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Estimating the Prevalence of Autism Spectrum Conditions in Adults: Extending the 2007 Adult Psychiatric Morbidity Survey

1 Feb

You may recall that a couple of years ago a study came out looking at the prevalence of autism in adults in the United Kingdom. They found a prevalence of about 1%, the same as in children.

There’s now a follow up study. The press release is below. The study can be found here. I hope to have the time to go into this in more detail in the next couple of days.

University of Leicester researchers lead on new autism study published today
Britain’s first adult autism survey reveals previously ‘invisible’ group with autism

New research on autism in adults has shown that adults with a more severe learning disability have a greater likelihood of having autism.

This group, mostly living in private households, was previously ‘invisible’ in estimates of autism.

Dr Terry Brugha, Professor of Psychiatry at the University of Leicester, led research on behalf of the University for the report Estimating the Prevalence of Autism Spectrum Conditions in Adults: Extending the 2007 Adult Psychiatric Morbidity Survey, which has today been published by the NHS Information Centre.

The report involved a survey of adults from learning disability registers in Leicestershire, Lambeth and Sheffield between August 2010 and April 2011.

Today’s report presents findings from a new study based on a sample of people with learning disabilities living in private households and communal care establishments. The findings are combined with information from the Adult Psychiatric Morbidity Survey (APMS) 2007, previously published by the NHS Information Centre, which included research on autism also led by Dr Brugha.

Dr Brugha, also a consultant psychiatrist working in the NHS with the Leicestershire Partnership NHS Trust, said: “We were surprised by how many adults with moderate to profound learning disability had autism because previous estimates pointed to lower rates in this group. Because they form a very small part of the adult population, when we added these new findings to the rate we had previously found in adults living in private households, and able to take part in our national survey in 2007, the overall percentage of adults in England with autism did not increase significantly over our 2007 estimate of 1%.”

“Our finding that about 60% of men with profound learning disabilities and 43% of women with profound learning disabilities have autism has never been shown previously. It may also seem surprising how many live at home with parents or carers who provide 24 hour care and shoulder a considerable burden: 42% of men and 29% of women with severe learning disabilities living with family members and in other private households have autism. Taken together with the 2007 survey findings this means that most adults with autism live in private households, and before these two surveys they remained largely invisible”.

Dr Brugha added “This new information will be of particular importance for those who plan and provide services to support those with learning disabilities. In March 2010, the Government published a national strategy for autism and guidance for the condition, with the view to improving the quality of services provided to adults with autism in England. Such improvements can only be achieved if the number of people with recognised and unrecognised autism is quantified. The strategy gave special emphasis to the need to train staff who have responsibility for identifying people with autism and their care. It will be vital to repeat such studies in future years in order to make sure that the national strategy is working effectively.”

Sally-Ann Cooper, Professor of Learning Disabilities at the University of Glasgow, who also contributed to the latest study commented: “Until now routine statistics have not been gathered on the numbers of people with learning disabilities who also have autism leaving this as a hidden problem. Our study clearly shows that the more severe to profound an adult’s learning disability is, the more likely they will be found to have autism if actually assessed.”

New Definition of Autism May Exclude Many, Study Suggests

20 Jan

The New York Times reports New Definition of Autism May Exclude Many, Study Suggests. The study is not published yet and was presented at a conference in Iceland.

The Times reports:

The study results, presented on Thursday at a meeting of the Icelandic Medical Association, are still preliminary, but they offer the latest and most dramatic estimate of how tightening the criteria for autism could affect the rate of diagnosis. Rates of autism and related disorders like Asperger syndrome have taken off since the early 1980s, to prevalence rates as high as one in 100 children in some places. Many researchers suspect that these numbers are inflated because of vagueness in the current criteria.

The conference program doesn’t have abstracts, just paper titles. Prof. Volkmar had two talks on autism: “The Changing Face of Autism: An Introduction and Overview” and “Understanding Autism: Implications for Health Care”. This leaves us with the Times article as our source for information.

