NHS mortality data Content: Background: International and UK data suggest that Black, Asian and Minority Ethnic (BAME) groups are at increased risk of infection and death from COVID-19. We aimed to explore the risk of death in minority ethnic groups in England using data reported by NHS England. Methods: We used NHS data on patients with a positive COVID-19 test who died in hospitals in England published on 28th April, with deaths by ethnicity available from 1st March 2020 up to 5pm on 21 April 2020. We undertook indirect standardisation of these data (using the whole population of England as the reference) to produce ethnic specific standardised mortality ratios (SMRs) adjusted for age and geographical region. Results: The largest total number of deaths in minority ethnic groups were Indian (492 deaths) and Black Caribbean (460 deaths) groups. Adjusting for region we found a lower risk of death for White Irish (SMR 0.52; 95%CIs 0.45-0.60) and White British ethnic groups (0.88; 95%CIs 0.86-0.0.89), but increased risk of death for Black African (3.24; 95%CIs 2.90-3.62), Black Caribbean (2.21; 95%CIs 2.02-2.41), Pakistani (3.29; 95%CIs 2.96-3.64), Bangladeshi (2.41; 95%CIs 1.98-2.91) and Indian (1.70; 95%CIs 1.56-1.85) minority ethnic groups. Conclusion: Our analysis adds to the evidence that BAME people are at increased risk of death from COVID-19 even after adjusting for geographical region. We believe there is an urgent need to take action to reduce the risk of death for BAME groups and better understand why some ethnic groups experience greater risk. Actions that are likely to reduce these inequities include ensuring adequate income protection (so that low paid and zero-hours contract workers can afford to follow social distancing recommendations), reducing occupational risks (such as ensuring adequate personal protective equipment), reducing barriers in accessing healthcare and providing culturally and linguistically appropriate public health communications.

Title: How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy Content: Objective: Overall mortality is a relevant indicator of the population burden during an epidemic. It informs on both undiagnosed cases and on the effects of health system disruption. Methods: We aimed at evaluating the extent of the total death excess during the COVID-19 epidemic in Italy. Data from 4433 municipalities providing mortality reports until April 15th, 2020 were included for a total of 34.5 million residents from all Italian regions. Data were analyzed by region, sex and age, and compared to expected from 2015–2019. Results: In both genders, overall mortality was stable until February 2020 and abruptly increased from March 1st onwards. Within the municipalities studied, 77,339 deaths were observed in the period between March 1st to April 15th, 2020, in contrast to the 50,822.6 expected. The rate ratio was 1.11 before age 60 and 1.55 afterwards. Both sexes were affected. The excess was greater in the regions most affected by COVID-19 but always exceeded the deaths attributed to COVID-19. The extrapolation to the total Italian population suggests an excess of 45,033 deaths in the study period, while the number of COVID–19 deaths was 21,046. Conclusion: Our paper shows a large death excess during the COVID-19 epidemic in Italy; greater than the number attributed to it. Possible causes included both the undetected cases and the disruption of the Health Service organization. Timely monitoring of overall mortality based on unbiased nationwide data is an essential tool for epidemic control.

Title: How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy Content: Objective: Overall mortality is a relevant indicator of the population burden during an epidemic. It informs on both undiagnosed cases and on the effects of health system disruption. Methods: We aimed at evaluating the extent of the total death excess during the COVID-19 epidemic in Italy. Data from 4433 municipalities providing mortality reports until April 15th, 2020 were included for a total of 34.5 million residents from all Italian regions. Data were analyzed by region, sex and age, and compared to expected from 2015-2019. Results: In both genders, overall mortality was stable until February 2020 and abruptly increased from March 1st onwards. Within the municipalities studied, 77,339 deaths were observed in the period between March 1st to April 15th, 2020, in contrast to the 50,822.6 expected. The rate ratio was 1.11 before age 60 and 1.55 afterwards. Both sexes were affected. The excess was greater in the regions most affected by COVID-19 but always exceeded the deaths attributed to COVID-19. The extrapolation to the total Italian population suggests an excess of 45,033 deaths in the study period, while the number of COVID-19 deaths was 21,046. Conclusion: Our paper shows a large death excess during the COVID-19 epidemic in Italy; greater than the number attributed to it. Possible causes included both the undetected cases and the disruption of the Health Service organization. Timely monitoring of overall mortality based on unbiased nationwide data is an essential tool for epidemic control.

Title: Long-term trends in seasonality of mortality in urban Madagascar: the role of the epidemiological transition Content: Background: Seasonal patterns of mortality have been identified in Sub-Saharan Africa but their changes over time are not well documented. Objective: Based on death notification data from Antananarivo, the capital city of Madagascar, this study assesses seasonal patterns of all-cause and cause-specific mortality by age groups and evaluates how these patterns changed over the period 1976–2015. Methods: Monthly numbers of deaths by cause were obtained from death registers maintained by the Municipal Hygiene Office in charge of verifying deaths before the issuance of burial permits. Generalized Additive Mixed regression models (GAMM) were used to test for seasonality in mortality and its changes over the last four decades, controlling for long-term trends in mortality. Results: Among children, risks of dying were the highest during the hot and rainy season, but seasonality in child mortality has significantly declined since the mid-1970s, as a result of declines in the burden of infectious diseases and nutritional deficiencies. In adults aged 60 and above, all-cause mortality rates are the highest in the dry and cold season, due to peaks in cardiovascular diseases, with little change over time. Overall, changes in the seasonality of all-cause mortality have been driven by shifts in the hierarchy of causes of death, while changes in the seasonality within broad categories of causes of death have been modest. Conclusion: Shifts in disease patterns brought about by the epidemiological transition, rather than changes in seasonal variation in cause-specific mortality, are the main drivers of trends in the seasonality of all-cause mortality.

Title: Beyond Deaths per Capita: Three CoViD-19 Mortality Indicators for Temporal and International Comparisons Content: CoViD-19 deaths to population size ratios fail to account for well-documented age and sex differences in CoViD-19 mortality. To assess trends across populations for which CoViD-19 deaths might not be available by age and sex, an indirect age-and-sex adjustment can still be performed. The corresponding Comparative CoViD-19 Mortality Ratio (CCMR) only requires population age and sex compositions. To compare CoViD-19 and overall mortality levels, the Crude Death Rate (CDR) and life expectancy at birth for recent calendar years are the most widely available overall mortality indicators. Readily comparable to an annual CDR, a Crude CoViD-19 Death Rate (CCDR) can be calculated for periods of any duration. CoViD-19-induced declines in projected life expectancy at birth for 2020 can also be calculated from existing life tables. We calculate the CCMR and CCDR for the period from their first CoViD-19 death to the present using US age and sex data and current estimates of CoViD-19 deaths in 166 Countries whose population composition is available from the UN, 28 Provinces in China, the 50 United States and DC. Across these 245 populations, 14 States and 11 Countries have CCMR values above 1—the US value by construction. Most affected to date, the period CCDR in New York exceeds its CDR for the most recent year available (7.83 per thousand in 2017). We also calculate CCMR and CCDR values corresponding to projections for the 50 States and DC, and for 49 countries, for which we can additionally calculate reductions in 2020 life expectancy at birth using UN life tables. This suggests life-expectancy reductions between .5 and 1 year for 7 European Countries, 3 South-American Countries and the US. The .55 reduction in the U.S. amounts to nearly twice the largest single-year decline induced by HIV/AIDS (−.3 between 1992 and 1993) or the total decline induced by opioid overdoses (also −.3 between 2014 and 2017), and would bring US life expectancy at birth down to its lowest level since 2008. As current CoViD-19 death counts likely underestimate the total increase in deaths and current projections do not account for possible new infection waves later this year, the impact on 2020 life expectancies at birth should be expected to exceed these figures.

Title: Did elderly people living in small towns or rural areas suffer heavier disease burden during the COVID-19 epidemic? Content: Background: Health disparities were often overlooked during the emerging epidemic. Objectives: This study examined geographic differences in the rates of health care use and deaths among elderly patients. Methods: Based on individual patient records, multivariate Poisson and logistic models were used to calculate adjusted incidences of COVID-19 and probabilities of emergency department (ED) visits, hospitalizations and deaths. Results: Of 8,203 elderly patients, 11% died. Elderly people living in small metropolitan areas were half as likely to be diagnosed with COVID-19. Elderly female patients living in small metropolitan areas had much lower rates of ED visits (23% vs. 34%; Odds Ratio (OR): 0.58; 95%confidence interval (CI): 0.41-0.81; p=0.002) and hospitalizations (22% vs. 31%; OR: 0.62; 95%CI: 0.44 - 0.87; p=0.006) than those living in large metropolitan areas. Furthermore, those living in non-metropolitan areas were more likely to be hospitalized than those living in large metropolitan areas (44% vs. 33%; OR: 1.46; 95%CI: 1.07-1.99; p=0.016), especially among elderly men (51% vs. 35%; OR:1.86; 95%CI: 1.18-2.93; p=0.008). Finally, there was a significant linear trend in hospitalization rates among elderly male patients (p for trend = 0.01). Conclusions: Profound health disparities exist in the time of emerging epidemic.

Title: Ethnic variations in morbidity and mortality from lower respiratory tract infections: a retrospective cohort study. Content: OBJECTIVE There is evidence of substantial ethnic variations in asthma morbidity and the risk of hospitalisation, but the picture in relation to lower respiratory tract infections is unclear. We carried out an observational study to identify ethnic group differences for lower respiratory tract infections. DESIGN A retrospective, cohort study. SETTING Scotland. PARTICIPANTS 4.65 million people on whom information was available from the 2001 census, followed from May 2001 to April 2010. MAIN OUTCOME MEASURES Hospitalisations and deaths (any time following first hospitalisation) from lower respiratory tract infections, adjusted risk ratios and hazard ratios by ethnicity and sex were calculated. We multiplied ratios and confidence intervals by 100, so the reference Scottish White population's risk ratio and hazard ratio was 100. RESULTS Among men, adjusted risk ratios for lower respiratory tract infection hospitalisation were lower in Other White British (80, 95% confidence interval 73-86) and Chinese (69, 95% confidence interval 56-84) populations and higher in Pakistani groups (152, 95% confidence interval 136-169). In women, results were mostly similar to those in men (e.g. Chinese 68, 95% confidence interval 56-82), although higher adjusted risk ratios were found among women of the Other South Asians group (145, 95% confidence interval 120-175). Survival (adjusted hazard ratio) following lower respiratory tract infection for Pakistani men (54, 95% confidence interval 39-74) and women (31, 95% confidence interval 18-53) was better than the reference population. CONCLUSIONS Substantial differences in the rates of lower respiratory tract infections amongst different ethnic groups in Scotland were found. Pakistani men and women had particularly high rates of lower respiratory tract infection hospitalisation. The reasons behind the high rates of lower respiratory tract infection in the Pakistani community are now required.

