The most demanding period for acquiring speech and language skills is the first 3 years of life, when the brain is developing and maturing. These skills are best developed in a world that is rich with sounds, sights, and consistent exposure to the speech and language of others.
There are certain critical periods for speech and language development in infants and young children. This is the period when the brain is best able to absorb language. If these periods are missed without exposure to language, it will lead to learning difficulties.
Milestones for speech and language development
When an infant learns that a cry will bring food, comfort, and company that is when the first signs of communication occurs. Newborn babies begin to recognize key sounds in their environment, such as the voice of their mother or primary caretaker. Babies begin to sort out the speech sounds that compose the words of their language as they progress in growth. Most babies recognize the basic sounds of their native language by 6 months of age.
The development of speech and language skills in children differs. They follow a natural advancement or timetable for mastering the skills of language. There are certain milestones which help doctors and professionals determine if a child is on track or if the child may need extra help. Sometimes a delay may be caused by hearing loss, while other times it may be due to a speech or language disorder.
How to nurture your baby’s language development?
1. Talk, talk, talk. …
2. Read, read, read. …
3. Enjoy music together. …
4. Tell stories. …
5. Follow your child’s lead. …
6. Never criticize your child’s articulation or speech patterns. …
7. Use television and computers sparingly. …
8. Treat ear infections thoroughly.
Language development varies considerably between children, even within the same family. However, they tend to follow a natural progression for mastering the skills of language and there are certain ‘milestones’ that can be identified as a rough guide to normal development.
Children develop their speech at an individual rate but there are certain milestones to be aware of.
Development of speech over time
Babies need to learn how language sounds before being able to learn how to speak.
Although children improve at their own rate, there are some general patterns:
- From 1-3 months of age, babies cry and coo
- At 4 to 6 months of age, babies sigh, grunt, gurgle, squeal, laugh and make different crying sounds.
- Between 6-9 months, babies babble in syllables and start imitating tones and speech sounds.
- Between 12 months, a baby’s first words usually appear, and by 18 months to 2 years’ children use around 50 words.
- Between 2-3 years, sentences extend to 4 and 5 words. Children can recognize and identify almost all common objects and pictures.
- Between 3-5 years, conversations become longer, and more abstract and complex.
- By the time a child turns 5, they usually have a 2,500-word vocabulary and talk in complete, grammatically correct sentences. They ask a lot of ‘why?’, ‘what?’ and ‘who?’ questions.
How can parents help?
- making faces and noises and talking about your activities from the day they’re born
- playing interactive games like peek-a-boo and singing nursery rhymes
- looking at books from an early age – you don’t have to read the words, just talk about what you can see
- talking slowly and clearly and using short, simple sentences.
- avoiding testing, such as asking ‘What’s this?’, as children learn better without pressure
- not criticizing wrong words and instead saying the word properly – for example, if your baby points to a dog and says ‘do!’ say: ‘Yes, it’s a dog
- letting your child lead the conversation and help them expand on their thoughts
- giving your child lots of opportunities to talk, with plenty of time to answer your questions
Who is a late talker?
A “Late Talker” is a toddler (between 18-30 months) who has good understanding of language, typically developing play skills, motor skills, thinking skills, and social skills, but has a limited spoken vocabulary for his or her age.
When to seek medical help?
- By 12 months, your child is not trying to communicate with you (using sounds, gestures and/or words), particularly when needing help or wanting something
- By 2 years, your child has not started combining words.
If your child hasn’t mastered most of the speech and language development milestones for his or her age or you’re concerned about any aspect of your child’s development seek help immediately. Speech delays occur for many reasons, including hearing loss and developmental disorders. Depending on the circumstances, your child’s doctor might refer your child to a hearing specialist or a speech-language pathologist.
In the meantime, talk to your child about what you’re doing and where you’re going. Sing songs and read together. Teach your child to imitate actions, such as clapping, and to say animal sounds. Practice counting. Show your child that you’re pleased when he or she speaks. Listen to your child’s sounds and repeat them back to him or her. These steps can encourage your child’s speech and language development.
Encouraging your toddler to talk
Talk to your toddler as much as possible as you go about your daily routine and when you are out and about. The more you talk to your toddler, the newer words she’ll learn, and the better she’ll get at talking.
Chat to your toddler as you change diapers, feed, or bathe her. But make sure you give give her time to respond with a smile or eye-to-eye contact. Use everyday activities to help your toddler to make connections between actions and objects and the words that represent them. Point out things you see when you’re out and about.
Simplify your speech when you talk to your toddler. Use short sentences and emphasize key words. This will help your toddler to focus on the important information.
Try talking to your toddler from time to time in sentences that are about one word longer than the sentences she is using. So if your child uses two-word sentences, use lots of three-word and four-word sentences when talking back to her. For example, if your toddler says “a bird”, you could say, “yes, a big bird.”
You can increase your child’s vocabulary by giving her choices, such as “Do you want an apple or a pear?”. You could even show your child both an apple and a pear. This helps your toddler to store a picture of the word in her mind.
It will help your toddler to learn how to talk if you make time to sit in front of her and talk to her. You could even sit in front of her when you read a book, rather than have her on your lap, so she can watch you talking.
Look at books with your toddler regularly. Even if you don’t follow the story as it unfolds, your toddler will learn by listening to you talk about the pictures.
I recently came across a site that helps you check if your child is on track. http://www.talkingpoint.org.uk/
They have different choices of months which can be selected. It’s basically a quiz for the parent with their child’s development.
So mommies get going and do the talking.


Parents who send children to schools have many concerns. Will their kid get along with others? What should they pack for lunch? Would they be able to keep up with the lessons? Perhaps the most crucial, however, is that of safety. Are my children safe?
A good school is prepared to keep its students safe, even from veiled threats. For example, one of the most insidious of health hazards in many Australian schools is asbestos.
Our staff has made an effort to learn about asbestos and the dangers it poses. At the same time, the school has hired professionals to remove any fibres or sheets from all areas of the school. In fact, you can contact the people we hired if you click here.
Asbestos poses many dangers, especially to children.
The fibres are small enough that they can be hard to see except in small clusters. The naked eye can spot individual ones, but it isn’t easy.
When someone breaths it in, the body can’t break it down. Instead, it lingers in the lungs. The damage isn’t apparent early on, as it can take years to manifest. The fibres begin to tear at the lining of the lung, causing it to produce fluid in an attempt to remove the irritant.
As time progresses, the damage develops into a cancerous tumour. Depending on the severity of exposure, it could be anywhere from five to ten years before symptoms manifest. By that point, the damage has a high rate of lethality.
Asbestos can be found in many areas.
Damaged floor tiles, old walls that have let the underlying structure become exposed, and even some pipes may have the fibres or sheets.
In most cases, as long as the material is intact, it is safe. It’s only if the fibres come loose due to damage that they can be breathed in. It may also be in the ground, as a consequence of construction methods that were typical of the time asbestos was legal to use.
Our school took great pains to secure and prevent any children from being exposed. Professional crews were called in to seal off contaminated areas, as well as inspect the rest of the grounds. A full sweep was conducted for safety reasons, and the work areas were sealed to prevent spread.
Asbestos is a grave, unseen danger. We spared no expense in making sure all of our students were safe.


Good journalists file clean copy. But what does that mean? This article gives journalists the basics they need to know to ensure that every character, word, sentence, and paragraph they intended to write gets correctly saved and reproduced on computer systems, and ultimately online and in print. You’ll learn enough to avoid the dreaded borked Unicode.
Writing clean copy
Clean copy is an established concept in print journalism. Conservatively, the term refers to text that is spelled and punctuated correctly and makes sense. As an editor who was formative in my development, the late Sid Adilman of the Toronto Star, put it, the goal is to write an article that “reads well.” Clean copy is a prerequisite for that.
But I want to expand the definition to encompass character encoding. Your copy can’t be considered “clean” unless and until it is stored and reproduced correctly. Getting character encoding right is an absolute necessity for working print journalists, which is all well and good except for the fact that nobody has ever bothered to teach journalists what character encoding is.
What you’re going to learn
By the time you’re done reading this article, you’ll gain knowledge of character encoding that leads to confidence that you can write clean copy and muscle memory and good habits to actually do it.
Sidebars to this article
Later (probably the week of 2011.11.21), I’ll divide this article up into a shorter main article with sidebars – to make it more digestible and to make linking to this information easier. (Does you colleague just need to know how to write “Skarsgård”? Link them just to the right page.)
The concepts involved in producing clean copy can extend way out to the horizon, but journalists don’t need to worry about expert-level details. Here is the complete list of facts you need to know.
Computers store characters as numbers. That includes visible characters like letters and numerals; whitespace characters like spaces and tabs; and invisible characters like optional hyphens. At root, they’re all numbers. A system of enumeration of characters is called character encoding.
In the past, there were dozens of conflicting sets of numbers used to enumerate characters. Those have all been superseded by a single numbering system, Unicode.
Unicode does not include every conceivable character, but every character you the journalist will need is available in Unicode. Corollary: There is no such thing as a “special character.” (Really, there isn’t.)
To write clean copy, everything you write, edit, pass on to someone else, receive from someone else, and publish has to use Unicode from start to finish.
Unicode is a large specification that can be expressed in a variety of ways, but in the normal course of events the only variation you need to know about is UTF-8. You don’t even have to know what that stands for.