According to the Times:

In the new analysis, Dr. Volkmar, along with Brian Reichow and James McPartland, both at Yale, used data from a large 1993 study that served as the basis for the current criteria. They focused on 372 children and adults who were among the highest-functioning and found that over all, only 45 percent of them would qualify for the proposed autism spectrum diagnosis now under review. The focus on a high-functioning group may have slightly exaggerated that percentage, the authors acknowledge.

The Times has quotes from Catherine Lord (who, amongst other achievements, is one of the authors of the ADOS) who disagrees with Prof. Volkmar to some degree:

Dr. Lord said that the study numbers are probably exaggerated because the research team relied on old data, collected by doctors who were not aware of what kinds of behaviors the proposed definition requires. “It’s not that the behaviors didn’t exist, but that they weren’t even asking about them — they wouldn’t show up at all in the data,” Dr. Lord said.

The question of how the DSM 5 will change the criteria for how autism is defined has been a subject of great speculation and some study. One can find parents claiming that the DSM 5 is designed to redefine autism as only “high functioning” all the way to autistics worried that many with Asperger syndrome will no longer be classified as autistic.

The results presented by Prof. Volkmar would suggest that “classic” autism, PDD-NOS and Asperger syndrome would all see significant changes:

The likelihood of being left out under the new definition depended on the original diagnosis: About a quarter of those identified with classic autism in 1993 would not be so identified under the proposed criteria; about three quarters of those with Asperger’s would not qualify; and 85 percent of those with P.D.D.-N.O.S. would not.

As noted above, this is not the first study to consider the DSM 5 and autism. For example, a group from Finland published Autism spectrum disorders according to DSM-IV-TR and comparison with DSM-5 draft criteria: an epidemiological study. they found the DSM-5 draft criteria were ” less sensitive in regard to identification of subjects with ASDs, particularly those with Asperger’s syndrome and some high-functioning subjects with autism.”

Abstract
OBJECTIVE:

The latest definitions of autism spectrum disorders (ASDs) were specified in DSM-IV-TR in 2000. DSM-5 criteria are planned for 2013. Here, we estimated the prevalence of ASDs and autism according to DSM-IV-TR, clarified confusion concerning diagnostic criteria, and evaluated DSM-5 draft criteria for ASD posted by the American Psychiatry Association (APA) in February 2010.
METHOD:

This was an epidemiological study of 5,484 eight-year-old children in Finland, 4,422 (81%) of them rated via the Autism Spectrum Screening Questionnaire by parents and/or teachers, and 110 examined by using a structured interview, semi-structured observation, IQ measurement, school-day observation, and patient records. Diagnoses were assigned according to DSM-IV-TR criteria and DSM-5 draft criteria in children with a full-scale IQ (FSIQ) ?50. Patient records were evaluated in children with an FSIQ <50 to discover diagnoses of ASDs.
RESULTS:

The prevalence of ASDs was 8.4 in 1,000 and that of autism 4.1 in 1,000 according to DSM-IV-TR. Of the subjects with ASDs and autism, 65% and 61% were high-functioning (FSIQ ?70), respectively. The prevalence of pervasive developmental disorder not otherwise specified was not estimated because of inconsistency in DSM-IV-TR criteria. DSM-5 draft criteria were shown to be less sensitive in regard to identification of subjects with ASDs, particularly those with Asperger's syndrome and some high-functioning subjects with autism.
CONCLUSIONS:

DSM-IV-TR helps with the definition of ASDs only up to a point. We suggest modifications to five details of DSM-5 draft criteria posted by the APA in February 2010. Completing revision of DSM criteria for ASDs is a challenging task.

Lower birth weight indicates higher risk of autistic traits in discordant twin pairs

7 Dec

Twin studies have shown that there is a strong genetic component to autism. When one “identical” twin has autism, the odds are high that the other twin does as well. But, what about those cases where only one twin has autism? The pair is “discordant”.