Title: Severe Acute Respiratory Illness Deaths in Sub-Saharan Africa and the Role of Influenza: A Case Series From 8 Countries Content: Background. Data on causes of death due to respiratory illness in Africa are limited. Methods. From January to April 2013, 28 African countries were invited to participate in a review of severe acute respiratory illness (SARI)–associated deaths identified from influenza surveillance during 2009–2012. Results. Twenty-three countries (82%) responded, 11 (48%) collect mortality data, and 8 provided data. Data were collected from 37 714 SARI cases, and 3091 (8.2%; range by country, 5.1%–25.9%) tested positive for influenza virus. There were 1073 deaths (2.8%; range by country, 0.1%–5.3%) reported, among which influenza virus was detected in 57 (5.3%). Case-fatality proportion (CFP) was higher among countries with systematic death reporting than among those with sporadic reporting. The influenza-associated CFP was 1.8% (57 of 3091), compared with 2.9% (1016 of 34 623) for influenza virus–negative cases (P < .001). Among 834 deaths (77.7%) tested for other respiratory pathogens, rhinovirus (107 [12.8%]), adenovirus (64 [6.0%]), respiratory syncytial virus (60 [5.6%]), and Streptococcus pneumoniae (57 [5.3%]) were most commonly identified. Among 1073 deaths, 402 (37.5%) involved people aged 0–4 years, 462 (43.1%) involved people aged 5–49 years, and 209 (19.5%) involved people aged ≥50 years. Conclusions. Few African countries systematically collect data on outcomes of people hospitalized with respiratory illness. Stronger surveillance for deaths due to respiratory illness may identify risk groups for targeted vaccine use and other prevention strategies.

Title: The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong Content: Human mortality is in part a function of multiple socioeconomic factors that differ both spatially and temporally. Adjusting for other covariates, the human lifespan is positively associated with household wealth. However, the extent to which mortality in a geographical region is a function of socioeconomic factors in both that region and its neighbors is unclear. There is also little information on the temporal components of this relationship. Using the districts of Hong Kong over multiple census years as a case study, we demonstrate that there are differences in how wealth indicator variables are associated with longevity in (a) areas that are affluent but neighbored by socially deprived districts versus (b) wealthy areas surrounded by similarly wealthy districts. We also show that the inclusion of spatially-distributed variables reduces uncertainty in mortality rate predictions in each census year when compared with a baseline model. Our results suggest that geographic mortality models should incorporate nonlocal information (e.g., spatial neighbors) to lower the variance of their mortality estimates, and point to a more in-depth analysis of sociospatial spillover effects on mortality rates.

Title: Differences in race and other state‐level characteristics and associations with mortality from COVID‐19 infection Content: As reporting of COVID‐19 at the US state level has become more granular, many states have reported a higher proportion of deaths among African‐Americans. In our study, we assessed state level data on race, population density, age, obesity rates, insurance data, GDP, per capita healthcare resources (hospital‐beds/ventilators per‐capita), median household income and high‐school graduation rates. We report a higher death rate among states with a greater proportion of African‐American residents despite adjusting for case rates and state‐level factors. To the best of our knowledge this is the first study looking at state level data (from across the US) and mortality with COVID‐19. This article is protected by copyright. All rights reserved.

Title: Serology-informed estimates of SARS-COV-2 infection fatality risk in Geneva, Switzerland Content: The infection fatality risk (IFR) is the average number of deaths per infection by a pathogen and is key to characterizing the severity of infection across the population and for specific demographic groups. To date, there are few empirical estimates of IFR published due to challenges in measuring infection rates. Outside of closed, closely surveilled populations where infection rates can be monitored through viral surveillance, we must rely on indirect measures of infection, like specific antibodies. Representative seroprevalence studies provide an important avenue for estimating the number of infections in a community, and when combined with death counts can lead to robust estimates of the IFR. We estimated overall and age-specific IFR for the canton of Geneva, Switzerland using age-stratified daily case and death incidence reports combined with five weekly population-based seroprevalence estimates. From February 24th to June 2nd there were 5'039 confirmed cases and 286 reported deaths within Geneva (population of 506'765). We inferred age-stratified (5-9, 10-19, 20-49, 50-65 and 65+) IFRs by linking the observed number of deaths to the estimated number of infected individuals from each serosurvey. We account for the delays between infection and seroconversion as well as between infection and death. Inference is drawn in a Bayesian framework that incorporates uncertainty in seroprevalence estimates (supplement). Of the 286 reported deaths caused by SARS-CoV-2, the youngest person to die was 31 years old. Infected individuals younger than 50 years experienced statistically similar IFRs (range 0.00032-0.0016%), which increases to 0.14% (95% CrI 0.096-0.19) for those 50-64 years old to 5.6% (95% CrI 4.3-7.4) for those 65 years and older (supplement). After accounting for demography and age-specific seroprevalence, we estimate a population-wide IFR of 0.64% (95% CrI 0.38-0.98). Our results are subject to two notable limitations. Among the 65+ age group that died of COVID-19 within Geneva, 50% were reported among residents of assisted care facilities, where around 0.8% of the Geneva population resides. While the serosurvey protocol did not explicitly exclude these individuals, they are likely to have been under-represented. This would lead to an overestimation of the IFR in the 65+ age group if seroprevalence in this institutionalized population was higher than in the general population (supplement). Further, our IFR estimates are based on current evidence regarding post-infection antibody kinetics, which may differ between severe and mild infections. If mild infections have significantly lower and short-lived antibody responses, our estimates of IFR may be biased upwards. Estimates of IFR are key for understanding the true pandemic burden and for weighing different risk reduction strategies. The IFR is not solely determined by host and pathogen biology, but also by the capacity of health systems to treat severe cases. Despite having among the highest per capita incidence in Switzerland, Geneva's health system accommodated the influx of cases needing intensive care (peak of 80/110 ICU-beds including surge capacity) while maintaining care quality standards. As such, our IFR estimates can be seen as a best-case scenario with respect to health system capacity. Our results reveal that population-wide estimates of IFR mask great heterogeneity by age and point towards the importance of age-targeted interventions to reduce exposures among those at highest risk of death.

Title: Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults Content: RAPID COMMUNICATION 22 March 2020 Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults Background: The medical, health service, societal and economic impact of the COVID-19 emergency has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom (to date at least) have underlying conditions. Models have not incorporated information on high risk conditions or their longer term background (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence rates and differing mortality impacts. Methods: Using population based linked primary and secondary care electronic health records in England (HDR UK - CALIBER), we report the prevalence of underlying conditions defined by UK Public Health England COVID-19 guidelines (16 March 2020) in 3,862,012 individuals aged ≥30 years from 1997-2017. We used previously validated phenotypes, openly available (https://caliberresearch.org/portal), for each condition using ICD-10 diagnosis, Read, procedure and medication codes. We estimated the 1-year mortality in each condition, and developed simple models of excess COVID-19-related deaths assuming relative risk (RR) of the impact of the emergency (compared to background mortality) of 1.2, 1.5 and 2.0. Findings: 20.0% of the population are at risk according to current PHE guidelines, of which; 13.7% were age>70 years and 6.3% aged ≤70 years with ≥1 underlying condition (cardiovascular disease (2.3%), diabetes (2.2%), steroid therapy (1.9%), severe obesity (0.9%), chronic kidney disease (0.6%) and chronic obstructive pulmonary disease, COPD (0.5%). Multimorbidity (co-occurrence of ≥2 conditions in an individual) was common (10.1%). The 1-year mortality in the at-risk population was 4.46%, and age and underlying conditions combine to influence background risk, varying markedly across conditions (5.9% in age>70 years, 8.6% for COPD and 13.1% in those with ≥3 or more conditions). In a suppression scenario (at SARS CoV2 rates of 0.001% of the UK population), there would be minimal excess deaths (3 and 7 excess deaths at relative risk, RR, 1.5 and 2.0 respectively). At SARS CoV2 rates of 10% of the UK population (mitigation) the model estimates the numbers of excess deaths as: 13791, 34479 and 68957 (at RR 1.2, 1.5 and 2.0 respectively). At SARS CoV2 rates of 80% in the UK population (do-nothing), the model estimates the number of excess deaths as 110332, 275,830 and 551,659 (at RR 1.2, 1.5 and 2.0) respectively. Interpretation: We provide the public, researchers and policy makers a simple model to estimate the excess mortality over 1 year from COVID-19, based on underlying conditions at different ages. If the relative mortality impact of COVID-19 were to be about 20% (similar magnitude as the established winter vs summer mortality excess), then the excess deaths would be 0 when 1 in 100 000 (suppression), 13791 when 1 in 10 (mitigation) and 110332 when 8 in 10 are infected (do nothing) scenario. However, the relative impact of COVID-19 is unknown. If the emergency were to double the mortality risk, then we estimate 7, 68957 and 551,659 excess deaths in the same scenarios. These results may inform the need for more stringent suppression measures as well as efforts to target those at highest risk for a range of preventive interventions.

Title: A Note on UK Covid19 death rates by religion: which groups are most at risk? Content: There has been great concern in the UK that people from the BAME (Black And Minority Ethnic) community have a far higher risk of dying from Covid19 than those of other ethnicities. However, the overall fatalities data from the Government's ONS (Office of National Statistics) most recent report on deaths by religion shows that Jews (very few of whom are classified as BAME) have a much higher risk than those of religions (Hindu, Sikh, Muslim) with predominantly BAME people. This apparently contradictory result is, according to the ONS statistical analysis, implicitly explained by age as the report claims that, when 'adjusted for age' Muslims have the highest fatality risk. However, the report fails to provide the raw data to support this. There are many factors other than just age that must be incorporated into any analysis of the observed data before making definitive conclusions about risk based on religion/ethnicity. We propose the need for a causal model for this. If we discount unknown genetic factors, then religion and ethnicity have NO impact at all on a person's Covid19 death risk once we know their age, underlying medical conditions, work/living conditions, and extent of social distancing.

Title: Racial and Ethnic Disparities in Population Level Covid-19 Mortality Content: Background: Current reporting of Covid-19 mortality data by race and ethnicity across the United States could bias our understanding of population-mortality disparities. Moreover, stark differences in age distribution by race and ethnicity groups are seldom accounted for in analyses. Methods: To address these gaps, we conducted a cross-sectional study using publicly-reported Covid-19 mortality data to assess the quality of race and ethnicity data (Black, Latinx, white), and estimated age-adjusted disparities using a random effects meta-analytic approach. Results: We found only 28 states, and NYC, reported race and ethnicity-stratified Covid-19 mortality along with large variation in the percent of missing race and ethnicity data by state. Aggregated relative risk of death estimates for Black compared to the white population was 3.57 (95% CI: 2.84-4.48). Similarly, Latinx population displayed 1.88 (95% CI: 1.61-2.19) times higher risk of death than white patients. Discussion: In states providing race and ethnicity data, we identified significant population-level Covid-19 mortality disparities. We demonstrated the importance of adjusting for age differences across population groups to prevent underestimating disparities in younger population groups. The availability of high-quality and comprehensive race and ethnicity data is necessary to address factors contributing to inequity in Covid-19 mortality.

Title: TRACKing Excess Deaths (TRACKED): an interactive online tool to monitor excess deaths associated with COVID-19 pandemic in the United Kingdom Content: Aim: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.

Title: Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study Content: BACKGROUND: The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. METHODS: In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. FINDINGS: We included 3â862â012 individuals (1â957â935 [50·7%] women and 1â904â077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41-4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18â374 excess deaths with an RR of 1·5, 36â749 with an RR of 2·0, and 73â498 with an RR of 3·0. In a do nothing scenario, we estimated 146â996 excess deaths with an RR of 1·5, 293â991 with an RR of 2·0, and 587â982 with an RR of 3·0. INTERPRETATION: We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. FUNDING: National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.

Title: Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study Content: BACKGROUND: The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. METHODS: In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK–CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. FINDINGS: We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41–4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. INTERPRETATION: We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. FUNDING: National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.