In essentially every case, you just type, insert, or paste the actual character you want – just as with characters you find noncontroversial. In rare cases, you will refer to characters by their Unicode number. (That’s called using a character entity or escaping a character.)
There. Now you’re up to speed. For the working hack, it really is that simple.
Just type the character
The most important advice is the easiest: Just type the character you want. You may need to learn how to type it, but I’m going to teach you how. You may need to copy and paste it from another source. But the point is use the character you want right in your document. And do that everywhere – hed, dek, body copy, in RSS, on Twitter.
There are rare exceptions to this rule. When the character your system displays can be confused with something else or is simply invisible, as in the case of whitespace or non-breaking hyphen (see below), you need to enter a character entity, which uses a sequence of other characters to escape the character you actually want. In these cases, you’re specifying the character by an agreed-upon name or by its Unicode number. You do that by starting the name or number with an ampersand and ending it with a semicolon. Some examples, purely for illustration purposes:
&for ampersand &
You have to know this troublesome implementation detail because it is the only way to reliably enter and edit the few characters that demand this approach. Absolutely do not use this method to enter what you think are “special characters” in the day-to-day run of your work as writer or editor.
What can go wrong?
I want to make sure you know what I’m talking about, so I’m going to show you a few errors of character encoding. After you finish this article, you will be in a position to avoid borked Unicode like this for the rest of your career.
A mismatch in server and browser settings means the browser can’t figure out the character encoding and uses the wrong characters.
Characters are saved as numerical references instead of the actual character, but that process goes wrong.
The character may exist in the file, but it’s so badly encoded the browser can’t even guess what it is. (The question mark in a diamond is a character from the Apple Last Resort font. It’s widely seen in this scenario but it isn’t any kind of “standard.”)
Accented characters just disappear.
Smart quotes never live up to their name and simply go crazy.
If you need a poster child for character encoding, this is it
In the English language, the giveaway character that can conclusively prove your copy is dirty is this: ‘ (opening single quotation mark). Why?
If it’s missing or replaced by ' (neutral apostrophe), that means someone can’t type the character or thinks downstream systems can’t accept it, or those downstream systems changed it behind your back.
If it’s replaced by apostrophe (’), it means someone relied on so-called smart quotes and didn’t double-check for errors.
If it’s used where it shouldn’t be – a common occurrence, as in rock ‘n’ roll or ‘90s grunge rock – it means someone didn’t know the difference or (again) foolishly trusted smart quotes.
If you can’t get opening single quotation mark right, you probably can’t get anything right that isn’t a nice easy letter or a number.
Start using a good editor
You can bang out copy in Microsoft Word if you want. With modern versions of MS Word, that copy will always use Unicode. Problem solved? No, because Word is borderline useless when it comes to fixing someone else’s copy.
At a minimum, you need to be able to do all of the following:
Save and reopen files of unknown or incorrect encoding. (Goal: Always yield UTF-8 plain text or markup like HTML. Never yield word-processing formats like
Remove carriage returns from inside paragraphs and other places.
Reliably change neutral quotes to correct quotes (including when nested).
Reliably change any of the countless incorrect analogues of en and em dashes to the real thing.
Escape the rare characters that need them.
You can gin up macros to do most of these things in MS Word, but you have better things to do.
Maybe you associate writing on a computer with “word processing,” and associate word processing with the market leader, MS Word. But here I am strongly recommending you update your workflow to use a real text editor. You may not even know this category of software exists, but it does, and it is mature and can do everything you need.
Windows options: You shouldn’t be using Windows to edit clean copy. If you have no choice, consider Notepad++; Sublime Text; Dreamweaver. (Absolutely not the built-in Notepad utility, not even for emergency usage; it accepts Unicode handily but is too underpowered and inconvenient.)
Unreadable onscreen type leads to copy errors. Always use nice big fonts (16 pixels minimum in typical cases), and unless you know you need to, don’t use monospaced fonts, especially not Courier.
What characters do people get wrong?
Apostrophes and quotation marks
Neutral versions of either of those (' and ") do not cut it anywhere, at any time, outside of programming and markup.
When consecutive quotes follow each other, or when an apostrophe sits inside a quotation mark, you have to use at least a thin space to separate them, as described below.
Accents and diacritics
By consensus, we don’t have to write foreign words in their own script if it isn’t Latin script. We don’t have to write Москва for Moscow and 日本 for Japan. Foreign proper nouns with accepted English spellings, like Cologne (for Köln, Germany), don’t have to be changed.
But one source of unclean copy is the belief that a word that contains accents or diacritics is weird and foreign and that the accents are optional. Wrong. Accents or diacritics are intrinsic to correct spelling. Just as cant and wont are words that differ from can’t and won’t, resume and résumé are two different words.
In case I’m not making myself clear, leaving out accents means you’ve misspelled the word.
To write clean copy, you have to know what accents are called. You can’t use fake French names for accents; all of them already have English names. You cannot use vague, impressionistic, guaranteed-to-be-misunderstood descriptors like “the one that goes from left to right.”
Why learn the right terminology? You can’t work in ignorance, first of all, but more importantly, you have to be able to correct someone’s copy, or instruct someone on how to enter text correctly, over the phone, in person, or via chat – anywhere you can’t actually draw a character on a printout. (“No, the first letter is cap E acute. You sent me grave accent. Fix it.”)
- Acute (just the word “acute,” not faux-French “aksã aygoo”): Áá
- Grave (just the word “grave” that rhymes with “save,” not “aksã graav”): Àà
- Circumflex: Ââ
- Dieresis: Ää (“umlaut” is a term applied solely to German; an umlaut is also a dieresis)
- Cedilla (not “sedee”): Çç (Șș and Țț have a comma, not a cedilla, under them)
- Tilde (it’s two syllables, like Swinton): Ãã (Ññ is just n-tilde and is not called “enya”)
- Háček (“hatchek”) or caron: Čč (but Ď/ď, Ľ/ľ )
- Macron: Āā
- Breve (“breev”): Ăă
- Double acute: Őő
- Ogonek: Ąą
Important single letters from other languages:
- Nordic languages (Swedish, Danish, Norwegian, Icelandic), when viewed all together, use these letters:
- A ring Åå
- AE digraph (not “ligature”) or “ash” Ææ
- Slash O Øø
- Thorn Þþ
- Eth Ðð (that’s a voiced consonant at the end of the word eth, as in breathe)
(I’ve grouped these letters for convenience. None of these four languages uses all of them.)
- Turkish: Dotless Iı; dotted İi; Ğğ
That isn’t the full list of diacritics or letters, but the point is you must be able to name these letters and accents on sight, cold, without a cheatsheet. Do you think they’ll never come up in the copy you write? Well, maybe they won’t, but they’ll come up in copy you read and possibly in copy you edit.
What if the Icelandic banking system collapses? Who won the Turkish election?
If you’re an arts writer and think this sort of thing is never going to come up because it’s “too technical,” well, don’t half your friends work at Condé Nast? Then again, they can’t get that name right either:
And I assume you’ll someday have to name-drop the family of actors named Skarsgård, or review popular mystery writers like Jo Nesbø and Arnaldur Indriðason, or write a thinkpiece about cinéma vérité or causes célèbres.
And tell me: What kind of restaurant critic can’t spell chèvre?
The idea that accents are not really an integral and mandatory component of good copy – it’s just so passé.
Hyphens and dashes
You need to know when to use and how to enter an en dash (between these letters: a–b) and an em dash (between these letters: a—b).
Style guides may insist you use an em dash not surrounded by spaces, but that usage does not work online (browsers break lines unpredictably) and barely works in print. Use space-endash-space by preference.
Typewriter-style fake em dashes -- (two hyphens possibly surrounded by spaces) have to be converted. Don’t ever use hyphen-hyphen as a claimed em dash. First of all, it isn’t, and second of all, some system will surely come along and break a line between the dashes.
Space-hyphen-space is not an em dash and needs to be converted.
You have to manually inspect copy for en dashes errantly replaced by hyphen. I’m talking about copy that might have been correct in the original but was dumbed down for the Web by someone or some system who didn’t understand Unicode – e.g., converting New York–style pizza to New York-style pizza or New-York-style pizza.
Non-breaking hyphen is available and should be used, especially in small alphanumeric sequences (IRS W‑8B form) or in words that begin or end with a hyphen (left‑ and right-hand drive; free-speech and ‑assembly rights). As with whitespace (see below), you need to escape the character – enter it as
Your system may mis-encode the regular visible hyphen any number of ways, including as a non-breaking hyphen that is immediately followed by a displayed optional hyphen or as two hyphens.
The standard wordspace (what you get when you whack the spacebar on your computer) is noncontroversial in the hack context. (Behind the scenes, it causes a lot of trouble, but that isn’t your problem.)
Among the many available whitespace characters:
- Em space (between these letters: a b)
- En space (between these letters: a b)
- Thin space (between these characters: ’ ”)
- Non-breaking space (in the middle of this postal code: M5W 1E6)
These space characters are tricky enough that you should use character entities for them. Why? So you can identify them with certainty in source code. Two normal wordspaces look a lot like an em space. Of course no one writes two consecutive spaces in normal English prose, but HTML source code and many other contexts permit two consecutive wordspaces. To tell those apart from an intended em or en space, use a character entity for them.