One of the major twin studies ongoing is the “Child and Adolescent Twin Study of Sweden” (CATSS). The study is not just an autism study, as their website notes:

The aim of this study is to investigate how both genetic and environmental effects influence health and behavior in children and adolescents. In this study parents to all Swedish twins turning 9 or 12 years are asked to complete a telephone interview concerning the health and behavior of their twins. The interview screens for several different health (e.g., asthma, allergies, diabetes) and behavior (e.g., attention, social interaction) problems. Some of the families will be followed up with additional questionnaires, as well as with genotyping and clinical interviews.

By studying discordant pairs, they are able to look for other risk factors. In this case, low birth weight. They found that low birth weight confers a significant risk for autism. Three times higher risk for a discordant autism pair for low birth weights.

They conclude ” a non-genetic influence associated with birth weight may contribute to the development of ASD”

Here is the abstract:

Lower birth weight indicates higher risk of autistic traits in discordant twin pairs.
Losh M, Esserman D, Anckarsäter H, Sullivan PF, Lichtenstein P.
Source

Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.
Abstract
BACKGROUND:

Autism spectrum disorder (ASD) is a neurodevelopmental disorder of complex etiology. Although strong evidence supports the causal role of genetic factors, environmental risk factors have also been implicated. This study used a co-twin-control design to investigate low birth weight as a risk factor for ASD.

Method
We studied a population-based sample of 3715 same-sex twin pairs participating in the Child and Adolescent Twin Study of Sweden (CATSS). ASD was assessed using a structured parent interview for screening of ASD and related developmental disorders, based on DSM-IV criteria. Birth weight was obtained from medical birth records maintained by the Swedish Medical Birth Registry.

RESULTS:

Twins lower in birth weight in ASD-discordant twin pairs (n=34) were more than three times more likely to meet criteria for ASD than heavier twins [odds ratio (OR) 3.25]. Analyses of birth weight as a continuous risk factor showed a 13% reduction in risk of ASD for every 100 g increase in birth weight (n=78). Analysis of the effect of birth weight on ASD symptoms in the entire population (most of whom did not have ASD) showed a modest association. That is, for every 100 g increase in birth weight, a 2% decrease in severity of ASD indexed by scores on the Autism – Tics, attention-deficit hyperactivity disorder (AD/HD), and other Comorbidities (A-TAC) inventory would be expected in the sample as a whole.

CONCLUSIONS:

The data were consistent with the hypothesis that low birth weight confers risk to ASD. Thus, although genetic effects are of major importance, a non-genetic influence associated with birth weight may contribute to the development of ASD.

The Prevalence of Autism Spectrum Disorders in Toddlers: A Population Study of 2-Year-Old Swedish Children.

6 Nov

A recent study, The Prevalence of Autism Spectrum Disorders in Toddlers: A Population Study of 2-Year-Old Swedish Children, considers changes in prevalence in very young children and the effect of early screening:

Autism Spectrum Disorder (ASD) is more common than previously believed. ASD is increasingly diagnosed at very young ages. We report estimated ASD prevalence rates from a population study of 2-year-old children conducted in 2010 in Gothenburg, Sweden. Screening for ASD had been introduced at all child health centers at child age 21/2 years. All children with suspected ASD were referred for evaluation to one center, serving the whole city of Gothenburg. The prevalence for all 2-year-olds referred in 2010 and diagnosed with ASD was 0.80%. Corresponding rates for 2-year-olds referred to the center in 2000 and 2005 (when no population screening occurred) were 0.18 and 0.04%. Results suggest that early screening contributes to a large increase in diagnosed ASD cases.

The prevalence for this young age group in Gothenburg Sweden showed a dramatic rise: from 0.04% in the year 2000, to 0.18% in 2005 and a big jump to 0.80% in 2010.

I’m sure many things have changed in Gothenburg in the past 10 years. However, the implementation of an early screening program is cited as having the major impact, as this was in place in 2010, but not for 2005 or 2000.

For those who will undoubtedly ask: the vaccine schedule for Sweden did not change remarkably in that time period.

2007: A revised schedule is implemented from 2007, including a diphtheria-tetanus-pertussis booster at school entry (DTaP) and at school leaving (dTap), and also a lower age for the second MMR (6-8 years). The new schedule starts with children born from 2002. Children born 1995-2001 receive a single dose pertussis catch-up in form of DTaP instead of DT at 10 years.