Title: The Longevity-Frailty Hypothesis: Evidence from COVID-19 Death Rates in Europe Content: COVID-19 death rates vary strikingly across Europe. The death rate in Spain, for example, is greater than the death rate in Germany by more than a factor of ten. Few if any epidemiological indicators distinguish the countries of Europe by such a vast margin. Evidence on age-specific case-fatality rates (deaths over observed infections) and age-specific death rates (deaths over population) indicate that COVID-19 disproportionately afflicts the elderly and frail, suggesting that the share of elderly population (≥ 65 years of age) in a country ought to be a strong predictor of the COVID-19 death rate. However, the COVID-19 death rate and the share of elderly population are statistically uncorrelated (r = 0.163, p = 0.399). Share of population ≥ 65 years of age is confounded by mortality selection, as well as other demographic dynamics. By contrast, elderly longevity or life expectancy at 65 more effectively captures population survival and the accumulation of age-related frailty in society. We find a strong statistical relationship between the COVID-19 death rate (r = 0.839, p < .001) and elderly longevity, and a moderately strong relationship between the date of epidemic timing and elderly longevity (r = −0.634, p < .001). These relationships are robust to the inclusion of statistical controls for international tourism inflow and hospital bed capacity. While the countries of Europe vary meaningfully in healthcare system capacity and in the timing and intensity of non-pharmaceutical interventions, the striking variation in COVID-19 death rates across these countries is statistically and intuitively associated with elderly survival and consequent frailty.

Title: Health Inequalities, General Trends in Mortality and Morbidity, and Associated Factors Content: All measures of health status are ultimately derived from observations of individuals. At the field level we have such measures as self-assessed health status, report of a specific disease, record of a particular death, or an individual’s test on a biomarker, such as blood pressure or serum cholesterol. The observations for individuals are combined and summarized to represent subnational geographic areas, demographic or socioeconomic groups within countries, or national populations. The summary measures, whether they are percentages, averages, or rates, apply to groups. A problem arises when the measures that are based on groups are assumed to represent individuals. The analysis becomes especially problematic when the units analyzed are geographic areas and inferences are being made about individuals from the analysis for these geographic areas.

Title: Pathogen Genomics and the Potential for Understanding Diseases in the Developing World Content: Approximately 46% and 32% of deaths among children under five globally occur in sub-Saharan Africa and South Asia, respectively. Over 80% of the 4.2 million child deaths in Africa are caused by infectious diseases, sharply contrasted to Europe where 39% of the 0.15 million child deaths are attributable to infectious diseases (Fig. 5.1) (Black et al. 2010). Hence, despite the remarkable public health advancements in hygiene, sanitation, antimicrobial drugs and vaccine strategies of the twenty-first century, the burden of infectious diseases remains unacceptably high in the developing world.

Title: Age-specific and sex-specific morbidity and mortality from avian influenza A(H7N9) Content: Abstract We used data on age and sex for 136 laboratory confirmed human A(H7N9) cases reported as of 11 August 2013 to compare age-specific and sex-specific patterns of morbidity and mortality from the avian influenza A(H7N9) virus with those of the avian influenza A(H5N1) virus. Human A(H7N9) cases exhibit high degrees of age and sex bias: mortality is heavily biased toward males >50 years, no deaths have been reported among individuals <25 years old, and relatively few cases documented among children or adolescents. The proportion of fatal cases (PFC) for human A(H7N9) cases as of 11 August 2013 was 32%, compared to a cumulative PFC for A(H5N1) of 83% in Indonesia and 36% in Egypt. Approximately 75% of cases of all A(H7N9) cases occurred among individuals >45 years old. Morbidity and mortality from A(H7N9) are lowest among individuals between 10 and 29 years, the age group which exhibits the highest cumulative morbidity and case fatality rates from A(H5N1). Although individuals <20 years old comprise nearly 50% of all human A(H5N1) cases, only 7% of all reported A(H7N9) cases and no deaths have been reported among individuals in this age group. Only 4% of A(H7N9) cases occurred among children<5 years old, and only one case from the 10 to 20 year age group. Age- and sex-related differences in morbidity and mortality from emerging zoonotic diseases can provide insights into ecological, economic, and cultural factors that may contribute to the emergence and proliferation of novel zoonotic diseases in human populations.

Title: Diagnoses made in an Emergency Department in rural sub-Saharan Africa. Content: BACKGROUND Information on diagnoses made in emergency departments situated in rural sub-Saharan Africa is scarce. The aim was: to evaluate the frequency of different diagnoses made in a new emergency department to define relevant healthcare requirements; and to find out if in-hospital mortality rates would decrease after the implementation of the emergency department. METHODS In this observational study, we prospectively collated diagnoses of all patients presenting to the emergency department of the St Francis Referral Hospital in Ifakara, Tanzania during 1 year. In addition, we compared in-hospital mortality rates before and after the implementation of the emergency department. RESULTS From July 2016 through to June 2017, a total of 35,903 patients were included. The median age was 33.6 years (range 1 day to 100 years), 57% were female, 25% were children <5 years, 4% were pregnant and 9% were hospitalised. The most common diagnoses were respiratory tract infection (12.6%), urinary tract infection (11.4%), trauma (9.8%), undifferentiated febrile illness (5.4%), and malaria (5.2%). The most common clinical diagnoses per age group were: lower respiratory tract infection (16.1%) in children <5 years old; trauma (21.6%) in 5- to 17-year-olds; urinary tract infection (13.5%) in 18- to 50-year-olds; and hypertensive emergency (12.4%) in >50-year-olds. Respiratory tract infections peaked in April during the rainy season, whereas malaria peaked 3 months after the rainy season. In-hospital mortality rates did not decrease during the study period (5.6% in 2015 vs 7.6% in 2017). CONCLUSIONS The majority of diagnosed disorders were of infectious or traumatic origin. The majority of febrile illnesses were poorly defined because of the lack of diagnostic methods. Trauma systems and inexpensive accurate diagnostic methods for febrile illnesses are needed in rural sub-Saharan Africa.

Title: Age-Specific Excess Mortality Patterns During the 1918–1920 Influenza Pandemic in Madrid, Spain Content: Although much progress has been made to uncover age-specific mortality patterns of the 1918 influenza pandemic in populations around the world, more studies in different populations are needed to make sense of the heterogeneous death impact of this pandemic. We assessed the absolute and relative magnitudes of 3 pandemic waves in the city of Madrid, Spain, between 1918 and 1920, on the basis of age-specific all-cause and respiratory excess death rates. Excess death rates were estimated using a Serfling model with a parametric bootstrapping approach to calibrate baseline death levels with quantified uncertainty. Excess all-cause and pneumonia and influenza mortality rates were estimated for different pandemic waves and age groups. The youngest and oldest persons experienced the highest excess mortality rates, and young adults faced the highest standardized mortality risk. Waves differed in strength; the peak standardized mortality risk occurred during the herald wave in spring 1918, but the highest excess rates occurred during the fall and winter of 1918/1919. Little evidence was found to support a “W”-shaped, age-specific excess mortality curve. Acquired immunity may have tempered a protracted fall wave, but recrudescent waves following the initial 2 outbreaks heightened the total pandemic mortality impact.

Title: Are men dying more than women by COVID-19? Content: We aimed to clarify if the infection and death rate by COVID-19 differ among gender in the top 50 countries with the highest death rates. Also, we investigated if secondary variables such as HDI, number of hospital beds, average age, temperature, percentage of elderly, smoker and obesity are contributing to the variability observed among countries. Meta-analyses and meta-regressions approaches were applied to official public data reported by the Word Health Organization and governments until May, 2020. A random effect model was used for the meta-analysis and heterogeneity was calculated by I2 statistic. There was not significative difference between men and women to be infected by COVID-19 (P = 0.42), though a significative difference was observed for death rate (P < 0.0001). High heterogeneity was observed among countries. For both infection and death rates this variability was mainly explained by the HDI (42.3% and 54.2%), average age (40.9% and 40.3%) and temperature (30.1% and 39.3%). Man are dying more than women around the word by COVID-19. Countries with highest HDI present less difference between sexes. These results reinforce that public politics promoting social isolation, health care and general well-being of the population are key factors in combating COVID-19.

Title: Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters Content: OBJECTIVE: To provide estimates of the relative rate of COVID-19 death in people <65 years old versus older individuals in the general population, the absolute risk of COVID-19 death at the population level during the first epidemic wave, and the proportion of COVID-19 deaths in non-elderly people without underlying diseases in epicenters of the pandemic. ELIGIBLE DATA: Cross-sectional survey of countries and US states with at least 800 COVID-19 deaths as of April 24, 2020 and with information on the number of deaths in people with age <65. Data were available for 14 countries (Belgium, Canada, France, Germany, India, Ireland, Italy, Mexico, Netherlands, Portugal, Spain, Sweden, Switzerland, UK) and 13 US states (California, Connecticut, Florida, Georgia, Illinois, Indiana, Louisiana, Maryland, Massachusetts, Michigan, New Jersey, New York, Pennsylvania). We also examined available data on COVID-19 deaths in people with age <65 and no underlying diseases. MAIN OUTCOME MEASURES: Proportion of COVID-19 deaths in people <65 years old; relative mortality rate of COVID-19 death in people <65 versus ≥65 years old; absolute risk of COVID-19 death in people <65 and in those ≥80 years old in the general population as of June 17, 2020; absolute COVID-19 mortality rate expressed as equivalent of mortality rate from driving a motor vehicle. RESULTS: Individuals with age <65 account for 4.5–11.2% of all COVID-19 deaths in European countries and Canada, 8.3–22.7% in the US locations, and were the majority in India and Mexico. People <65 years old had 30- to 100-fold lower risk of COVID-19 death than those ≥65 years old in 11 European countries and Canada, 16- to 52-fold lower risk in US locations, and less than 10-fold in India and Mexico. The absolute risk of COVID-19 death as of June 17, 2020 for people <65 years old in high-income countries ranged from 10 (Germany) to 349 per million (New Jersey) and it was 5 per million in India and 96 per million in Mexico. The absolute risk of COVID-19 death for people ≥80 years old ranged from 0.6 (Florida) to 17.5 per thousand (Connecticut). The COVID-19 mortality rate in people <65 years old during the period of fatalities from the epidemic was equivalent to the mortality rate from driving between 4 and 82 miles per day for 13 countries and 5 states, and was higher (equivalent to the mortality rate from driving 106–483 miles per day) for 8 other states and the UK. People <65 years old without underlying predisposing conditions accounted for only 0.7–3.6% of all COVID-19 deaths in France, Italy, Netherlands, Sweden, Georgia, and New York City and 17.7% in Mexico. CONCLUSIONS: People <65 years old have very small risks of COVID-19 death even in pandemic epicenters and deaths for people <65 years without underlying predisposing conditions are remarkably uncommon. Strategies focusing specifically on protecting high-risk elderly individuals should be considered in managing the pandemic.