For regular Web pages, just use
for em and en space. Thin space is, not surprisingly;
. Non-breaking space is
Dozens of arrow characters exist in Unicode and you should never use sequences of punctuation in their place. To show four of many options:
- Leftarrow ← not <--
- Rightarrow → not -->
- Uparrow ↑ not ^ (caret)
- Downarrow ↓
Many commonly-used fractions are available as predefined Unicode characters. There is no reason to write something like 3 1/4 ever again. (Also inadvisable because, somewhere along the way, a line will break between the integer and the fraction.)
- ½ · ⅓ · ¼ · ⅕ · ⅙ · ⅐ · ⅛ · ⅑ · ⅒
- ⅔ · ⅖
- ¾ · ⅗ · ⅜
- ⅚ · ⅝
Subscripts and superscripts
Do not try to fake subscript or superscript numerals by using smaller font sizes. Also don’t give up and just write a normal number inside parentheses or brackets. Use the actual Unicode numerals:
Superscribed and subscribed letters and other characters are barely available in Unicode. This is another way of saying you can rely only on sub/super numerals, not letters or anything else.
It shouldn’t surprise you that basic symbols exist in Unicode. As with arrows, you shouldn’t use other characters to fake them.
Currency: $, £, and ¢ are easy ones, but nearly 20 years after the introduction of the euro (not “Euro”), hacks still write currency values like “20.99 euros” instead of using the available € symbol (€20.99).
Legal: ©, ®, and ™ but not (C), (R), and (TM); servicemark ℠ and music publishing ℗ are available. ¶ and § can and should be used instead of “para.” and “s” or “S.”: ¶2, ¶¶7–8, §A2, §§1–3.
Heart: I♥NY as much as anybody, but I do not [heart] it or <3 it.
Math: The letter eks is not a multiplication sign; × is. (Hence no one buys a stack of “2x4s” at the lumber yard.) An opinion poll may be valid ±3 points 19 times out of 20, but it isn’t valid “+/-” 3 points.
And at the very least use an en dash for a minus sign in reporting temperatures and other figures. (We can discuss the vagaries of Unicode in this regard some other time.)
Muscle memory and habits
You can easily find guides on the Web about typing “special characters.” These won’t help you at all. True, you do need to learn the technical basics about how to enter a character that isn’t printed on your keyboard. But what all those online guides don’t tell you is you need to develop muscle memory and habits.
If you can touch-type, you need to be able to touch-type common characters like accents and dashes. You can’t stop to think about it; that’s the kind of barrier that makes people think “To hell with it!” and just enter an incorrect substitute character.
When typing isn’t an option, you have to develop reliable ways of solving the problem, which can be as simple as Googling the character and copying and pasting.
To form muscle memory and habits, you need practice, practice, practice. The way to do this is to write a lot of copy using characters that aren’t simple letters and numbers. Don’t do that often? Then put some time into your professional development and carry out exercises like these.
Print out, or just set up in a separate window, easy text that uses accents, like Wikipedia’s lists of foreign-language terms used in English (e.g., from French, from German). Sit down and retype a few dozen of the entries.
Look up any common concept or noun (water, sky, calcium, life, baby) at Wikipedia, pick a translation in the target language of your choice, and retype a few paragraphs.
Take some well-edited copy from a print publication (e.g., a popular U.S. consumer magazine like Vanity Fair or GQ) and retype a few paragraphs. (For advanced learners, try duplicating the New Yorker’s idiosyncratic style.)
At all times use correct quotation marks and em and en dashes even if not in the original (a skill to develop in itself). These exercises will begin the process of instilling the muscle memory of typing the right characters.
If you aren’t a ten-finger touch-typist, do the same exercises. Even if you hunt and peck, you have your own muscle memory to develop.
Three ways to enter a character
Excluding speech recognition and other edge cases, you have three options for entering any character.
- Type it on a hardware or onscreen keyboard. May include modifier keys like Shift, Option, Command, or Ctrl. May involve dead keys that do nothing until you type the next key (e.g., Option-n N to produce Ñ).
Look it up and paste it. This is by far the best option for the first time a document needs a truly rare character. But even in an age where we Google everything, this just never occurs to working hacks. Google the character you’re looking for and copy and paste it into your copy. (Now you see why you need to know what characters are called.) You then have the character at the ready for further copying and pasting. (Use Paste Special to paste as unformatted text in Microsoft Word or equivalent.)
Use a character picker. InDesign, Microsoft Word, Mac OS X, and countless other software “boasts” graphical character maps you can use to “easily” insert “special” characters. In practice they are phenomenally difficult and cumbersome to use and require near-expert knowledge just to figure out which category to look in. Use as a last resort.
And here’s how you absolutely are not going to enter a character:
On Windows, look up a number for a character and type it while holding down Alt, or type that number and then press Alt-X. Online guides tell you this is the only way to enter “special” characters. They’re wrong and they’re missing the point. It’s not that the numerical method is the only method, it’s the worst method. (Could you enter a full sentence of French text that way?)
Use “smart quotes.” Decades on, so-called smart quotes simply cannot handle English usage. It is smart quotes that cause the typical opening-single-quote errors mentioned before (rock ‘n’ roll, ‘90s). Even typographers make this mistake:
Systems cannot handle consecutive quotation marks (as in quotes within quotes). Smart quotes cannot disentangle typical British usage, which presents many structural ambiguities (opening single quote or apostrophe? closing single quote or apostrophe?). Advanced hacks, who are rare, can overcome the failings of smart quotes. Everyone else falls prey to them, and the victims are readers.
This is not a time for “platform equivalency”
Typically but not universally, print publications are all-Mac shops. Online publications, and freelancers and independent bloggers, very often use Macs.
These people have nothing to worry about. It is dead simple to write, save, and transmit clean copy on Macs. Important keystrokes on Mac have not changed since the introduction of the Macintosh in 1984 and it is readily possible for a ten-finger typist to touch-type them.
The problem here is Windows. You need to have a lot of Unicode knowledge even to debate the issue, but just take my word for it on two counts here, and accept that I am not saying this just because I am a Macintosh supremacist.
- At the system level, Windows has phenomenal Unicode support (noticeably better than Mac OS).
- At the user level, since the day Windows was introduced it has been punishingly difficult (bordering on impossible) to type anything that isn’t printed on the keycaps of a U.S. keyboard.
One explanation for why you see so many incorrect characters online is simple: The writers are on Windows, and even if they know the right character, they pretty much can’t figure out how to.
So: This is not a time for platform equivalency. Use of Microsoft Windows prevents people from producing clean copy in the real world. Hence they over-rely on smart quotes, but that just means the system beats you up twice – once in your inability to type a character, once more when the computer guesses wrong.
Solution for Windows users
There is a reasonable fix for professional writers using Windows: Turn on the U.S. International keyboard layout. Do that and all of a sudden you have the equivalent of a Mac keyboard layout and nearly everything just works. (More details.)
Common errors you need to fix
When somebody hands you copy, you need to do all the following to ensure it is clean:
Change all tab characters to space characters. Don’t just delete them, because they could be separating other characters or words and you don’t want to destroy that separation. Replace one tab character (^t in MS Word, \t in BBEdit) with one space.
Remove all soft-hyphen characters, especially word-initial soft hyphens used as a command not to hyphenate that word. These exported characters simply aren’t handled well by browsers. Soft hyphens exported by software like InDesign or newspaper composition systems like Harris or Atex will use the wrong character.
Soft hyphen displayed as ¬:
Soft hyphens erratically replaced by space or hyphen:
To make this work, export a test document known to have soft hyphens. Open that document in your text editor. Find the soft-hyphen character and save it in a document you can find later. Replace that character with nothing. Do the same with all your files from now on.
Any number of fake soft-hyphen characters are possible; you have to test your own system first to know which one it uses. Ideally your system would just stop outputting soft hyphens, but let’s be realistic.
If for some reason you want to add soft hyphens later, do so at that later stage. I strongly discourage this practice because it is the rendering engine (whatever sets the type in the final stage before a reader sees it) that should insert soft hyphens. Manually-inserted soft hyphens should be reserved for intentional fine control, not as a task you apply to every line of text.
Check every non-breaking space to ensure it really has to be there. Systems include
for a variety of spurious reasons, and your copy can be littered with them without your knowing. In particular, Mac users must check that inadvertent typing of Option-spacebar or Command-spacebar did not introduce one non-breaking-space character for each such keypress.
Remove linebreaks inside paragraphs.
Convert quotation marks and dashes (never a strictly automated process).
Exporting from Word and PDF
You will receive countless MS Word files and PDFs. These are a leading cause of borked Unicode, especially when block quotations from these sources are plunked inside correctly-encoded text.
What goes wrong?
Early MS Word versions – still very much in use in large corporate environments – didn’t use Unicode by default and mis-encode characters. MS Word is engineered to avoid displaying the wrong character, but it remains the wrong character internally and stays wrong when you paste or drag it somewhere else.
PDFs can include nearly any imaginable form of digital object, including visible characters interspersed with invisible characters and sentences with no space characters between words. (In that case a PDF merely displays a break between words even if it doesn’t actually exist.) What you see is not necessarily what you get in PDF.
The following workflow avoids most mis-encodings from Word and PDF.
Do not copy and paste from either of these sources. Don’t drag and drop, either.