2009: PCV7 was introduced into the national childhood vaccination programme and recommended at 3, 5 and 12 months of age to all children born from October 2008 onwards.

2010: HPV introduced into the national childhood vaccination programme on 1st January 2010.

The 2007 change doesn’t affect children 2 1/2 and under. The 2009 addition of PCV7 doesn’t affect the children in 2005, where the prevalence was over 4 times higher than in 2000. HPV doesn’t affect children aged 2 1/2. Thimerosal was removed from vaccines in Sweden in the early 1990’s, so that exposure was unchanged over the entire period. My guess is this won’t stop people from pointing to the PCV7 vaccine as the “toxic tipping point” for Swedish kids.

Call me biased. I’m going with the authors on this one and giving credit to the hard work of the screening program implemented.

Autism Risk and low birth weight newborns

19 Oct

A recent article in the journal Pediatrics has gathered a lot of news coverage this week. Prevalence of Autism Spectrum Disorder in Adolescents Born Weighing<2000 Grams

Here is the abstract:

Objective: To estimate the diagnostic prevalence of autism spectrum disorders (ASDs) in a low birth weight (LBW) cohort.

Methods: Participants belonged to a regional birth cohort of infants (N = 1105) born weighing <2000 g between October 1, 1984, and July 3, 1989, and followed up by periodic assessments to 21 years of age. At 16 years (n = 623), adolescents were screened for ASD using a wide net (previous professional diagnosis of an ASD or a score above a liberal cutoff on the Social Communication Questionnaire or the Autism Spectrum Symptoms Questionnaire). At 21 years (n = 189), 60% of screen positives and 24% of screen negatives were assessed for diagnoses of ASD by the Autism Diagnostic Observation Schedule or the Autism Diagnostic Interview–Revised.

Results: Samples retained at ages 16 and 21 years were representative of samples assessed at earlier ages except for lower levels of social risk. Of positive screens, 11 of 70 had ASD; of negative screens, 3 of 119 had ASD. The fractions of the 2 screening groups with ASD (14.3% in screen-positives and 2.5% in screen negatives) were weighted by fractions of screen-positives and screen-negatives among the adolescents (18.8% and 81.2%, respectively). This calculation produced an estimated prevalence rate of ASD in the entire cohort of 5% (31 of 623).

Conclusions: The diagnostic prevalence of ASD in this LBW preterm cohort was higher than that reported by the Centers for Disease Control and Prevention for 8-year-olds in the general US population in 2006.

The idea that low birth wieght might increase risk of autism isn’t new, but this is a different design: following a low birthweight cohort into adulthood.

The paper, and definitely the media coverage, has some limitiations. A great discussion of this paper and the media coverage can be found at The Biology Files in an article by Emily Willingham: Autism and low birthweight: study–and quote–limitations It’s written much better than I could do, an whatever I’d write at this point would just be a distillation of it.

This is different from the risk of autism due to premature birth, something the media mixed up on occasion and that Emily Willingham discusses in her article.

There are certainly some concerns about how the 5% figure was derived, and one can’t really make a direct comparison between a closely watched cohort at adulthood to the prevalence of 8 year olds based on record review (as in the CDC prevalence estimates). However, the idea that low birth weight is a risk factor is worth investigation.

Sacramento County Schools “See” The Invisible Epidemic

5 Sep

At the end of this past week, California’s Sacramento Bee reports that “Autism rates quadruple in local schools over last decade“. The article, written by Phillip Reese, seems largely unremarkable. Even though headline is suggestive, there are no claims of “autism epidemic” that follow. In fact, Reese points out that:

Whether autism is actually more prevalent — as opposed to just more frequently diagnosed — is a matter of controversy.

From a scientific perspective, Reese definitely could have dug a lot deeper, but to a casual reader, the relevant facts seem pretty accurate, and a clear chart is provided.