Title: Changing pattern of premature mortality burden over 6 years of rapid growth of the economy in suburban south-west China: 1998–2003 Content: Summary Background This study was conducted in Kunming, the capital of Yunnan, a poor province in south-west China experiencing rapid economic growth. The study examined the short-term trend in premature mortality burden from common causes of death in a suburban region between 1998 and 2003. Methods Years of life lost (YLL) per 1000 population and mortality rate per 100,000 population were calculated from medical death certificates, and broken down by cause of death, sex and year without age weighting but with a discounting rate of 3%. Results Non-communicable diseases contributed over 80% of all causes of YLL, with a slightly increasing trend. The combined rate for communicable, maternal, prenatal and nutritional deficiencies declined from 4.7 to 2.4 per 1000 population. Remarkably, declining trends in YLL were also seen for chronic obstructive pulmonary disease, drug use and road traffic accidents, whereas increasing trends were seen for ischaemic heart disease (IHD) and liver cancer (males). The YLL rate for stroke, self-inflicted injuries, lung cancer and stomach cancer fluctuated over time. Conclusions The region should focus on further control of IHD and liver cancer.

Title: Erratum: COVID-19, Australia: Epidemiology Report 15 (Reporting week to 23:59 AEST 3 May 2020) Content: An error in data processing resulted in the tabulation of incorrect crude case fatality rate values, for age groups of 50-59 and above, in Table 5 (Crude Case Fatality Rate of all cases and hospitalised cases, by age group) as originally published in the COVID-19 (Australia) epidemiology report 14. The table below provides the corrected values.

Title: Erratum: COVID-19, Australia: Epidemiology Report 15 (Reporting week to 23:59 AEST 3 May 2020). Content: An error in data processing resulted in the tabulation of incorrect crude case fatality rate values, for age groups of 50-59 and above, in Table 5 (Crude Case Fatality Rate of all cases and hospitalised cases, by age group) as originally published in the COVID-19 (Australia) epidemiology report 14. The table below provides the corrected values.

Title: Homicide rates among persons aged 10-24 years - United States, 1981-2010. Content: Homicide disproportionately affects persons aged 10-24 years in the United States and consistently ranks in the top three leading causes of death in this age group, resulting in approximately 4,800 deaths and an estimated $9 billion in lost productivity and medical costs in 2010. To investigate trends in homicide among persons aged 10-24 years for the period 1981-2010, CDC analyzed National Vital Statistics System data on deaths caused by homicide of persons in this age group and examined trends by sex, age, race/ethnicity, and mechanism of injury. This report describes the results of that analysis, which indicated that homicide rates varied substantially during the study period, with a sharp rise from 1985 to 1993 followed by a decline that has slowed since 1999. During the period 2000-2010, rates declined for all groups, although the decline was significantly slower for males compared with females and for blacks compared with Hispanics and persons of other racial/ethnic groups. By mechanism of injury, the decline for firearm homicides from 2000 to 2010 was significantly slower than for nonfirearm homicides. The homicide rate among persons aged 10-24 years in 2010 was 7.5 per 100,000, the lowest in the 30-year study period. Primary prevention strategies remain critical, particularly among groups at increased risk for homicide.

Title: The male excess in case-fatality rates for COVID-19. A meta-analytic study of the age-related differences and consistency over six countries Content: Background Early in the COVID-19 pandemic, it was noted that males seemed to be more affected than females. We examined the magnitude and consistency of the sex differences in age-specific case-fatality rates (CFRs) in six countries. Methods Data on the cases and deaths from COVID-19, by sex and age group, were extracted from the published reports from Denmark, England, Israel, Italy, Spain, and the United States . Age-specific CFRs were computed for males and females separately. The ratio of the male to female CFRs were computed and meta-analytic methods were used to obtained pooled estimates of the male to female ratio of the CFRs over the six countries, for seven age-groups. Findings The CFRs were consistently higher in males at all ages. The differences were greater in the younger age groups. The pooled M:F CFR ratios were 2.53, 2.92, 2.57, 1.83, 1.57, 1.58 and 1.48 for ages 0-39, 40-49, 50-59, 60-69, 70-79, 80-89 and 90+. There was remarkable consistency between countries in the magnitude of the M:F CFRs, in each age group. In meta-regression, age group explained almost all the heterogeneity in the CFR ratios. Conclusions The sex differences in the CFRs are intriguing and are compatible with the male dominance in the incidence rates of many infectious diseases. For COVID-19, factors such as sex differences in the prevalence of underlying diseases may play a part in the CFR differences. However, the greater severity of the disease in males, particularly at younger ages, may be part of the disease mechanism and should be explored further.

Title: Racial/ethnic disparities in fatal unintentional drowning among persons aged ≤ 29 years - United States, 1999-2010. Content: In the United States, almost 4,000 persons die from drowning each year. Drowning is responsible for more deaths among children aged 1-4 years than any other cause except congenital anomalies. For persons aged ≤29 years, drowning is one of the top three causes of unintentional injury death (2). Previous research has identified racial/ethnic disparities in drowning rates. To describe these differences by age of decedent and drowning setting, CDC analyzed 12 years of combined mortality data from 1999-2010 for those aged ≤29 years. Among non-Hispanics, the overall drowning rate for American Indians/Alaska Natives (AI/AN) was twice the rate for whites, and the rate for blacks was 1.4 times the rate for whites. Disparities were greatest in swimming pools, with swimming pool drowning rates among blacks aged 5-19 years 5.5 times higher than those among whites in the same age group. This disparity was greatest at ages 11-12 years; at these ages, blacks drown in swimming pools at 10 times the rate of whites. Drowning prevention strategies include using barriers (e.g., fencing) and life jackets, actively supervising or lifeguarding, teaching basic swimming skills and performing bystander cardiopulmonary resuscitation (CPR). The practicality and effectiveness of these strategies varies by setting; however, basic swimming skills can be beneficial across all settings.

Title: A Chain Multinomial Model for Estimating the Real-Time Fatality Rate of a Disease, with an Application to Severe Acute Respiratory Syndrome Content: It is well known that statistics using cumulative data are insensitive to changes. World Health Organization (WHO) estimates of fatality rates are of the above type, which may not be able to reflect the latest changes in fatality due to treatment or government policy in a timely fashion. Here, the authors propose an estimate of a real-time fatality rate based on a chain multinomial model with a kernel function. It is more accurate than the WHO estimate in describing fatality, especially earlier in the course of an epidemic. The estimator provides useful information for public health policy makers for understanding the severity of the disease or evaluating the effects of treatments or policies within a shorter time period, which is critical in disease control during an outbreak. Simulation results showed that the performance of the proposed estimator is superior to that of the WHO estimator in terms of its sensitivity to changes and its timeliness in reflecting the severity of the disease.

Title: Global Variability in Reported Mortality for Critical Illness during the 2009-10 Influenza A(H1N1) Pandemic: A Systematic Review and Meta-Regression to Guide Reporting of Outcomes during Disease Outbreaks Content: PURPOSE: To determine how patient, healthcare system and study-specific factors influence reported mortality associated with critical illness during the 2009–2010 Influenza A (H1N1) pandemic. METHODS: Systematic review with meta-regression of studies reporting on mortality associated with critical illness during the 2009–2010 Influenza A (H1N1) pandemic. DATA SOURCES: Medline, Embase, LiLACs and African Index Medicus to June 2009-March 2016. RESULTS: 226 studies from 50 countries met our inclusion criteria. Mortality associated with H1N1-related critical illness was 31% (95% CI 28–34). Reported mortality was highest in South Asia (61% [95% CI 50–71]) and Sub-Saharan Africa (53% [95% CI 29–75]), in comparison to Western Europe (25% [95% CI 22–30]), North America (25% [95% CI 22–27]) and Australia (15% [95% CI 13–18]) (P<0.0001). High income economies had significantly lower reported mortality compared to upper middle income economies and lower middle income economies respectively (P<0.0001). Mortality for the first wave was non-significantly higher than wave two (P = 0.66). There was substantial variability in reported mortality among the specific subgroups of patients: unselected critically ill adults (27% [95% CI 24–30]), acute respiratory distress syndrome (37% [95% CI 32–44]), acute kidney injury (44% [95% CI 26–64]), and critically ill pregnant patients (10% [95% CI 5–19]). CONCLUSION: Reported mortality for outbreaks and pandemics may vary substantially depending upon selected patient characteristics, the number of patients described, and the region and economic status of the outbreak location. Outcomes from a relatively small number of patients from specific regions may lead to biased estimates of outcomes on a global scale.

Title: Non‐parametric estimation of the case fatality ratio with competing risks data: an application to Severe Acute Respiratory Syndrome (SARS) Content: For diseases with some level of associated mortality, the case fatality ratio measures the proportion of diseased individuals who die from the disease. In principle, it is straightforward to estimate this quantity from individual follow‐up data that provides times from onset to death or recovery. In particular, in a competing risks context, the case fatality ratio is defined by the limiting value of the sub‐distribution function, F (1)(t) = Pr(T ⩽t and J = 1), associated with death, as t → ∞, where T denotes the time from onset to death (J = 1) or recovery (J = 2). When censoring is present, however, estimation of F (1)(∞) is complicated by the possibility of little information regarding the right tail of F (1), requiring use of estimators of F (1)(t(*)) or F (1)(t (*))/(F (1)(t (*))+F (2)(t (*))) where t (*) is large, with F (2)(t) = Pr(T ⩽t and J = 2) being the analogous sub‐distribution function associated with recovery. With right censored data, the variability of such estimators increases as t (*) increases, suggesting the possibility of using estimators at lower values of t (*) where bias may be increased but overall mean squared error be smaller. These issues are investigated here for non‐parametric estimators of F (1) and F (2). The ideas are illustrated on case fatality data for individuals infected with Severe Acute Respiratory Syndrome (SARS) in Hong Kong in 2003. Copyright © 2006 John Wiley & Sons, Ltd.

Title: Trends in Infectious Disease Mortality, South Korea, 1983–2015 Content: We used national statistics from 1983–2015 to evaluate trends in mortality caused by infectious diseases in South Korea. Age-standardized mortality from infectious disease decreased from 43.5/100,000 population in 1983 to 16.5/100,000 in 1996, and then increased to 44.6/100,000 in 2015. Tuberculosis was the most common cause of death in 1983 and respiratory tract infections in 2015. We observed a significant decline in infant deaths caused by infectious diseases, but mortality in persons age >65 years increased from 135 deaths/100,000 population in 1996 to 307/100,000 in 2015. The relative inequality indices for respiratory tract infections, sepsis, and tuberculosis tended to increase over time. Although substantial progress has been achieved in terms of infant mortality, death rates from infectious disease has not decreased overall. Elderly populations with lower education levels and subgroups susceptible to respiratory infections and sepsis should be the focus of preventive policies.

Title: Disparities in premature deaths from heart disease--50 States and the District of Columbia, 2001. Content: In 2001, heart disease accounted for approximately 29.0% of deaths among U.S. residents; 16.8% of those deaths occurred among persons aged <65 years. Although mortality rates from heart disease have decreased, the decline has not been uniform for all populations. One of the two overall national health objectives for 2010 is to eliminate health disparities among different segments of the U.S. population. To better understand these disparities, CDC analyzed death certificate data for premature deaths from heart disease occurring in 2001. This report summarizes the results of that analysis, which indicated that the proportion of premature heart disease deaths varied by state and was higher among blacks, American Indians/Alaska Natives (AI/ANs), Asians/Pacific Islanders (A/PIs), and Hispanics. Reducing premature death from heart disease and eliminating disparities will require preventing, detecting, treating, and controlling risk factors for heart disease in young and middle-aged adults.