You must export as plain text (UTF-8) in Word and then open the resulting file in your editor.
You also must export as Text (Plain) in Acrobat. Oddly, the Text (Accessible) setting produces worse results. Even this won’t work all the time because PDFs can include text that is hard to export. Open the resulting file in your editor.
Whether you like it or not, you have no real choice but to use Adobe Acrobat for this function, not any other PDF viewer.
Common errors on specific platforms
WordPress double-prime error. When typing inside the textarea on a WordPress blog with smart quotes turned on, any sequence that ends in a numeral followed by a neutral quotation mark becomes a numeral followed by a double-prime character, ″. This may also happen even if a period or comma sits between the numeral and the end quote. (I long ago reported this bug.)
Solution: Type real quotation marks, or at least always check for the double-prime character and change it.
The Awl/Gawker quote/emdash combo. Leading blogs like the Awl and Gawker use a nonsensical combination of neutral quotation marks but also em dashes. This practices makes believe that em dashes are easy characters while quotation marks are difficult. Do not follow this pattern.
Newspapers. Online versions of print newspapers, including the New York Times, export what are surely internally correct quotation marks as neutral. Do not follow this pattern.
I believe every publication, including every individual blogger, should specifically invite corrections of typos and copy errors. A lot of sites do that already, but I think it should be universal. And the invitation to submit corrections should specifically mention that readers can report characters that don’t show up properly. In other words, you or your publication should have a stated policy inviting people to report character-encoding errors in the same way they’d report any other copy error.
There’s so much to learn about Unicode that you could spend the next year doing so. You probably won’t. But if you do want to learn a little more, start with the resources listed in the Links section.


MVP is an architectural pattern, a derivation of the Model–View–Controller. It's represented by three distinct components: Model, View and the Presenter.
It was engineered to facilitate automated unit testing and improve the separation of concerns in presentation logic.
In examples you'll find a simple project built with MVP pattern in mind.
- Model is an interface responsible for the domain data (to be displayed or otherwise acted upon in the GUI)
- View is responsible for the presentation layer (GUI)
- Presenter is the "middle-man" between Model and View. It reacts to the user’s actions performed on the View, retrieves data from the Model, and formats it for display in the View
|Communicates with DB layer||Renders data||Performs queries to the Model|
|Raising appropriate events||Receives events||Formats data from Model|
|Very basic validation logic||Sends formatted data to the View|
|Complex validation logic|
Differences between MVC and MVP:
- View in MVC is tightly coupled with the Controller, the View part of the MVP consists of both UIViews and UIViewController
- MVP View is as dumb as possible and contains almost no logic (like in MVVM), MVC View has some business logic and can query the Model
- MVP View handles user gestures and delegates interaction to the Presenter, in MVC the Controller handles gestures and commands Model
- MVP pattern highly supports Unit Testing, MVC has limited support
- MVC Controller has lots of UIKit dependencies, MVP Presenter has none
- MVP makes UIViewController a part of the View component it's dumb, passive and...less massive ;]
- Most of the business logic is incapsulated due to the dumb Views, this gives an excellent testability. Mock objects can be introduced to test the domain part.
- Separated entities are easier to keep in head, responsibilities are clearly divided.
- You will write more code.
- Barrier for unexperienced developers or for those who don't yet work with the pattern.


The daylight-saving time has been in use for some time now across different countries in the world although not all. The daylight-saving time can be defined as the concept of changing the clock backward and forward. One important thing to know about the daylight saving time concept is that it was introduced during the world war one. The primary reason why they daylight saving time concept was introduced is because of the impact on the use of power because it was believed it a lot of the consumption rate. For the countries that are the daylight saving time or the DST adjust their clocks one hour forward when it is the start of the springtime and adjust it backward with one hour it is the autumn season which means that the time is standardized.
There are many such also of conducted studies to improve the efficiency of the time adjustment that is done for those that use DST. The findings by the scientists and the other researchers across the world to protect overtime the DST as lost the meaning. The reason why it has been proven that it has lost the meaning is because the negative effects supersede the positive impacts. Due to this, there are many people that have petitioned for the stop of the daylight saving time. The daylight savings petition is because of the following reasons.
Overtime people develop a sleeping pattern according to the schedule. The daylight savings time as the negative impact on the sleep because for countries that use it by shifting one hour backward, deprive people of their sleep. The impact of the deprived sleep varies with different people as they are affected negatively. One unique character with the human body is that it notices any changes in the pattern especially in sleeping pattern and to some people, they will suffer headaches as the body tried to adjust to the short-term changes on time. The increased cardiovascular conditions risks is another reason why these petitions to end the daylight -saving time.
It has been proven by many researchers that when people are adapting to changes in the sleeping patterns, they become less productive during the work days. Findings have proven that during the DST, many businesses experience was that how was by the employees as the entertain themselves using the Internet and the computers at the workplace. The concentration levels of the employees are lowering it is the DST season resulting in many workplace injuries. Due to the concentration levels also, many people across the countries that use DST, end up in fatal road accidents. The petition, therefore, is to rally for the end of DST.


Grim statistics on COPD cases in women
For generations of women born after World War II, making their mark toward equality in society and in the workplace often meant adopting a habit many men had embraced: smoking cigarettes. But experts say the consequence of that habit is now taking its toll on women of a certain age.
Chronic obstructive pulmonary disease (COPD) is responsible for more deaths in women than breast cancer and diabetes combined, according to the COPD Foundation. In 2010, COPD surpassed strokes to become the third-leading cause of death in America. More women are diagnosed with, and die from, COPD than men, a stark change from only 10 years ago; and more than 90 percent of deaths from COPD occur in adults 65 and older.
The No. 1 cause of COPD is smoking cigarettes, followed by industrial pollutants and other biohazards. But it's not just heavy lifetime smokers who are at risk. The COPD Foundation says if you have smoked even 100 cigarettes in your lifetime, you are at increased risk. Add in years of secondhand smoke from a time when lighting up was common in bars, restaurants and businesses, and the risk is heightened further. The National Institutes of Health notes that 1 in 6 people diagnosed with COPD have never smoked.
"Women's lungs are generally smaller than men's," says Jane Martin, a respiratory therapist and associate director of education at the COPD Foundation. "Smoking and hazards damage the lungs equally, therefore the women have more proportionate lung damage than a man does." What makes the disease even more insidious is that many women compensate for the shortness of breath by cutting back on physical activity, making their overall health worse.
Symptoms of COPD include shortness of breath and chest tightness. Another sign is if you get a cold that lingers longer than a week. There is no cure, but treatments and inhaled medications can relieve some symptoms.
About 15 million American adults have been diagnosed with COPD, but another 12 million are believed to have the disease and don't know it. Martin says women tend to ignore the warning signs. "She might think, 'Oh, I'm just out of shape, I'm getting older, I'm just tired.' " Making the problem worse is that some primary-care physicians do not suspect COPD when a woman complains of shortness of breath. Martin says the doctor will often diagnose the woman with bronchitis or asthma. "They're not thinking of women and COPD," Martin says.
For more, go to copdfoundation.org or the National Institutes of Health page at bit.ly/NIH-COPD.


Louis Emmanuel Chavignier (1922–1972) was an internationally renowned French sculptor. After a brief stay at the École nationale des beaux-arts de Paris, he went to work at the Louvre, where he restored objects from Egyptian and Chaldean antiquity. During the 1950s, he began to create his own artworks, influenced by his work as a restorer.
He executed a number of works of public art and integrations of art with architecture in France, notably at Vitry-sur-Seine and Blanc-Mesnil. Also on public display is his Le vaisseau lunaire, produced for Expo 67, on the shore of Lac des Nations in Sherbrooke.
- 27 Artworks
- Lac-aux-Castors Pavilion
- Chalet du Mont-Royal
On an oval concrete slab at the top of a wooded rise in Mount Royal Park, a small pavilion formed of five limestone monoliths supporting a ring is presented as a lovers’ trysting place. In the surrounding area are fragments of rock that seem displaced, like temple ruins. The artwork forms a place of encounter in which the rocks, which can be used as tables and chairs, offer a convenient spot for conversation.
There are many quotations of ancient architecture in the artwork. Menhirs, dolmens, cromlechs, and tombs are nostalgically evoked with these rocks, marking the lasting gesture of humans who conquer death only through their artistic creativity. “I don’t want to seduce, I want to disturb,” the artist summarized on the effect of strangeness produced by these unusual evocations. 1
On the other hand, the title suggests something magical in the composition, a sort of merry-go-round transporting viewers into another world where the everyday rules don’t apply. With its circularity and verticality, Le carrousel sauvage explicitly fits with the “carrousel” series that Chavignier executed between 1962 and 1969.
1. Pierre Cabanne, “Louis Chavignier parmi nous,” Coloquio, no. 80 (1989): 4 (our translation).


The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Accurate prediction of daily milk production is a crucial aspect of the dairy industry. During the past decades, although many models using various data analytic techniques have been proposed in literature to address the milk prediction problem, these models have yet to be widely applied in daily operations. Dairy producers need to predict milk yield at individual cow and group level. Given the increasing amount of milk production information collected every year, difficulty also arises from analyzing big data. To address challenges in dairy supply chains and help dairy producers, especially small-scale producers, make use of data analytics in milk supply decision-making, a targeted effort to develop a feasible and cost-effective tool, Milk Yield Prediction and Analysis Tool (PAT), is launched. This tool allows dairy producers to use various prediction models to discover insight into milk production and forecast future milk yield at both the individual cow and the group level. This paper provides a detailed discussion on the design of this tool and demonstrates how big data analytics can be applied in a cost-effective manner.