The problem with an article like this, is that to a casual reader it may appear that there doesn’t seem to be any explanation in sight. “Autism is on the increase in Sacramento County Schools for the past decade”, and that’s that – “Why” is some sort of “controversy”, “some districts have more autistic students than others”, “here’s a chart”, and the article ends.

Did the Sacramento Bee miss an opportunity to carry their headline further, and expose an acutal “autism epidemic” in northern California schools?

Not surprisingly, Age Of Autism (always on the lookout for support of the notion that there’s been an autism “epidemic”) thought so. As it turns out, AoA resisted the urge to dig much deeper too. They were apparently satisfied to present a simple retort to the indication that whether or autism is actually more prevalent or more frequently diagnosed is “controversial”.

Seems the SacBee hasn’t read the study from their own state U that said, A study by researchers at the UC Davis M.I.N.D. Institute has found that the seven- to eight-fold increase in the number children born in California with autism since 1990 cannot be explained by either changes in how the condition is diagnosed or counted – and the trend shows no sign of abating.

Emphasis AoA’s.

If you think the emapahsized quote above sounds more like a press release than an acutal study, you’d be correct. Does the quoted press release overstate the actual conclusions of the study?

I’ll let readers be the judge of that, here’s the actual study’s conclusion:

Autism incidence in California shows no sign yet of plateauing. Younger ages at diagnosis, differential migration, changesin diagnostic criteria, and inclusion of milder cases do not fully explain the observed increases. Other artifacts have yet to be quantified, and as a result, the extent to which the continued rise represents a true increase in the occurrence of autism remains unclear.

Emphasis mine.

As foreshadowed for us in the conclusion of the actual study, what other artifacts might there be, that have “yet to be quantified”? Big ones like changes in awareness or diagnostic substitution?

Let’s quantify one of those potential artifacts (diagnostic substitution) for the Sacramento County Schools data, shall we?

Here’s the data (available online to the public):

To sum things up, I think Reese’s article/blurb would have been more interesting, only requiring a few extra minutes (the data is already there, presented on the same page when looking up the autism numbers), if it had included information about other changes like the “more than offsetting decrease” of Specific Learning Disabilities over the same time period.

Tell us what you think? Could newspapers do better when reporting on autism data, or do they simply present what their readers are really looking for?

Additional reading on this subject:

California’s Invisible Autism Epidemic (Jan 2009)

California’s Invisible Autism Epidemic Continues (Feb 2010)

California’s Specific Learning Disabilities Counter Epidemic (Feb 2011)

Prof. Paul Shattuck: ASD outcomes in adulthood

2 Sep

Below is a presentation given at the last IACC (Interagency Autism Coordinating Committee) meeting. Prof. Shattuck has done some excellent work in recent years. He’s one of the people looking into the areas I find critical and underserved. If you want to hear about research which can have a real impact on the life of this generation of autistic youth, you should set aside the time to listen to this talk.

Prof. Shattuck is looking at the critical transition from school to adulthood. How well are autistic students making that transition (largely, not so well as it turns out). What are the factors that help make that transition successful? If we don’t look into these questions today the problems will only continue unresolved.


Get Microsoft Silverlight

Prevalence and Correlates of Autism in a State Psychiatric Hospital

24 Aug

I’ve said it before: I really like David Mandell’s work. He and his team take on some very important and tough questions. I am very concerned about the lack of information on autistic adults. We don’t know an accurate prevalence. Without study ongoing into the needs of autistic adults, those of us with autistic children will face a

That’s why I like studies like this one: Prevalence and Correlates of Autism in a State Psychiatric Hospital.

This study estimated the ASD prevalence in a psychiatric hospital and evaluated the Social Responsiveness Scale (SRS) combined with other information for differential diagnosis. Chart review, SRS and clinical interviews were collected for 141 patients at one hospital. Diagnosis was determined at case conference. Receiver operating characteristic (ROC) curves were used to evaluate the SRS as a screening instrument. Chi-squared Automatic Interaction Detector (CHAID) analysis estimated the role of other variables, in combination with the SRS, in separating cases and non-cases. Ten percent of the sample had ASD. More than other patients, their onset was prior to 12 years of age, they had gait problems and intellectual disability, and were less likely to have a history of criminal involvement or substance abuse. Sensitivity (0.86) and specificity (0.60) of the SRS were maximized at a score of 84. Adding age of onset <12 years and cigarette use among those with SRS 80 increased specificity to 0.90 but dropped sensitivity to 0.79. Undiagnosed ASD may be common in psychiatric hospitals. The SRS, combined with other information, may discriminate well between ASD and other disorders.