Title: Is investing in religious institutions a viable pathway to reduce mortality in the population? Content: There is established and consistent findings from epidemiologic studies, among individuals, that religion— broadly assessed through frequency of attending worship services—is associated with lower all-cause and cause-specific mortality attributed to suicide, alcohol, cardiovascular disease and cancer. Religious norms, social support, character, virtue, compassion, love, generosity, and religious community are among some mechanisms purported to explain lower mortality, on aggregate. The religious ecology or characteristics of religion within an area or geographic level (e.g., county, ZIP-code, country), has been linked with overall and cause-specific mortality, but directions of findings are mixed. Mechanisms to explain the links between the religious ecology and mortality included social integration, civic engagement, and social control. The manuscript (SSM-D-19-03928R2) adds a fresh and timely perspective by investigating another mechanism: investment in local healthcare spending. The study found some support of an indirect association from county-level religious denominational composition, through investments in health spending, on Black and White all-cause mortality rates. Should society or government invest finances in religious institutions to indirectly improve population health? This work adds evidence to debate that question. Future work on the topic will need to address several conceptual and methodological challenges. Conceptually, is investigating the market share of religious denominations (i.e., % Catholics vs % Protestants) relevant today given diversity in population and declining trends of worship attendance? Is mortality the most relevant for moving policy or should the focus be on well-being? Methodologically, are there alternate observable measures religious investments/spending in the local economy? Mechanisms, challenges, and opportunities for social epidemiology research on this topic are discussed.

Title: What does and does not correlate with COVID-19 death rates Content: We correlate county-level COVID-19 death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates. The correlation between driving into work, relative to telecommuting, and death rates is also positive across both models, but statistically significant only when we look across states and counties. We also find that a higher share of people not working, and thus not commuting either because they are elderly, children or unemployed, is correlated with higher death rates. Counties with higher home values, higher summer temperatures, and lower winter temperatures have higher death rates. Contrary to past work, we do not find a correlation between pollution and death rates. Also importantly, we do not find that death rates are correlated with obesity rates, ICU beds per capita, or poverty rates. Finally, our model that looks within states yields estimates of how a given state's death rate compares to other states after controlling for the variables included in our model; this may be interpreted as a measure of how states are doing relative to others. We find that death rates in the Northeast are substantially higher compared to other states, even when we control for the four sets of variables above. Death rates are also statistically significantly higher in Michigan, Louisiana, Iowa, Indiana, and Colorado. California's death rate is the lowest across all states.

Title: Thermal stress associated mortality risk and effect modification by sex and obesity in an elderly cohort of Chinese in Hong Kong Content: We assessed the effects of apparent temperature (AT) on mortality and the effect modifications attributable to individual characteristics in Hong Kong with subtropical climate conditions. Two datasets are used for analyses: one from mortality data of the general elderly population in 1998–2009; the other from an elderly cohort with 66,820 subjects recruited in 1998–2001 with mortality outcomes followed up until 2009. We found that AT below 20.8 °C was associated with an increase in mortality risk of 1.99% (95% confidence interval: 0.64%, 2.64%) for all causes, 2.48% (0.57%, 4.36%) for cardiovascular disease, and 3.19% (0.59%, 5.73%) for respiratory disease for every 1 °C decrease in AT over the following 3 days. The associations were modified by sex and body mass index, in particular stronger associations were observed for females and for obese subjects.

Title: Incidence and Mortality Rates of Disasters and Mass Casualty Incidents in Korea: A Population-Based Cross-Sectional Study, 2000-2009 Content: The objective of study was to evaluate the incidence and mortality rates of disasters and mass casualty incidents (MCIs) over the past 10 yr in the administrative system of Korea administrative system and to examine their relationship with population characteristics. This was a population-based cross-sectional study. We calculated the nationwide incidence, as well as the crude mortality and injury incidence rates, of disasters and MCIs. The data were collected from the administrative database of the National Emergency Management Agency (NEMA) and from provincial fire departments from January 2000 to December 2009. A total of 47,169 events were collected from the NEMA administrative database. Of these events, 115 and 3,079 cases were defined as disasters and MCIs that occurred in Korea, respectively. The incidence of technical disasters/MCIs was approximately 12.7 times greater than that of natural disasters/MCIs. Over the past 10 yr, the crude mortality rates for disasters and MCIs were 2.36 deaths per 100,000 persons and 6.78 deaths per 100,000 persons, respectively. The crude injury incidence rates for disasters and MCIs were 25.47 injuries per 100,000 persons and 152 injuries per 100,000 persons, respectively. The incidence and mortality of disasters/MCIs in Korea seem to be low compared to that of trend around the world.

Title: Epidemiology of Traumatic Brain Injury in Europe: A Living Systematic Review. Content: This systematic review provides a comprehensive, up-to-date summary of traumatic brain injury (TBI) epidemiology in Europe, describing incidence, mortality, age, and sex distribution, plus severity, mechanism of injury, and time trends. PubMed, CINAHL, EMBASE, and Web of Science were searched in January 2015 for observational, descriptive, English language studies reporting incidence, mortality, or case fatality of TBI in Europe. There were no limitations according to date, age, or TBI severity. Methodological quality was assessed using the Methodological Evaluation of Observational Research checklist. Data were presented narratively. Sixty-six studies were included in the review. Country-level data were provided in 22 studies, regional population or treatment center catchment area data were reported by 44 studies. Crude incidence rates varied widely. For all ages and TBI severities, crude incidence rates ranged from 47.3 per 100,000, to 694 per 100,000 population per year (country-level studies) and 83.3 per 100,000, to 849 per 100,000 population per year (regional-level studies). Crude mortality rates ranged from 9 to 28.10 per 100,000 population per year (country-level studies), and 3.3 to 24.4 per 100,000 population per year (regional-level studies.) The most common mechanisms of injury were traffic accidents and falls. Over time, the contribution of traffic accidents to total TBI events may be reducing. Case ascertainment and definitions of TBI are variable. Improved standardization would enable more accurate comparisons.

Title: Trends in maternal and neonatal mortality in South Africa: a systematic review protocol. Content: BACKGROUND Measuring and monitoring progress towards Millennium Development Goals (MDG) 4 and 5 requires valid and reliable estimates of maternal and neonatal mortality. In South Africa, there are conflicting reports on the estimates of maternal and neonatal mortality, derived from both direct and indirect estimation techniques. This study aims to systematically review the estimates made of maternal and neonatal mortality in the period from 1990 to 2015 in South Africa and determine trends over this period. METHODS For the purpose of this review, searches for eligible studies will be conducted in MEDLINE, Africa-Wide Information, African Index Medicus, African Journals Online, Scopus, Web of Science and CINAHL databases. Searches will be restricted to articles written in English and presenting data covering the period between 1990 and 2015. Reference lists of retrieved articles will also be screened for additional publications. Three independent reviewers will be involved in the study selection, data extractions and achieving consensus. Study quality and risk of bias will thereafter be assessed by two authors. The results will be presented as rates/ratio with their corresponding 95% confidence/uncertainty intervals. DISCUSSION Identifying trends in maternal and neonatal mortality will help to track progress in MDGs 4 and 5 and will serve in evaluating interventions focusing on reducing maternal and child mortality in the country. This study will, in particular, provide the context for understanding inconsistencies in reported estimates of maternal and neonatal mortality by considering estimation methods, data sources and definitions used. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42016042769.

Title: Mortality estimates among adult patients with severe acute respiratory infections from two sentinel hospitals in southern Arizona, United States, 2010–2014 Content: BACKGROUND: From October 2010 through February 2016, Arizona conducted surveillance for severe acute respiratory infections (SARI) among adults hospitalized in the Arizona-Mexico border region. There are few accurate mortality estimates in SARI patients, particularly in adults ≥ 65 years old. The purpose of this study was to generate mortality estimates among SARI patients that include deaths occurring shortly after hospital discharge and identify risk factors for mortality. METHODS: Patients admitted to two sentinel hospitals between 2010 and 2014 who met the SARI case definition were enrolled. Demographic data were used to link SARI patients to Arizona death certificates. Mortality within 30 days after the date of admission was calculated and risk factors were identified using logistic regression models. RESULTS: Among 258 SARI patients, 47% were females, 51% were white, non-Hispanic and 39% were Hispanic. The median age was 63 years (range, 19 to 97 years) and 80% had one or more pre-existing health condition; 9% died in hospital. Mortality increased to 12% (30/258, 30% increase) when electronic vital records and a 30-day post-hospitalization time frame were used. Being age ≥ 65 years (OR = 4.0; 95% CI: 1.6–9.9) and having an intensive care unit admission (OR = 7.4; 95% CI: 3.0–17.9) were independently associated with mortality. CONCLUSION: The use of electronic vital records increased SARI-associated mortality estimates by 30%. These findings may help guide prevention and treatment measures, particularly in high-risk persons in this highly fluid border population.

Title: SARS hits hard Content: Death rates higher than expected, but control measures seem to be working.

Title: Analysis of Austrian COVID-19 deaths by age and sex Content: We analyze the age and sex distribution of the reported COVID-19 deaths in Austria. In accordance with international studies, the Austrian data also suggests that the risk of death increases substantially with age. The observed age dependency of the proportions of registered COVID-19 deaths in relation to the population sizes in the age groups is approximately exponential, similar to the age dependency of the general age specific mortality rate. Furthermore, we compare the general age specific mortality rate in Austria with the estimates of the SARS-CoV‑2 infection fatality rate by Ferguson et al. (2020). The parallels to the general age specific mortality rates do not imply that COVID-19 does not pose an additional risk. On the contrary, it follows from the structure and magnitude of the infection fatality rate that it is substantial, especially for higher age groups. However, since in many cases persons with severe pre-existing conditions are affected, it is not yet possible to estimate what effects COVID-19 will have on life expectancy.

Title: Analysis of Austrian COVID-19 deaths by age and sex Content: We analyze the age and sex distribution of the reported COVID-19 deaths in Austria. In accordance with international studies, the Austrian data also suggests that the risk of death increases substantially with age. The observed age dependency of the proportions of registered COVID-19 deaths in relation to the population sizes in the age groups is approximately exponential, similar to the age dependency of the general age specific mortality rate. Furthermore, we compare the general age specific mortality rate in Austria with the estimates of the SARS-CoV2 infection fatality rate by Ferguson et al. (2020). The parallels to the general age specific mortality rates do not imply that COVID-19 does not pose an additional risk. On the contrary, it follows from the structure and magnitude of the infection fatality rate that it is substantial, especially for higher age groups. However, since in many cases persons with severe pre-existing conditions are affected, it is not yet possible to estimate what effects COVID-19 will have on life expectancy.

Title: Determinants of COVID-19 incidence and mortality: A cross-country analysis Content: Objective: We undertook this study to explore the role of important determinants affecting global COVID-19 incidence and mortality taking multifactorial disease dynamics into consideration. Design: Secondary data as on March 28, 2020 were obtained for 97 countries. Association of COVID-19 cumulative incidence and mortality measures were assessed with ten indictors representing health system characteristics, climate, demography, promptness of international travel restriction and population movement using Generalized Linear Modelling. Main outcome measures: Country-specific COVID-19 cumulative incidence, cumulative cause-specific mortality and case fatality rate. Results: Significant inter-country variation in incidence and mortality rates were observed. Five variables were found to be associated with cumulative incidence: testing rate per 1000 population ({beta} = 0.119, p < 0.01), UHC index ({beta} = 0.043, p = 0.04), percentage elderly population ({beta} = 0.122, p < 0.01), percentage below-poverty line population ({beta} = -0.048, p < 0.01) and disability adjusted life years due to NCDs ({beta} = -0.013, p < 0.01). Case fatality rate was observed to be associated with testing rate per 1000 population ({beta} = -0.058, p = 0.03) and population density ({beta} = 0.002, p = 0.02), while the cumulative cause-specific mortality was associated with only percentage elderly population ({beta} = 0.096, p = 0.04) in the country. Conclusions: Health system response, population susceptibility and demography were the most important factors determining the progression. Policy response should focus towards increasing testing, primarily targeting high population density areas. Health system strengthening and reduction in population risk factors should be long term goals for a better response to such epidemics.