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XXfich-iz (the English word "fitch" is the same as "vetch"):
(1) qetsach (Isa 28:25,27; the Revised Version, margin has "black cummin" (Nigella sativa)). This is the "nutmeg flower," an annual herb (Natural Order, Ranunculaceae), the black seeds of which are sprinkled over some kinds of bread in Palestin. They were used as a condiment by the ancient Greeks and Romans. These seeds have a warm aromatic flavor and are carminative in their properties, assisting digestion. They, like all such plants which readily yield their seed, are still beaten out with rods. The contrast between the stouter staff for the "fitches" and the lighter rod for the cummin is all the more noticeable when the great similarity of the two seeds is noticed.
(2) kuccemim (pl.) (Ezek 4:9) the Revised Version (British and American) "spelt" (which see).
E. W. G. Masterman


Papers / Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE) 2004,20
The first example involves the real data given in Table 1 which are the results of an interlaboratory test. The boxplots are shown in Fig. 1 where the dotted line denotes the mean of the observations and the solid line the median. We note that only the results of the Laboratories 1 and 3 lie below the mean whereas all the remaining laboratories return larger values. In the case of the median, 7 of the readings coincide with the median, 24 readings are smaller and 24 are larger. A glance at Fig. 1 suggests that in the absence of further information the Laboratories 1 and 3 should be treated as outliers. This is the course which we recommend although the issues involved require careful thought. For the moment we note simply that the median is a robust statistic whereas the mean is not.


Black Pepper is pungent and hot in nature. Pepper has a warming effect and is suitable in cases of abdominal pain of cold and deficiency types. Pepper is also beneficial for nausea and vomiting due to cold invading the stomach. Pepper is beneficial for acidic stomach. If added to some fish recipes, pepper will help the body digest the fish and help to absorb the nutrition.
Pepper is good for appetite. Pepper warms the stomach and so is good for gastric cold or intestinal cramps caused by overeating cold damp foods such as some salads or raw fish. Pepper clears dampness from the digestive system. Szechuan Pepper is an even stronger solution for clearing damp from the digestive system and is also good for stiffness of joints and for poor circulation.


9 Innocent Habits That Might Be Ruining Your Immune System
Your habits could leave you vulnerable to disease. Here are the ones to avoid.
You don’t get enough sleep
While you’re asleep, your body ramps up the part of your immune system that learns the best ways to attack new bacteria, viruses, and other triggers. If you aren’t getting enough sleep, though, your body doesn’t have the chance to fight diseases as effectively, according to a study in European physiology journal Pflugers Archiv. Just six days of restricted sleep could prevent your body from using a vaccination effectively, and other studies have shown lack of sleep makes it harder to kick a cold. Aim for seven or eight hours a night to keep your immune system at its prime. Here, sleep doctors debunk sleep myths you still believe.
You sit all day
Lack of exercise could make you sicker longer. Upper respiratory tract infections lasted 42 percent longer in volunteers who worked out once a week or less than in those who did aerobic exercises five or more times a week, according to a study in the British Journal of Sports Medicine. The sedentary participants also had more severe symptoms. Squeeze in moderate exercise every day, like taking a quick walk during your lunch hour. Here’s more on how to recover from a day of sitting.
You feel lonely
Loneliness puts your body into fight or flight mode, according to research in the journal Proceedings of the National Academy of Sciences. The five-year study found that when people felt lonely, the hormone norepinephrine was higher. During crises, norepinephrine boosts production of the white blood cells that fight wounds. But in the process, it shuts down the virus-fighting part of your immune system, leaving you vulnerable to disease. If you’re feeling down, don’t wallow alone on the couch—ask a friend out for coffee or call a loved one for some support. Don’t miss these little ways to reconnect when you’re lonely.
You’re ALWAYS stressed
The pressure to hit a single deadline on time won’t cause major damage, but if you let your job stress you out even after office hours, you could be setting yourself up for sickness. Stress from a specific event has mixed results for your immune system—it puts your body’s defenses up before infections or wounds, but could also cause inflammation—while chronic stress could wreak havoc on immunity. For instance, people going through long-term stressful experiences are at higher risk of developing a cold than those without an ongoing stressor, according to a study in the Proceedings of the National Academy of Sciences. Read these tips to de-stress your workday.
You eat the wrong fats
Saturated fats kick your immune system into overdrive, causing inflammation. On the other hand, unsaturated omega-3 fatty acids are anti-inflammatory and help control some of the proteins that help your body recognize pathogens, according to a study in Nutrition Journal. Swap out a meal of saturated fat-heavy beef for salmon or tuna, which are rich in omega-3s, or cook with canola oil instead of butter. Check out these clear signs you need more healthy fats.
You take antibiotics at the first sign of a sore throat
Antibiotics disrupt the dialogue between your immune system and the bacteria—good and bad—in your body. Mice studies have shown that antibiotics can reduce certain disease-fighting white blood cells and the molecules that signal immune-boosting proteins to kick into gear, according to a report in The American Journal of Human Genetics. Your body might kick a disease faster while you’re taking the medication, but once your prescription is over, your immune system will be even more vulnerable. When possible, you might want to let your body fight a disease by itself before you ask your doctor for medication. Always ask your doctor these key questions before taking antibiotics.
Your partner’s immune system is lousy
If your partner doesn’t have a great immune system, you could end up suffering too. A study in Nature Immunology found parents who lived together had 50 percent less variation between each other’s immune systems than with a similar person in the larger population. The authors conclude that people who live together have the same environment and adopt similar habits.
You drink—a lot
Alcohol suppresses the immune system. Chronic drinking makes your white blood cells less effective at attacking harmful bacteria and makes your body less able to produce the cells that identify and kill bacteria and viruses. Even a full day after being drunk, your body will be weaker in its fight against infections, according to the National Institute on Alcohol Abuse and Alcoholism. Here are other health boosts that can happen if you stop drinking alcohol.
A healthy weight won’t just make you feel fit, but also will protect you from disease. Obesity is a type of malnutrition in excess, and it can alter the number of white blood cells in your body. Belly fat and the fat around your organs affect your immune system more than total body fat does, according to a report in the Proceedings of the Nutrition Society.


Definitions for errorˈɛr ər
This page provides all possible meanings and translations of the word error
Random House Webster's College Dictionary
a deviation from accuracy or correctness; mistake.
the holding of mistaken opinions.
the condition of believing what is not true:
I was in error about the date.
a moral offense.
a baseball misplay allowing a batter to reach base or a runner to advance.
the difference between the observed or approximately determined value and the true value of a quantity in mathematics or statistics.
Category: Math, Statistics
Law. a mistake in a matter of fact or law in a case tried in a court of record.
a postage stamp distinguished by an imperfection, as in design.
* Syn: See mistake.
Origin of error:
1250–1300; ME errour < L error <err(āre) to wander, err
mistake, error, fault(noun)
a wrong action attributable to bad judgment or ignorance or inattention
"he made a bad mistake"; "she was quick to point out my errors"; "I could understand his English in spite of his grammatical faults"
error, erroneous belief(noun)
a misconception resulting from incorrect information
(baseball) a failure of a defensive player to make an out when normal play would have sufficed
departure from what is ethically acceptable
error, computer error(noun)
(computer science) the occurrence of an incorrect result produced by a computer
part of a statement that is not correct
"the book was full of errors"
Kernerman English Learner's Dictionary
a mistake that results in problems
a mathematical/computer error; Someone in finance made an error.
an unwise decision
indicates a person made a mistake, not a machine
a crash due to human error
The letter was sent to you in error.
The state, quality, or condition of being wrong.
A mistake; an accidental wrong action or a false statement not made deliberately.
A failure to complete a task, usually involving a premature termination.
The difference between a measured or calculated value and a true one.
A play which is scored as having been made incorrectly.
One or more mistakes in a trial that could be grounds for review of the judgement.
To function improperly due to an error, especially accompanied by error message.
To show or contain an error or fault.
The block transmission errored near the start and could not be received.
Origin: From errour, from error, infinitive of erro. Cognate with , . More at err.
a wandering; a roving or irregular course
a wandering or deviation from the right course or standard; irregularity; mistake; inaccuracy; something made wrong or left wrong; as, an error in writing or in printing; a clerical error
a departing or deviation from the truth; falsity; false notion; wrong opinion; mistake; misapprehension
a moral offense; violation of duty; a sin or transgression; iniquity; fault
the difference between the approximate result and the true result; -- used particularly in the rule of double position
the difference between an observed value and the true value of a quantity
the difference between the observed value of a quantity and that which is taken or computed to be the true value; -- sometimes called residual error
a mistake in the proceedings of a court of record in matters of law or of fact
a fault of a player of the side in the field which results in failure to put out a player on the other side, or gives him an unearned base
The word error entails different meanings and usages relative to how it is conceptually applied. The concrete meaning of the Latin word "error" is "wandering" or "straying". Unlike an illusion, an error or a mistake can sometimes be dispelled through knowledge. For example, a person who uses too much of an ingredient in a recipe and has a failed product can learn the right amount to use and avoid repeating the mistake. However, some errors can occur even when individuals have the required knowledge to perform a task correctly. Examples include forgetting to collect change after buying chocolate from a vending machine, forgetting the original document after making photocopies, and forgetting to turn the gas off after cooking a meal. Some errors occur when an individual is distracted by something else.