For reference:

Sensitivity relates to the test’s ability to identify positive results.
Specificity relates to the ability of the test to identify negative results.

Identifying autistic adults is not easy. Prevalence studies are far more difficult than when working with students. But Prof. Mandell is out there, trying to find autistic adults. In this case, he found that in a given psychiatric hospital, about 10% of the patients were autistic. He is calibrating instruments (the SRS together with correlates like smoking, age-of-onset, ID) to provide for a fairly direct screening tool.

This is one type of work that needs to be done. I’m glad that Prof. Mandell’s group is out there doing it, but I hope that more groups pick this up in the future.

Epidemiology Night School Project

24 Aug

Here is an introductory post by EpiRen on his Epidemiology Night School Project:

I’m seriously thinking of writing a series of posts about epidemiology, making the most complex concepts as clear as I can. I would call this project “Epidemiology Night School.” I would offer no college credit for it, though. And I would not say that it would replace any class you can get in a formal, accredited pubic health program. But I will say that it might make it a little easier to understand the myriad of studies and health-related news that you see in the media. After the series of posts, I hope that you will be able to answer the following:

  • What is epidemiology?
  • What tables, graphs, and measures are used to describe disease trends? And what rules do you need to follow to present the data in the most honest and open way?
  • When do you use an “average”? When do you use a “median”? And how do you interpret these?
  • What is public health surveillance? And what are its limitations?
  • How do you investigate an outbreak?

I’ll be using a lot of my own experience in addressing these and other questions. If you need some text to follow along, I recommend CDC’s Principles of Epidemiology (PDF).
Of course, there are some prerequisites. You can’t just walk in off the street and understand epidemiology, though I will aim to do that. The main prerequisite will be an understanding of mathematics (adding, dividing, multiplying, and subtracting) and an open mind (because some stuff will blow your mind).
I plan on starting this project this coming weekend, maybe sooner than that or maybe later than that. We’ll see how it goes.

Epidemiology Night School: Introduction to Outbreaks (or “Don’t expect Dr. Jay to understand all this stuff”)

23 Aug

With EpiRen offline, I feel a bit of a void. In his blogging he was taking on an educational project: using current topics to discuss important topics in epidemiology. EpiWonk is also offline, but his body of work remains. EpiWonk also took on describing topics and terminology in epidemiology. Since I find these efforts valuable, I’ve decided to lift some of EpiRen’s “Epidemiology Night School” posts to preserve here. Below is one from March 25, 2011. I picked this somewhat at random, so don’t read too much into the selection.

From here on out, it is in EpiRen’s voice. As he is offline, don’t expect him to respond to comments directed at him.

If you’ve been reading me for a while, you know that I absolutely detest having to attack someone personally. Sure, I may point out the stupidity in some statements by people like Christina England, some homeopath here and there, and even Ms. Jennings was a subject of several postings. But I try not to inject my personal opinions about a person (much) because discussions of science should leave personal feelings out of it. (Sorry it was too late for you, Galileo.) Doing this avoids all that background noise. Know what I mean?

Still, there are those times when someone just somehow manages to get under my skin with comments so outrageous (in my opinion) that I am forced to think ill of them. (Not wish them ill, though. Even I am not that big of a bastard so as to wish others ill.) So I’m going to weave in some comments from the twitter feed of one Dr. Jay Gordon, just to show you how someone who doesn’t understand epidemiology can come off as crass and uncaring (in the opinion of many). All, of course, after the jump…

You see a monkey. I see flying Ebola.