Title: Infection fatality risk of the pandemic A(H1N1)2009 virus in Hong Kong. Content: One measure of the severity of a pandemic influenza outbreak at the individual level is the risk of death among people infected by the new virus. However, there are complications in estimating both the numerator and denominator. Regarding the numerator, statistical estimates of the excess deaths associated with influenza virus infections tend to exceed the number of deaths associated with laboratory-confirmed infection. Regarding the denominator, few infections are laboratory confirmed, while differences in case definitions and approaches to case ascertainment can lead to wide variation in case fatality risk estimates. Serological surveillance can be used to estimate the cumulative incidence of infection as a denominator that is more comparable across studies. We estimated that the first wave of the influenza A(H1N1)pdm09 virus in 2009 was associated with approximately 232 (95% confidence interval: 136, 328) excess deaths of all ages in Hong Kong, mainly among the elderly. The point estimates of the risk of death on a per-infection basis increased substantially with age, from below 1 per 100,000 infections in children to 1,099 per 100,000 infections in those 60-69 years of age. Substantial variation in the age-specific infection fatality risk complicates comparison of the severity of different influenza strains.

Title: Occupational Deaths among Healthcare Workers Content: Recent experiences with severe acute respiratory syndrome and the US smallpox vaccination program have demonstrated the vulnerability of healthcare workers to occupationally acquired infectious diseases. However, despite acknowledgment of risk, the occupational death rate for healthcare workers is unknown. In contrast, the death rate for other professions with occupational risk, such as police officer or firefighter, has been well defined. With available information from federal sources and calculating the additional number of deaths from infection by using data on prevalence and natural history, we estimate the annual death rate for healthcare workers from occupational events, including infection, is 17–57 per 1 million workers. However, a much more accurate estimate of risk is needed. Such information could inform future interventions, as was seen with the introduction of safer needle products. This information would also heighten public awareness of this often minimized but essential aspect of patient care.

Title: Maternal, neonatal, and child health in southeast Asia: towards greater regional collaboration Content: Although maternal and child mortality are on the decline in southeast Asia, there are still major disparities, and greater equity is key to achieve the Millennium Development Goals. We used comparable cross-national data sources to document mortality trends from 1990 to 2008 and to assess major causes of maternal and child deaths. We present inequalities in intervention coverage by two common measures of wealth quintiles and rural or urban status. Case studies of reduction in mortality in Thailand and Indonesia indicate the varying extents of success and point to some factors that accelerate progress. We developed a Lives Saved Tool analysis for the region and for country subgroups to estimate deaths averted by cause and intervention. We identified three major patterns of maternal and child mortality reduction: early, rapid downward trends (Brunei, Singapore, Malaysia, and Thailand); initially high declines (sustained by Vietnam but faltering in the Philippines and Indonesia); and high initial rates with a downward trend (Laos, Cambodia, and Myanmar). Economic development seems to provide an important context that should be coupled with broader health-system interventions. Increasing coverage and consideration of the health-system context is needed, and regional support from the Association of Southeast Asian Nations can provide increased policy support to achieve maternal, neonatal, and child health goals.

Title: Explaining national differences in the mortality of Covid-19: individual patient simulation model to investigate the effects of testing policy and other factors on apparent mortality. Content: There has been extensive speculation on the apparent differences in mortality between countries reporting on the confirmed cases and deaths due to Covid-19. A number of explanations have been suggested, but there is no clear evidence about how apparent fatality rates may be expected to vary with the different testing regimes, admission policies and other variables. An individual patient simulation model was developed to address this question. Parameters and sensitivity analysis based upon recent international data sources for Covid-19 and results were averaged over 100 iterations for a simulated cohort of over 500,000 patients. Different testing regimes for Covid-19 were considered; testing admitted patients only, various rates of community testing of symptomatic cases and active contact-tracing and screening. In the base case analysis, apparent mortality ranged from 10.5% under a policy of testing only admitted patients to 0.4% with intensive contact tracing and community testing. These findings were sensitive to assumptions regarding admission rates and the rate of spread, with more selective admission policies and suppression of spread increasing the apparent mortality and the potential for apparent mortality rates to exceed 18% under some circumstances. Under all scenarios the proportion of patients tested in the community had the greatest impact on apparent mortality. Whilst differences in mortality due to health service and demographic factors cannot be excluded, the current international differences in reported mortality are all consistent with differences in practice regarding screening, community testing and admission policies.

Title: A Comparison of Generalized Stochastic Milevsky-Promislov Mortality Models with Continuous Non-Gaussian Filters Content: The ability to precisely model mortality rates [Formula: see text] plays an important role from the economic point of view in healthcare. The aim of this article is to propose a comparison of the estimation of the mortality rates based on a class of stochastic Milevsky-Promislov mortality models. We assume that excitations are modeled by second, fourth and sixth order polynomials of outputs from a linear non-Gaussian filter. To estimate the model parameters we use the first and second moments of [Formula: see text]. The theoretical values obtained in both cases were compared with theoretical [Formula: see text] based on a classical Lee-Carter model. The obtained results confirm the usefulness of the switched model based on the continuous non-Gaussian processes used for modeling [Formula: see text].

Title: Using research to prepare for outbreaks of severe acute respiratory infection Content: Severe acute respiratory infections (SARI) remain one of the leading causes of mortality around the world in all age groups. There is large global variation in epidemiology, clinical management and outcomes, including mortality. We performed a short period observational data collection in critical care units distributed globally during regional peak SARI seasons from 1 January 2016 until 31 August 2017, using standardised data collection tools. Data were collected for 1 week on all admitted patients who met the inclusion criteria for SARI, with follow-up to hospital discharge. Proportions of patients across regions were compared for microbiology, management strategies and outcomes. Regions were divided geographically and economically according to World Bank definitions. Data were collected for 682 patients from 95 hospitals and 23 countries. The overall mortality was 9.5%. Of the patients, 21.7% were children, with case fatality proportions of 1% for those less than 5 years. The highest mortality was in those above 60 years, at 18.6%. Case fatality varied by region: East Asia and Pacific 10.2% (21 of 206), Sub-Saharan Africa 4.3% (8 of 188), South Asia 0% (0 of 35), North America 13.6% (25 of 184), and Europe and Central Asia 14.3% (9 of 63). Mortality in low-income and low-middle-income countries combined was 4% as compared with 14% in high-income countries. Organ dysfunction scores calculated on presentation in 560 patients where full data were available revealed Sequential Organ Failure Assessment (SOFA) scores on presentation were significantly associated with mortality and hospital length of stay. Patients in East Asia and Pacific (48%) and North America (24%) had the highest SOFA scores of >12. Multivariable analysis demonstrated that initial SOFA score and age were independent predictors of hospital survival. There was variability across regions and income groupings for the critical care management and outcomes of SARI. Intensive care unit-specific factors, geography and management features were less reliable than baseline severity for predicting ultimate outcome. These findings may help in planning future outbreak severity assessments, but more globally representative data are required.

Title: The basic principles of migration health: Population mobility and gaps in disease prevalence Content: Currently, migrants and other mobile individuals, such as migrant workers and asylum seekers, are an expanding global population of growing social, demographic and political importance. Disparities often exist between a migrant population's place of origin and its destination, particularly with relation to health determinants. The effects of those disparities can be observed at both individual and population levels. Migration across health and disease disparities influences the epidemiology of certain diseases globally and in nations receiving migrants. While specific disease-based outcomes may vary between migrant group and location, general epidemiological principles may be applied to any situation where numbers of individuals move between differences in disease prevalence. Traditionally, migration health activities have been designed for national application and lack an integrated international perspective. Present and future health challenges related to migration may be more effectively addressed through collaborative global undertakings. This paper reviews the epidemiological relationships resulting from health disparities bridged by migration and describes the growing role of migration and population mobility in global disease epidemiology. The implications for national and international health policy and program planning are presented.

Title: Burden and changes in HIV/AIDS morbidity and mortality in Southern Africa Development Community Countries, 1990–2017 Content: BACKGROUND: The 16 Southern Africa Development Community (SADC) countries remain the epicentre of the HIV/AIDS epidemic with the largest number of people living with HIV/AIDS. Anti-retroviral treatment (ART) has improved survival and prevention of mother-to-child transmission (PMTCT) of HIV, but the disease remains a serious cause of mortality. We conducted a descriptive epidemiological analysis of HIV/AIDS burden for the 16 SADC countries using secondary data from the Global Burden of Diseases, Injuries and Risk Factor (GBD) Study. METHODS: The GBD study is a systematic, scientific effort by the Institute for Health Metrics and Evaluation (IHME) to quantify the comparative magnitude of health loss due to diseases, injuries, and risk factors by age, sex, and geographies for specific points in time. We analyzed the following outcomes: mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to HIV/AIDS for SADC. Input data for GBD was extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service utilisation, disease notifications, and other sources. Country- and cause-specific HIV/AIDS-related death rates were calculated using the Cause of Death Ensemble model (CODEm) and spatiotemporal Gaussian process regression (ST-GPR). Deaths were multiplied by standard life expectancy at each age-group to calculate YLLs. Cause-specific mortality was estimated using a Bayesian meta-regression modelling tool, DisMod-MR. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases to calculate YLDs. Crude and age-adjusted rates per 100,000 population and changes between 1990 and 2017 were determined for each country. RESULTS: In 2017, HIV/AIDS caused 336,175 deaths overall in SADC countries, and more than 20 million DALYs. This corresponds to a 3-fold increase from 113,631 deaths (6,915,170 DALYs) in 1990. The five leading countries with the proportion of deaths attributable to HIV/AIDS in 2017 were Botswana at the top with 28.7% (95% UI; 23.7–35.2), followed by South Africa 28.5% (25.8–31.6), Lesotho, 25.1% (21.2–30.4), eSwatini 24.8% (21.3–28.6), and Mozambique 24.2% (20.6–29.3). The five countries had relative attributable deaths that were at least 14 times greater than the global burden of 1.7% (1.6–1.8). Similar patterns were observed with YLDs, YLLs, and DALYs. Comoros, Seychelles and Mauritius were on the lower end, with attributable proportions less than 1%, below the global proportion. CONCLUSIONS: Great progress in reducing HIV/AIDS burden has been achieved since the peak but more needs to be done. The post-2005 decline is attributed to PMTCT of HIV, resources provided through the US President’s Emergency Plan For AIDS Relief (PEPFAR), and behavioural change. The five countries with the highest burden of HIV/AIDS as measured by proportion of death attributed to HIV/AIDS and age-standardized mortaility rate were Botswana, South Africa, Lesotho, eSwatini, and Mozambique. SADC countries should cooperate, work with donors, and embrace the UN Fast-Track approach, which calls for frontloading investment from domestic or other sources to prevent and treat HIV/AIDS. Robust tracking, testing, and early treatment are required, as well as refinement of individual treatment strategies for transient individuals in the region.