Translations for error
Kernerman English Multilingual Dictionary
noun a mistake
His written work is full of errors.
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Water Consumption & Caffeine
The water you take in each day is more important than any other nutrient in your diet. Without it, you can quickly compromise your survival -- losing just 10 percent of your body’s water content can lead to muscle spasms, delirium, heat stroke and collapse. The amount of water you should consume each day depends to some extent on factors such as your activity level and the temperature of your environment. Dietary factors such as caffeine intake also affects how much water you need.
What Exactly is Caffeine?
Caffeine is essentially a drug that is common in coffee, tea, soda, energy drinks and chocolate. It stimulates your central nervous system and affects your brain by causing your adrenal glands to secrete adrenaline and by increasing the release of dopamine, a neurotransmitter that also responds to heroin and amphetamines. Caffeine can be mildly addictive, particularly if you consume it regularly. It can make you feel more alert for a brief period of time, but you might also experience side effects including insomnia, anxiety, restlessness, headache and an increased heart rate. In addition, caffeine can act as a diuretic.
Effects of Short-Term Use
The diuretic effect of caffeine increases your urine output. The more you drink in a short amount of time, the more water you could lose, especially if you are not used to caffeine. If you are exercising or are in a hot environment where you are already losing extra water due to perspiration, taking caffeine could magnify the potential for dehydration. For approximately every 100 milligrams of caffeine you consume – for instance, the approximate amount in one cup of coffee or two cups of black tea – you should drink an additional cup of water to compensate for the drug’s diuretic effect.
Effects of Long-Term Use
Using caffeine regularly over an extended period of time can lead to a tolerance of its diuretic nature. In other words, your body can adjust to long-term use of caffeine and might no longer lose large amounts of your body’s water through urination. However, this effect can be temporary and is reversed after you refrain from caffeine ingestion for days or weeks. Therefore, you may need to increase your water consumption as you begin to use caffeine again.
Your personal physiology can determine how caffeine affects your fluid balance. Drinking an extra cup of water for each cup of coffee is a convenient rule of thumb, but actual signs of dehydration may be a better way of determining your fluid balance. Thirst, weakness, fatigue, reddened skin and dry mouth are all indicators that you need to consume more water, regardless of how much caffeine you ingest. On the other hand, feeling fine without developing symptoms of dehydration may mean that your caffeinated beverages contribute to your fluid balance rather than detract from it.
A writer since 1985, Jan Annigan is published in "Plant Physiology," "Proceedings of the National Academy of Sciences," "Journal of Biological Chemistry" and on various websites. She holds a sports medicine and human performance certificate from the University of Washington, as well as a Bachelor of Science in animal sciences from Purdue University.


“What is the information we need from modeling? We need to know where, and we need to know when [effects occur].”—Nick Ogden
“How do you take all the disparate data from different sources, scales, and times and space and come up with something that people can use to make decisions?”—Gregory Glass
Many organizations are modeling the effects of climate change on local, regional, and global scales. Most models focus on a particular sector, such as agriculture, energy, or the economy. Fewer models exist for the human health sector. What does it take to model the health risks posed by climate change? Workshop speakers outlined the basic mechanics of and key considerations for developing useful models. Discussions focused on recent model developments for evaluating the health effects of climate-induced spread of vectorborne disease and other health risks of changes in water and air quality and temperature. Discussions also explored overcoming hurdles to improve modeling capabilities.
The models needed to understand climate change and its effects on human health are complex. How can the climate-change community—scientists, model developers, policymakers, and other stakeholders—get a handle on the complexity? Ben Zaitchik, of Johns Hopkins University, outlined three factors that correspond to how the Intergovernmental Panel on Climate Change frames the issue: the physical environment, ecology (“natural processes”), and institutions. Those three factors mediate the relationships between changing climate conditions and human health outcomes. They also interact with one another. For example, climate change may result in increased rainfall (a component of the physical environment), and increased rainfall may support conditions for an increase in the population of a disease vector (ecology) in a country that lacks adequate institutionalized programs for vector control (institutions). Increased rainfall, increased number of disease vectors, and inadequate vector control all have effects on human health systems, such as medical practice and disaster response. Throughout the process of modeling, “we must think about humans,” Zaitchik emphasized. Humans “modify our physical environment and are deeply involved in ecologic processes and institutions,” he said. It takes many scientific disciplines and tools in addition to climate science to understand the interactions among the three factors and associated health outcomes, including hydrology, geography, ecology, agriculture, sociology,
economics, biomedical science, and clinical medicine. When it comes to developing models, data to feed the models, and potential model applications, “we need developments in all those fields . . . to help us to understand climate,” Zaitchik said.
What information is needed from models of climate-change effects? “We need to know where, and we need to know when” effects of climate change will occur, said Nick Ogden, a senior research scientist in the Public Health Agency of Canada. Ogden described four basic steps in developing and applying models of health risks due to climate change. First, we gather “our knowledge of current potential influences of climate and weather” on particular disease risks. Second, a model is used to “integrate the knowledge into abundance or presence and absence of diseases.” Third, we use model outputs to “obtain a quantitative relationship between the climate and the . . . disease risk.” Fourth, “we use this simple quantitative relationship or perhaps some more complex model to produce estimates of future risk.” Ogden noted that models can be made to predict where an effect may occur, forecast effects in the near term, or project effects in the long term (Box 3-1). Model predictions, forecasts, and projections are used to help to decide and design “what we’re going to do” about health risks posed by climate change and to “produce adaptation tools”, Ogden explained.
Zaitchik noted that “in the climate-science world there is now a lot of talk about climate services,” information that helps the health community to make decisions. The current framework for model development is top-down, beginning with climate and ending with health outcomes. Somehow, data on climate, physical environment, ecology, institutions, and human dynamics coalesce to “tell the health-system people what they’re supposed to be doing.” Zaitchik said that “a grand challenge” is to determine how decision-making needs of the health-system practitioners ought to drive model development from the bottom up. “We have this global framework for climate services that is fantastic,” Zaitchik said, and the US National Oceanic and Atmospheric Administration (NOAA), the US Environmental Protection Agency (EPA), and many others are working on this problem. And yet, he asked, “how do we actually transform communities to think in this way and rebuild our tools to make [climate services] work?”
How modeling is approached depends heavily on the needs of the user, noted Sari Kovats, of the London School of Hygiene and Tropical Medicine. The priorities of local, state, regional, national, and federal governments are different, she stressed. Hence, Kovats, George Luber, of the US Centers for Disease Control and Prevention (CDC), and other workshop speakers emphasized that a critical component of any model is its scale. The methods and assumptions used in modeling depend on the scale, Kovats said. The scale determines what data are available to users of model outputs.
The temporal scales range from hours to multiple decades, Luber explained. On the spatial scale, there can be a city or international range. The policy planning horizons range from annual budgets to infrastructure meant to be in place for multiple decades. Anthony Janetos, director of Boston University’s Frederick S. Pardee Center for the Study of the Longer-Range Future, said that there is generally a tradeoff between a model’s spatial resolution and the period of time that it simulates. High-resolution climate models cannot be used for long-term simulations. Long-term simulations inevitably have lower spatial resolution than many climate-change scientists desire, he said.
How model outputs are interpreted also depends on their scale, Mary Hayden, of the National Center for Atmospheric Research (NCAR), pointed out. National and regional
Definitions: Predictions, Forecasts, and Projections
Nick Ogden provided definitions that his research group uses to frame different types of climate-change model outputs:
Predictions tell where an effect is occurring
Forecasts tell where and when an effect is likely to occur in the next week or month. As models move toward smaller temporal and spatial scales, they incorporate larger numbers of elements and involve a greater degree of complexity.
Projections estimate where and when an effect is likely to occur in the next decade, decades, or century.
assessments are great, but they can mask communities that are living in marginal conditions. If the goal is to mitigate hazards and develop adaptation strategies, models need to be adjusted for “local ecology” information. “Local-level assessment ensures a more targeted intervention, response, and adaptation,” Hayden explained.
In general, efforts to integrate climate-change models so that they can show the combined effects of different sectors are in their infancy. “We know that food and water interact, health interacts with many factors, and heat, urbanization, and air pollution all interact,” Kovats explained. Several types of modeling are used to study those interactions: one-way modeling, one-way modeling that includes adaptation and institutional responses, and two-way modeling (Box 3-2).
There are many challenges in model integration. For example, food security is important, but many facets of how the US food system works are not captured by the way that we have interconnected our agriculture, climate, and economic models, said Molly Brown, of the National Aeronautics and Space Administration. Brown came to that conclusion as a result of putting together a report on food security for the US Global Change Research Program’s recent National Climate Assessment.
Of the efforts toward intersectoral model integration, the furthest along are associated with combining modeling studies in different sectors, such as agriculture and hydrology, to explore interactions between sectors. The integrated-modeling community has been doing a lot of experiments with one-way modeling of effects, mostly physical and biologic effects, Janetos said. Studies on the effects of climate change rarely extend beyond physical and biologic effects to human health or economic consequences.