Title: Relative Coronavirus Disease 2019 Mortality: A Swiss Population-based Study Content: Objective: Severity of the coronavirus disease 2019 (covid-19) has been assessed in terms of absolute mortality in SARS-CoV-2 positive cohorts. An assessment of mortality relative to mortality in the general population is presented. Design: Retrospective population-based study. Setting: Individual information on symptomatic confirmed SARS-CoV-2 patients and subsequent deaths from any cause were compared to the all-cause mortality in the Swiss population of 2018. Starting February 23, 2020, mortality in covid-19 patients was monitored for 80 days and compared to the population mortality observed in the same time-of-year starting February 23, 2018. Participants: 5 160 595 inhabitants of Switzerland aged 35 to 95 without covid-19 (general population in spring 2018) and 20 769 persons tested positively for covid-19 (spring 2020). Measurements: Sex- and age-specific mortality rates were estimated using Cox proportional hazards models. Absolute probabilities of death were predicted and risk was assessed in terms of relative mortality by taking the ratio between the sex- and age-specific absolute mortality in covid19 patients and the corresponding mortality in the 2018 general population. Results: A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups, ranging from nine (6 to 15) times the population mortality in 35-year old infected females to a 53-fold increase (46 to 59) for 95 year old infected males. The highest relative risks were observed among males and older patients. The magnitude of these effects was smaller compared to increases observed in absolute mortality risk. Male covid-19 patients exceeded the population hazard for males (hazard ratio 1.20, 1.00 to 1.44). Each additional year of age increased the population hazard in covid-19 patients (hazard ratio 1.04, 1.03 to 1.05). Limitations: Information about the distribution of relevant comorbidities was not available on population level and the associated risk was not quantified. Conclusions: Health care professionals, decision makers, and societies are provided with an additional population-adjusted assessment of covid-19 mortality risk. In combination with absolute measures of risk, the relative risks presented here help to develop a more comprehensive understanding of the actual impact of covid-19.

Title: [Democracy and Covid-19 mortality in Europe.] Content: OBJECTIVE: In Europe there is a great variability in mortality by Covid-19 among different countries While some countries, such as Greece, Belarus or Ukraine, have a mortality rate of less than 5 cases/100,000 inhabitants, other countries such as Belgium, Spain or the United Kingdom have a mortality rate of well over 50 cases/100,000 inhabitants It is generally considered that the reason for this variability is multifactorial (including political reasons), but there are few studies that associate factors related to this variability The objective of this work was to analyse political risk factors/markers that could explain the variability in mortality due to Covid-19 among different European countries METHODS: This is a retrospective, multinational, ecological study based on the exploitation of the database provided by the European Centre for Disease Prevention and Control which collects daily information worldwide on new cases and deaths The accumulated mortality of Covid-19 in European countries (with more than 100 deaths on 01/05/2020) was calculated up to 29/05/2020 Political variables were compiled from different sources in the countries included in the study The variables analysed were: the democracy index and the different factors included in it, the country's political system and the country's corruption index On the other hand, specific political measures implemented in the different countries were collected, such as the number of days elapsed from the notification of the first infected person to 100 infected persons, to lockdown, to the closure of schools or the cancelation of meetings The number of people infected up to the date of lockdown was also registered For the statistical analysis of the association between the dependent variable (mortality) and the factors studied, correlation index were calculated, and the association was studied through univariate and multivariate linear regression models RESULTS: At May 1 2020, 27 European countries had at least 100 deaths The mean mortality was 19 83 cases/100,000 inhabitants (SD 22 4) and a median of 7 95 Mortality varied from a minimum of 1 49 cases/100,000 population in Ukraine to 82 19 cases/100,000 population in Belgium About factors analyzed both the democracy index (as well as the factors included in it), the political system (full democracy vs no) and the corruption index were statistically associated with mortality Also, the time until the implementation of the political measures was associated with mortality CONCLUSIONS: In Europe, there is a west to east (from highest to lowest) gradient in the mortality of Covid-19 Some of the observed mortality variability can be explained by political factors

Title: Age effects in monetary valuation of reduced mortality risks: the relevance of age-specific hazard rates Content: This paper highlights the relevance of age-specific hazard rates in explaining the age variation in “value of statistical life” (VSL) figures. The analysis—which refers to a stated preference framework—contributes to the ongoing discussion of whether benefits resulting from reduced mortality risk should be valued differently depending on the age of the beneficiaries. By focussing on a life-threatening environmental phenomenon I show that the consideration of the individual’s age-specific hazard rate is important. If a particular risk affects all individuals regardless of their age so that their hazard rate is age-independent, VSL is rather constant for people at different age; if hazard rate varies with age, VSL estimates are sensitive to age. The results provide an explanation for the mixed outcomes in empirical studies and illustrate in which cases an adjustment to age may or may not be justified. Efficient provision of live-saving measures requires that such differences to be taken into account.

Title: [Democracy and Covid-19 mortality in Europe.] Content: OBJECTIVE In Europe there is a great variability in mortality by Covid-19 among different countries. While some countries, such as Greece, Belarus or Ukraine, have a mortality rate of less than 5 cases/100,000 inhabitants, other countries such as Belgium, Spain or the United Kingdom have a mortality rate of well over 50 cases/100,000 inhabitants. It is generally considered that the reason for this variability is multifactorial (including political reasons), but there are few studies that associate factors related to this variability. The objective of this work was to analyse political risk factors/markers that could explain the variability in mortality due to Covid-19 among different European countries. METHODS This is a retrospective, multinational, ecological study based on the exploitation of the database provided by the European Centre for Disease Prevention and Control which collects daily information worldwide on new cases and deaths. The accumulated mortality of Covid-19 in European countries (with more than 100 deaths on 01/05/2020) was calculated up to 29/05/2020. Political variables were compiled from different sources in the countries included in the study. The variables analysed were: the democracy index and the different factors included in it, the country's political system and the country's corruption index. On the other hand, specific political measures implemented in the different countries were collected, such as the number of days elapsed from the notification of the first infected person to 100 infected persons, to lockdown, to the closure of schools or the cancelation of meetings. The number of people infected up to the date of lockdown was also registered. For the statistical analysis of the association between the dependent variable (mortality) and the factors studied, correlation index were calculated, and the association was studied through univariate and multivariate linear regression models. RESULTS At May 1 2020, 27 European countries had at least 100 deaths. The mean mortality was 19.83 cases/100,000 inhabitants (SD 22.4) and a median of 7.95. Mortality varied from a minimum of 1.49 cases/100,000 population in Ukraine to 82.19 cases/100,000 population in Belgium. About factors analyzed both the democracy index (as well as the factors included in it), the political system (full democracy vs. no) and the corruption index were statistically associated with mortality. Also, the time until the implementation of the political measures was associated with mortality. CONCLUSIONS In Europe, there is a west to east (from highest to lowest) gradient in the mortality of Covid-19. Some of the observed mortality variability can be explained by political factors.

Title: Estimating the Size of High-risk Populations for COVID-19 Mortality across 442 US Cities Content: A variety of predisposing factors have been associated with serious illness and death from COVID-19. Understanding the distribution of risks associated with these factors by local communities can provide important opportunities for targeting interventions. We characterize the distribution of risk for COVID-19 mortality for populations at large across 442 US cities, by utilizing recently published estimates of risk associated with age, gender, ethnicity, social deprivation and 12 health conditions from a very large UK-based study, combined with the information available on prevalence and co-occurrence of these factors in the US through a variety of population-based public databases. We estimate that across all the cities, an underlying weighted risk-score can identify a total of approximately 12.65 million, 4.09 million and 1.34 million individuals who are at 2-, 5- and 10-fold higher risk, respectively, compared to the average risk for the US population. The percentage of population which exceed the respective risk thresholds varies across the cities in the range (1st-99th percentile), 3.6%-20.1%, 0.7%-8.0% and 0.1%-3.2%, respectively. The percentage of deaths within a city that are expected to occur above these risk-thresholds varies in the range of 20.1%-53.5%, 8.5%-38.2% and 2.9%-25.4%, respectively. Our analysis can provide guidance to national and local policy makers regarding resources needed to protect the most vulnerable populations in these communities, and how much utility such interventions may have in reducing the total population burden of death.

Title: A geographic analysis of population density thresholds in the influenza pandemic of 1918–19 Content: BACKGROUND: Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918–19 in India, where over 15 million people died in the short span of less than one year. METHODS: Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918–19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts. RESULTS: The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%). CONCLUSIONS: This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold.

Title: Changes in cold-related mortalities between 1995 and 2016 in South East England Content: Abstract Objective The aim of the study was to examine trends in cold-related mortalities between 1995 and 2016. Study design This is a longitudinal mortality study. Methods For men and women aged 65–74 years or those older than 85 years in South East England, the relationship between daily mortality (deaths per million population) and outdoor temperatures below 18 °C, with allowance for influenza epidemics, was assessed by linear regression on an annual basis. The regression coefficients were expressed as a percentage of the mortality at 18 °C to adjust for changes in mortality through health care. Trends in ‘specific’ cold-related mortalities were then examined over two periods, 1977–1994 and 1995–2016. Results In contrast to the early period, annual trends in cold-related specific mortalities showed no decline between 1995 and 2016. ‘Specific’ cold-related mortality of women, but not men, in the age group older than 85 years showed a significant increase over the 1995–2016 period, which was different from the trend over the earlier period (P < 0.01). Conclusion Despite state-funded benefits to help alleviate fuel poverty and public health advice, very elderly women appear to be at increasing risk of cold-related mortality—greater help may be necessary.

Title: Mortality of people with intellectual disabilities during the 2017/2018 influenza epidemic in the Netherlands: potential implications for the COVID‐19 pandemic Content: BACKGROUND: Data on the development of Covid‐19 among people with intellectual disabilities (IDs) are scarce and it is uncertain to what extent general population data applies to people with ID. To give an indication of possible implications, this study investigated excess mortality patterns during a previous influenza epidemic. METHODS: Using Dutch population and mortality registers, a historical cohort study was designed to compare mortality during the 2017–2018 influenza epidemic with mortality in the same period in the three previous years. People with ID were identified by entitlements to residential ID‐care services as retrieved from a national database. RESULTS: Data covered the entire adult Dutch population (12.6 million; GenPop), of which 91 064 individuals were identified with an ID. During the influenza epidemic, mortality among people with ID increased almost three times as much than in the GenPop (15.2% vs. 5.4%), and more among male individuals with ID (+19.5%) than among female individuals with ID (+10.6%), as compared with baseline. In both cohorts, comparable increases in mortality within older age groups and due to respiratory causes were seen. Particularly in the ID‐cohort, excess deaths also occurred in younger age groups, due to endocrine diseases and ID‐specific causes. CONCLUSIONS: During the 2017–2018 influenza epidemic, excess mortality among people with ID was three times higher than in the general Dutch population, appeared more often at young age and with a broader range of underlying causes. These findings suggest that a pandemic may disproportionally affect people with ID while population data may not immediately raise warnings. Early detection of diverging patterns and faster implementation of tailored strategies therefore require collection of good quality data.

Title: Deaths in SARS-Cov-2 Positive Patients in Italy: The Influence of Underlying Health Conditions on Lethality Content: This study aims to underline the clinical characteristics of patients who died after testing positive for SARS-CoV-2 infection in one region of Italian and to evaluate the influence of underlying health conditions on the fatal outcome. A matched case-control study was designed by analyzing the data regarding positive subjects observed up to April 21, 2020. The case fatality rate was 7.9%, with a higher proportion of deaths in men than women. The specific standardized mortality ratio was 0.15—0.13 for males and 0.2 for females, showing that mortality is much lower than expected. Cardiovascular diseases, chronic lung diseases and diabetes mellitus showed a significant association with the outcome. Although the case fatality rate in Sardinia in regard to age and gender patterns seems to be similar to that for Italy as a whole, its quantitative value was far lower than the national one and possible explanations might include the genetic characteristics of the Sardinian population or the immediate closure of its borders as soon as the epidemic started. Our results highlighted that lethality is strongly dependent on the presence of multiple concomitant serious diseases. It is important to have epidemiological strategies for effective guidance on public health actions in order to improve chances of survival.

Title: Early Epidemiological Assessment of the Virulence of Emerging Infectious Diseases: A Case Study of an Influenza Pandemic Content: BACKGROUND: The case fatality ratio (CFR), the ratio of deaths from an infectious disease to the number of cases, provides an assessment of virulence. Calculation of the ratio of the cumulative number of deaths to cases during the course of an epidemic tends to result in a biased CFR. The present study develops a simple method to obtain an unbiased estimate of confirmed CFR (cCFR), using only the confirmed cases as the denominator, at an early stage of epidemic, even when there have been only a few deaths. METHODOLOGY/PRINCIPAL FINDINGS: Our method adjusts the biased cCFR by a factor of underestimation which is informed by the time from symptom onset to death. We first examine the approach by analyzing an outbreak of severe acute respiratory syndrome in Hong Kong (2003) with known unbiased cCFR estimate, and then investigate published epidemiological datasets of novel swine-origin influenza A (H1N1) virus infection in the USA and Canada (2009). Because observation of a few deaths alone does not permit estimating the distribution of the time from onset to death, the uncertainty is addressed by means of sensitivity analysis. The maximum likelihood estimate of the unbiased cCFR for influenza may lie in the range of 0.16–4.48% within the assumed parameter space for a factor of underestimation. The estimates for influenza suggest that the virulence is comparable to the early estimate in Mexico. Even when there have been no deaths, our model permits estimating a conservative upper bound of the cCFR. CONCLUSIONS: Although one has to keep in mind that the cCFR for an entire population is vulnerable to its variations among sub-populations and underdiagnosis, our method is useful for assessing virulence at the early stage of an epidemic and for informing policy makers and the public.

Title: How do environmental, economic and health factors influence regional vulnerability to COVID-19? Content: We have studied the correlations between twelve environmental, economic and health variables, by carrying out a statistical analysis of the fatality rate of COVID-19 in 14 countries. Our statistical analysis indicates that, among the 12 variables, the diabetes percentage of the total population and the extent of the population ages 65 and older in each country are correlated most strongly with the total number of deaths in them. Although the strength of the correlations between the variables and the total ND may change as the ongoing pandemic evolves, the study highlights the importance of integrating regional-specific variables in the modelling efforts aimed at projecting how the spread of the virus may influence different parts of the world.

Title: Mortality of Life‐Insured Swedish Cats during 1999–2006: Age, Breed, Sex, and Diagnosis Content: Background: A cat life insurance database can potentially be used to study feline mortality. Hypothesis: The aim was to describe patterns of mortality in life‐insured Swedish cats. Cats: All cats (<13 years of age) with life insurance during the period 1999–2006 were included. Methods: Age‐standardized mortality rates (MR) were calculated with respect to sex (males and females), age, breed, and diagnosis. Survival to various ages is presented by time period and breed. Results: The total number of cats insured was 49,450 and the number of cat‐years at risk (CYAR) was 142,049. During the period, 6,491 cats died and of these 4,591 cats (71%) had a diagnosis, ie, were claimed for life insurance. The average annual MR was 462 deaths per 10,000 CYAR (95% confidence interval, 431–493). Sex‐specific rates did not differ significantly. The overall mortality of the Persian and the Siamese groups was higher than that of several other breeds. Overall and breed‐specific (for most breeds) survival increased with time when analyzed by 2‐year periods. The 6 most common diagnostic categories (ignoring cats recorded as dead with no diagnosis) were urinary, traumatic, neoplastic, infectious, cardiovascular, and gastrointestinal. The MR within diagnostic categories varied by age and breed. Conclusions and Clinical Importance: In this mainly purebred, insured cat population, the overall mortality varied with age and breed but not with sex. The increase in survival over time is likely a reflection of willingness to keep pet cats longer and increased access to and sophistication of veterinary care.

Title: Impact of COVID-19 on 2020 US life expectancy for the Black and Latino populations Content: The Black and Latino populations have experienced a disproportionate burden of COVID-19 morbidity and mortality, reflecting persistent structural inequalities that increase risk of exposure to COVID-19 and risk of death for those infected. According to the National Center for Health Statistics, as of July 4, 2020, deaths to Black and Latino individuals comprised 23% and 17%, respectively, of the approximately 115,000 COVID-19 deaths. COVID-19 mortality is likely to result in a larger decline in life expectancy during 2020 than the US has experienced for decades as well as a particularly large reduction for Black and Latino individuals. We estimate life expectancy at birth and at age 65 for 2020, by race and ethnicity, using four scenarios of deaths-one in which the COVID-19 pandemic had not occurred and three including COVID-19 mortality projections produced by the Institute for Health Metrics and Evaluation. Our most likely estimate indicates a reduction in life expectancy at birth greater than 1.5 years for both the Black and Latino populations, which is one year larger than the reduction for whites. This would imply that the Black-white gap would increase by 30%, from 3.6 to 4.7 years, thereby eliminating progress made in reducing this differential since 2008 and reversing an overall trend of steeper mortality declines among the Black population since the early 1990s. Latinos, who have consistently experienced lower mortality than whites (a phenomenon known as the Latino or Hispanic paradox), would see their survival advantage decline by 36%, equivalent to its magnitude in 2006.

Title: Total COVID-19 Mortality in Italy: Excess Mortality and Age Dependence through Time-Series Analysis Content: We perform a counterfactual time series analysis using two different Data Science methods applied to 2020 mortality data reported from towns in Italy, with data from the previous five years as control. We find an excess mortality that is correlated in time with the COVID-19 reported death rate time series. Our analysis shows good agreement with reported COVID-19 mortality for age<70 years, but an excess in total mortality increasing with age above 70 years, suggesting there is a large population of predominantly old people missing from the official fatality statistics. We estimate that the number of COVID-19 deaths in Italy is 52,000 ± 2000 as of April 18 2020, more than a factor of 2 higher than the official number. The Population Fatality Rate (PFR) has reached 0.22% in the most affected region of Lombardia and 0.57% in the most affected province of Bergamo,which constitutes a lower bound to the Infection Fatality Rate (IFR). We estimate PFR as a function of age, finding a steep age dependence: in Lombardia (Bergamo province) 0.6% (1.7%) of the total population in age group 70-79 died, 1.6% (4.6%) in age group 80-89, and 3.41% (10.2%) in the age group above 90. We combine this with the Test Positivity Rate to estimate the lower bound of 0.84% on the IFR for Lombardia. We observe IFR to trace the Yearly Mortality Rate (YMR) above 60 years, which can be used to estimate the IFR for other regions in the world. We predict an IFR lower bound of 0.5% for NYC and 26% of total COVID-19 mortality arising from the population below 65 years, in agreement with the existing data and several times higher than Lombardia. Combining PFR with the Princess Diamond cruise ship IFR for ages above 70 we estimate the infection rates(IR) of regions in Italy, which peak in Lombardia at 23% (12%-41%, 95% c.l.), and for provinces in Bergamo at 67% (33%-100%, 95% c.l.). This suggests that Bergamo may have reached herd immunity, and that the number of infected people greatly exceeds the number of positive tests, by a factor of 35 in Lombardia.

Title: Staphylococcus aureus Colonization and Long-Term Risk for Death, United States. Content: To examine the association of colonization by Staphylococcus aureus and general population mortality, we followed 10,598 adults for 8.5 years on average. Methicillin-susceptible S. aureus colonization was not associated with death. Methicillin-resistant S. aureus carriage predicted death in a crude analysis but not after adjustment for socioeconomic status and co-morbidities.

Title: Deaths in SARS-Cov-2 Positive Patients in Italy: The Influence of Underlying Health Conditions on Lethality Content: This study aims to underline the clinical characteristics of patients who died after testing positive for SARS-CoV-2 infection in one region of Italian and to evaluate the influence of underlying health conditions on the fatal outcome. A matched case-control study was designed by analyzing the data regarding positive subjects observed up to April 21, 2020. The case fatality rate was 7.9%, with a higher proportion of deaths in men than women. The specific standardized mortality ratio was 0.15-0.13 for males and 0.2 for females, showing that mortality is much lower than expected. Cardiovascular diseases, chronic lung diseases and diabetes mellitus showed a significant association with the outcome. Although the case fatality rate in Sardinia in regard to age and gender patterns seems to be similar to that for Italy as a whole, its quantitative value was far lower than the national one and possible explanations might include the genetic characteristics of the Sardinian population or the immediate closure of its borders as soon as the epidemic started. Our results highlighted that lethality is strongly dependent on the presence of multiple concomitant serious diseases. It is important to have epidemiological strategies for effective guidance on public health actions in order to improve chances of survival.

Title: Worldwide differences in COVID-19-related mortality Content: Mortality statistics due to COVID-19 worldwide are compared, by adjusting for the size of the population and the stage of the pandemic. Data from the European Centre for Disease Control and Prevention, and Our World in Data websites were used. Analyses are based on number of deaths per one million inhabitants. In order to account for the stage of the pandemic, the baseline date was defined as the day in which the 10th death was reported. The analyses included 78 countries and territories which reported 10 or more deaths by April 9. On day 10, India had 0.06 deaths per million, Belgium had 30.46 and San Marino 618.78. On day 20, India had 0.27 deaths per million, China had 0.71 and Spain 139.62. On day 30, four Asian countries had the lowest mortality figures, whereas eight European countries had the highest ones. In Italy and Spain, mortality on day 40 was greater than 250 per million, whereas in China and South Korea, mortality was below 4 per million. Mortality on day 10 was moderately correlated with life expectancy, but not with population density. Asian countries presented much lower mortality figures as compared to European ones. Life expectancy was found to be correlated with mortality.

Title: Worldwide differences in COVID-19-related mortality. Content: Mortality statistics due to COVID-19 worldwide are compared, by adjusting for the size of the population and the stage of the pandemic. Data from the European Centre for Disease Control and Prevention, and Our World in Data websites were used. Analyses are based on number of deaths per one million inhabitants. In order to account for the stage of the pandemic, the baseline date was defined as the day in which the 10th death was reported. The analyses included 78 countries and territories which reported 10 or more deaths by April 9. On day 10, India had 0.06 deaths per million, Belgium had 30.46 and San Marino 618.78. On day 20, India had 0.27 deaths per million, China had 0.71 and Spain 139.62. On day 30, four Asian countries had the lowest mortality figures, whereas eight European countries had the highest ones. In Italy and Spain, mortality on day 40 was greater than 250 per million, whereas in China and South Korea, mortality was below 4 per million. Mortality on day 10 was moderately correlated with life expectancy, but not with population density. Asian countries presented much lower mortality figures as compared to European ones. Life expectancy was found to be correlated with mortality.