Scientists studying health effects of climate change are endeavoring to generate data that link environmental changes to health outcomes and then to incorporate the data into models of health risks posed by climate change. Three subjects that many scientists are focusing on are 1) disease vectors, 2) water quality, and 3) heat and air quality. The World Health Organization recently completed a quantitative risk assessment of climate change with respect to selected causes of death, the first assessment of its kind (Box 3-3).
Three Types of Integrated Models
Anthony Janetos defined three types of integrated modeling studies that endeavor to represent all world regions and sectors—such as agriculture, hydrology, and economics—to explore their interactions. Such studies do not always include health effects.
One-way models include climate variables as additional drivers of both disease and nondisease pathways of health outcomes. These are classical climate-impact/risk studies and include many of the models discussed in the workshop.
One-way models that include adaptation and institutional response assume that the health systems and institutions of 20, 30, or 50 years from now will not be the same as today’s. These models come closer to identifying actual health outcomes than simply assessing risk.
Two-way models include feedback from health outcomes and adaptation on the economy and on later consequences for both mitigation and future demographics. They offer the potential for “a complete integration of climate effects on health”. The value of two-way modeling is its ability to provide a better understanding of how the health effects themselves interact with future demographics.
Disease Vectors and Health
Ogden described models that are used to understand the effects of climate change on vectorborne diseases. “Historically, climate has had a relatively small role in the variation in the geographic occurrence of vectors” because such human activities as habitat alteration, vector-eradication programs, and adaptation (such as the use of bed nets) were considered more important drivers, Ogden explained. However, he hypothesized that climate change will be especially important in developing countries because of their relative inability to control the spread of vectorborne diseases. Most modeling efforts related to climate change and vectorborne disease focus on estimating future occurrence or abundance of disease vectors; this requires knowledge about various factors involved in vectorborne-disease cycles, including vector biology, reservoir host dynamics, host infection and transmission dynamics, and land-use dynamics, Ogden said. The advantage of models developed thus far is that they are built on “unequivocal” data—“true observed field or laboratory relationships between climate and some important attributes of the vectors or the pathogens”.
Simple mathematical models can be used for such science policy activities as country-level risk assessments or benefit–cost assessments. Simple models incorporate only one or two factors that have a known relationship between climate and a disease vector. Ogden and colleagues are using simple climatic indicators to project the distribution of the Asian tiger mosquito (Aedes albopictus) in Canada. The Asian tiger mosquito is a potential vector of chikungunya, an infectious disease typically found in the Caribbean. The number of infected travelers returning to Canada from the Caribbean is increasing because of the chikungunya epidemic in the Caribbean. Ogden compared two simple mathematical models that produced different outcomes. The model based on overwintering and annual mean temperature produced a map showing that the mosquito would not spread into Canada. The model based on temperatures in January and the summer and on annual rainfall produced a map showing that the mosquito could spread into Canada. “Much of the variation comes from the use of different indicators; this is one of the problems with simple models,” Ogden said.
Complex simulation models are used when a decision-maker needs to account for many variables and detailed information. The more complex models can be used to address such
World Health Organization Quantitative Risk Assessment of Climate Change with Respect to Selected Causes of Death, 2030s and 2050s
In fall 2014, the World Health Organization (WHO) published a report on the first quantitative assessment of the health effects of climate change on a global scale. The report was prepared by a multidisciplinary, multinational team. Workshop speaker Sari Kovats was one of the report’s four editors. Kovats gave workshop participants a brief overview of the report objectives, approach, and model end points.
Objectives: The risk assessment was conducted in response to a WHO health-assembly mandate to update what is known about global health risks posed by climate change. No assessment of health effects of climate change had been conducted in over a decade.
Approach: The assessment looked at a “future world with and without climate change”. The integrated modeling was conducted with one carbon dioxide emission scenario (A1b emissions trajectory), one world population projection out to the year 2100, and three economic-growth scenarios: high growth, base-case (middle) growth, and low growth. Model assumptions included some adaptation in response to climate change. Kovats explained that for all health categories except mortality due to coastal flooding, the models assumed general improvement in population health due to improvements in economic development. For flooding, the models assumed increased population vulnerability due to rapid urban development in coastal areas.
Model End Points: The risk assessment included annual projections of mortality from all causes and from six specific causes: heat (in people over 65 years old), coastal flooding, diarrheal disease, malaria, dengue, and undernutrition. Of particular interest was the distribution of mortality in different regions. The models were “all fitted with the best available observational global data”,,” Kovats said, although in the cases of heat and diarrhea outputs from statistical models based on locational data were included.
Kovats shared conclusions drawn both from the risk assessment and from the process of conducting it. An important message of the 2014 WHO risk assessment is that “even if you assume a lot of adaptation and high economic growth, the effects are still adverse,” she said. In addition, “the effects are regionally focused”; for example, projected malaria-caused mortality is concentrated in eastern African countries. However, limitations need to be addressed. “We know that climate change will have more complex effects on health and on determinants of health” than the assessment includes, and “the uncertainties are large.” Identifying uncertainties is useful because it helps us to “point to where research is needed”, but Kovats cautioned that “we need to develop better methods to communicate and describe them.”
programmatic activities as risk mapping to determine targets for disease surveillance or intervention strategies, identifying populations at risk, and predicting evolution of new pathogenic variants, Ogden said. He emphasized that complex simulation models are the only option for making dynamic projections of a vector’s spread under different conditions. Ogden and his colleagues used a complex simulation model to assess Lyme disease emergence in Canada. The model was used to map projected distributions of blacklegged tick (Ixodes scapularis), the vector of Lyme disease, in 2020, 2050, and 2080. The risk map shows a “high risk” of spreading into most of eastern Canada. Ogden’s group validated its findings with a prospective study. “Unfortunately, it’s gone from a modeling exercise to a public-health issue,” he said. He added that “systematic surveillance . . . in time and space” is needed to develop useful simulation models for other disease vectors.
Ogden noted that a weakness in modeling efforts is in the translation of projections of vector presence into cases of disease. “The ultimate goal is to correlate human risk with vector population densities and climatic variables so that we can project how climate change will affect disease risk,” said Charles Benjamin Beard (Ben Beard), of CDC. To do that, “we need much more information on the distribution and abundance of vector populations, such as the
blacklegged tick,” he said. We also need local disease occurrence and information on the effects of temperature and precipitation on local vector populations. Beard emphasized the need “to continue to push the models to finer resolution” because public-health assessment and response are conducted at the local level.
Water Quality and Health
Juli Trtanj, of NOAA, discussed current efforts to develop models of climate-change effects on waterborne diseases and water-related illnesses. Waterborne diseases and water-related illnesses can arise through many pathways—exposures to bacteria or viruses in drinking water, to algal blooms in recreational water, to chemical contaminants in groundwater, and so on (Figure 3-1). The pathways are complex: the water cycle is combined with infrastructure, land use, and other biologic and physical factors. Trtanj explained that the reasons that the climate-change community is not farther along in developing coupled models is that neither the basic science underlying the water–health outcome pathways nor coupling of the factors involved is well understood. Trtanj indicated that although models of climate effects on sources of water contamination or on human exposure to water contamination are not yet advanced, such models are important stepping stones toward modeling health outcomes.
Figure 3-1 Waterborne-Disease Pathways, Freshwater–Marine Continuum
Julie Trtanj used this illustration to show the many factors in the pathway that links climate change to waterborne diseases and water-related illnesses. Such climate drivers as increasing ocean temperatures, ocean currents, and sea-level interact with exposure to contaminants from urban and rural environments or wildlife. Humans may be exposed to pathogens or other contaminants through drinking water and recreational or occupational water uses. Source: Juli Trtanj, workshop presentation, slide 3. Based on image originally created by Hans Paerl of the University of North Carolina, Chapel Hill for the US EPA.
Trtanj discussed a few case studies that used modeling on a regional scale to demonstrate “where we are” with modeling. One study looked at how projected increases in storms that result in sewage overflows may affect drinking water in the Great Lakes. “We already know that we are expecting an increased incidence of precipitation events because of climate change, and 67% of waterborne-disease outbreaks are preceded by precipitation events,” Trtanj said. In the Great Lakes, she explained, intense rainfall taxes the wastewater-treatment infrastructure. Researchers developed a model that projected future increases in rainfall. The result was that future rainfall would exceed the amounts planned for by wastewater managers. The rainfall output of the regional precipitation model was then used as an input for an “infrastructure model” of “how much water is going to be coming through the pipes.” The bottom line is that the model predicted that sewage overflows will increase by 20%, Trtanj said.
Trtanj and Jan Semenza, of the European Centre for Disease Prevention and Control, also described models for investigating climate-change effects on water temperature in relation to the potential for outbreaks of Vibrio species, bacteria that occur naturally in coastal waters. Vibrio can cause gastrointestinal-tract illnesses and wound infections and are responsible for 95% of seafood-related deaths in the United States. “If your doctor is not prepared for wound infection in the emergency room, you might well lose your limb,” Trtanj emphasized. Although there are not many cases of vibrio infection, there is a shift in the range of the bacteria in coastal waters, she said. Semenza was involved in an effort to predict the likelihood of vibrio infection in the Baltic Sea. V. vulnifucus starts to bloom when sea temperatures exceed 15°C and salinity is low. The research team used geospatial tools to monitor surface temperature and salinity to predict the likelihood of the occurrence of vibrio infection. They developed the Vibrio Risk Model. Semenza also investigated the relationship between West Nile fever (WNF), which is driven by the presence of infected birds, and climate’s influence on water temperatures in southeastern Europe. After analyzing the factors involved in a major outbreak in 2010, he and colleagues put together a multivariate model that included water temperature, the presence or absence of wetlands, and the presence of the virus in the previous year. The model successfully predicted the incidence of WNF in 2014.
Trtanj summarized the status of models of climate-change effects on waterborne diseases and water-related illnesses as mostly qualitative but quantitative when data are available; mostly regional, subregional, or local but not global; and mostly statistical although more dynamic, mechanistic models are needed. It will be important to incorporate “risk windows” for waterborne diseases into the models; it is necessary to factor in the habitat suitability and period that would be associated with changes in risk, said Erin Lipp, of the University of Georgia College of Public Health. Current models are able to link climate-induced changes to environmental exposures but have not linked them to health outcomes, and they do not include social variables, Trtanj said. She stressed that “gaps abound” and added that “we have to have the fortitude as agencies and scientists to figure out what we need to do, and do it,” even with the knowledge that advances will be neither inexpensive nor fast.
Heat, Air Quality, and Health
It is “critically important” to understand how environmental stressors, such as air quality, affect human health today if we are to understand what happens to the relationship in a changing climate, stressed Michelle Bell, of Yale University. Research has demonstrated that human exposure to tropospheric ozone causes “increased risk of hospital admissions,
premature mortality, increases in such respiratory symptoms as coughing and wheezing, reduced lung function, and other conditions.” More than 100 million people in the United States live in areas that exceed the US EPA’s health-based ozone standard, she said. Climate change may affect tropospheric ozone through multiple pathways, including changing precipitation patterns, changing wind speed and direction, and increased temperature. “Higher temperature means higher ozone,” Bell said. She explained that higher average temperatures increase the speed of chemical reactions for ozone formation and increase emissions of natural ozone precursors.
Bell described a study that her group published that used global climate, air quality, and meteorologic modeling to investigate how climate change could affect summer ozone concentrations in 50 eastern US cities. The goal was to “isolate the effect of climate on health”, so they modeled ozone emissions if we experienced the projected climate of 2050 today. For this study, estimates of what ozone emission magnitudes, technology, or population would be like in 2050 were not needed. “All the cities showed either a negligible difference or an increase in ozone,” she said. In particular, she said, the models showed increases of 12% or more in cities in the upper Midwest, including Ohio, Michigan, Indiana, and Illinois. Uncertainty of regional effects was somewhat high; the overall models projected that the number of days with unhealthy ozone concentrations would increase.
Bell told the audience about an exercise that used different models and climate scenarios to investigate how heat waves linked to climate change might affect mortality in Chicago in 2081–2100. The models accounted for changes in population. All the models and scenarios showed an increase in mortality. “The biggest uncertainty was associated with the choice of climate-change model,” Bell said.
Hayden pointed out that NCAR has developed a risk map of heat-related mortality at the census-block level for the city of Houston. The map is based on outputs of a hierarchic model in which spatially varied coefficients are based on death counts, numerical-model weather simulations, and census and parcel data, Hayden said. The risk maps produced from the model outputs help researchers to understand differential vulnerability. “We have learned that an increase in heat-stress nights will increase mortality and that extreme heat disproportionately affects the elderly, those who are socially isolated, those of low income, blacks, and people who use public transportation.”
The model also is able to look at each census block and determine what demographic factors contribute to risk at that level. A publicly available map enables users to find the nearest cooling centers, such as the closest community centers, pools, or Walmart store. The map shows how far away cooling centers are and the centers’ hours of operation. And it gives users access to CDC’s tips for cooling oneself immediately, Hayden said. “We think that these maps are an important step toward including drivers of vulnerability on multiple scales. They connect people with where they are, and they increase the ability of communities and stakeholders to develop a program to mitigate risk,” she said.
The climate-assessment literature tends to be extremely cautious about projecting health outcomes. Most studies are couched in terms of risk in part because whether adaptation is included is highly variable in the underlying literature, Janetos said.
It is difficult to link changes in climate with public-health outcomes because of the large variance in data and the low signal-to-noise ratio, Semenza said. Another challenge is dealing with multifactorial disease patterns that involve complex interactions with different drivers and teasing out the contributions of the different drivers. A third difficulty involves attributing individual climate events to health outcomes, he said. “Any climate-related effect on health is mediated by other physical and environmental factors. There is no such thing as a direct climate effect,” Zaitchik emphasized; for example, the built environment plays an important role. There is extreme heterogeneity in rural and urban environments with regard to exposure to heat and air quality, Luber said. “Even within an urban environment, there is great variability in a census block; even the side of the street can affect exposures,” he said.
Further complicating the challenge is the need to factor in what the Intergovernmental Panel on Climate Change calls “natural mediators”, such as the ecologic and biologic processes associated with the pathogens that cause infectious disease and with allergens, Luber said.
Brown, who was involved in the US Global Change Research Program’s recent National Climate Assessment, pointed out that many agricultural models do not include pests and disease and therefore could be optimistic in their projections of agricultural output in 2050 and 2100. “Such secondary effects may be enormous, especially in light of the acceleration of organism changes that we are trying to prevent with genetic engineering.”
No surveillance system attempts to link effects of climatic events to real outcomes, Semenza said. Many health effects are institutionally mediated, Luber added, pointing out as an example that climate change does not directly cause famine.
Public-health leaders often lack knowledge about climate change or shy away from the issue because it is not seen as a winnable battle, observed Richard Jackson, of the University of California, Los Angeles.
Systems modelers do not necessarily have the same objectives as stakeholders, said Gary Geernaert, of the US Department of Energy. Even among the world’s top modelers of the health risks posed by climate change, it is not always clear what questions the models are being produced to answer, said Kristie Ebi, an independent consultant with ClimAdapt, LLC.
That all adds up to a massively interdisciplinary problem, Zaitchik said. It is easier to model exposures and risks than health outcomes, he commented.
Furthermore, many data have been collected on the possible health effects of climate change, but not many have been collected in a desirable way, Ogden said.
An important issue related to collecting data is privacy concerns, said John Balbus, the senior adviser for public health in the National Institute of Environmental Health Sciences. “Are there ways to aggregate to ameliorate that issue?” he asked.
Georges Benjamin, of the American Public Health Association, raised the potential value of insurance claims data. Peter Berry, of Health Canada, pointed out that his agency has been trying to improve its links with the urban-planning community.
Models addressing climate change and health can leverage many existing data, said Anne Grambsch, of EPA. They include data on disasters, such as air pollution, and health data and research data focused on temperature sensitivity. Many models control for weather, she pointed out.
Databases contain many types of data, but it is important to understand the implications of how they were collected, Beard said. We need not only to put data into a model but work with people who understand the data. For example, in the United States, cases of disease are recorded by county of residence, not by where people might have been exposed to disease agents. Thus, if a case of a disease is related to travel, that is not captured, he said.
The availability of new satellite data and of expanded data services and low-cost sensors is improving our ability to model the physical environment, Zaitchik said. NASA’s Global Precipitation Measurement Mission, on a satellite launched in February 2014, is “game-changing”, he said. It provides more data on global precipitation than its predecessors gathered and at a much higher resolution, less than 10 km, with multiple passes each day. A satellite scheduled to launch in January 2015 will collect unprecedented information on soil moisture throughout the world with better resolution and the ability to “see through” vegetation to collect information that cannot be collected now. And NASA’s Giovanni data services are making satellite data more accessible than they were previously, he added.
Now that researchers have access to more than 35 years of satellite data, they can capture decadal-scale variability related to local environmental characteristics in a way that can reveal something about climate change, Zaitchik pointed out. The open-data policy that most institutions have adopted gives scientists better information to use in analyzing how the climate is changing.
The increased availability of sensors facilitates collection of local data, which in turn can add greater spatial resolution to models, Zaitchik continued Many of the sensors are small and inexpensive enough to be placed almost anywhere. The ability of cell phones both to act as sensors and to share data via crowd-sourcing allows interested citizens to get involved in data collection. Technologies for assimilating all the data collected by the satellites and sensors are also improving, he said.
Scientists’ increasing use of geographic information systems and information from remote sensing allows modelers to incorporate potentially useful data from such sources as weather stations, habitat maps, and digital elevation models, Ogden said.
New datasets on human mobility are also helping climate modelers. Those data, often captured by mobile phones, enable models to factor in “the human side of the ecology” in addition to the environmental ecology, Zaitchik said. An emerging field is coupled analysis that combines information about human population dynamics with such information as parasite population dynamics. Zaitchik said that he is working on a coupled analysis of how human and mosquito dynamics in the Amazon can affect malaria rates.
It is clear that diverse approaches are needed to model the health risks posed by climate change, Ebi summarized. Models can help to provide insight into exposure–response relationships, including how the relationships may change. They can also serve as early-warning systems, she said. And some can help to identify prices and benefit–cost relationships in association with climate variability and long-term change. “We do not know what the future will look like, so models have different sets of assumptions. As we move forward, we will need various models with various assumptions to address the questions that policy-makers will ask us,” she said.


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