MINNESOTA

Todd W. over at “Harpocrates Speaks” has a great series covering the development of the current outbreak of measles in Minnesota. Here are the facts as I am writing this:

  • 11 confirmed cases of measles as of 3/23/11
  • 4 of 11 too young to be vaccinated against measles
  • 5 of 11 of age to be vaccinated but are not
  • 2 of 11 with an unknown vaccine status
  • All are epidemiologically linked to one another. (We’ll cover what this means in a little bit.)
  • Minnesota had not seen these many cases since 1997, when they had 8 total cases throughout the year. Here is the table from their statistics web page:

  • Furthermore, 5 of the 11 cases have been hospitalized.
  • Finally, several of the cases are part of a community of Somali ex-patriots (or refugees) that has been targeted by Andrew Wakefied and his friends with anti-vaccine propaganda.

    • WHAT IS AN OUTBREAK?
    Traditionally, an outbreak has been defined as “one case over the expected rate (or number) of cases for a given location in a period of time.” In Minnesota, they have seen 22 cases over the last 14 years (22/14=1.6 cases per year in all Minnesota). Rounding up, we can say that two cases per year is what is expected. Three cases in 2011 would mean an outbreak. What was that in 2010, you ask? Well, 19 cases in 13 years give us a rate of 1.5 cases per year. It would also be an outbreak situation, especially if the three cases were epidemiologically linked. That information is not yet available from the MDH, but it will be interesting to read later on.

    YES. YES, IT'S AN OUTBREAK. IT'S A FRIGGIN' OUTBREAK!!!


    YES. YES, IT’S AN OUTBREAK. IT’S A FRIGGIN’ OUTBREAK!!!

    EPIDEMIOLOGICALLY LINKED?
    When two or more people develop a disease or condition, and they have similar exposures, they are said to be epidemiologically linked. For example, if two people ate at the same place in the hours before their onset of the same illness, then they are epidemiologically linked regardless of whether or not the food they shared is found to be the culprit. Some links are stronger than others, but this concept is not lost in outbreak investigations. During the outbreak of what is now known as Legionnaires’ Disease in Philadelphia in 1976, the fact that all those men were coming down with pneumonia raised some flags… The fact that they were all staying at the same hotel AND were all members of the American Legion was a cause for alarm. (It would be a while before the bacteria that caused the outbreak was discovered, but their epidemiological link proved to be an enormous clue.)

    BACK TO MINNESOTA

    So, eleven cases, all epidemiologically linked, is that an outbreak?

    You Lost Me at Porn

    YOU LOST ME AT PORN.

    I learned in grade school that 11 cases (to date) in the current outbreak is 9 cases over the expected 2. I also learned that it’s over 5 times the expected rate. I then learned in epidemiology school (a master’s level degree) that the fact that all these cases are somehow related to each other pretty much makes this an outbreak. Am I – or anyone working on that outbreak – being obsessive about “a few extra cases of measles”?

    If it means stopping a disease that can do this to a child, then YES, YES I AM OBSESSED.

    I want to emphasize the fact that they are all related to each other. If they had absolutely nothing to do with each other and were found in different corners of planet Earth, I wouldn’t obsess. But they’re all in one region of Minnesota. There’s nothing random about that, is there?

    You can lead the horse to the water, but…
    RANDOM, I DO NOT THINK YOU UNDERSTAND WHAT THAT WORD MEANS

    As I’ve stated before, there are clearly defined guidelines on what constitutes an outbreak and what doesn’t. If you look at the definition, there are factors of person, place, and time. How many people, where, and when? As I’m writing this, the answer is 11 people, in one region of Minnesota, in the last two to three weeks. That’s an outbreak, my friends. It’s a clean and clear situation.

    What the hell does Noro have to do with measles?
    REMEMBER YOUR TRAINING

    Pop quiz. What is the definition of incidence? Yep. You got it. It’s the number of new cases divided by the population at risk. Vaccine coverage for measles is estimated at 85% in Minnesota (maybe lower or higher, but certainly not enough for herd immunity now). That means that about 780,000 people in Minnesota are at risk for measles because they’re not considered immune. (Others who have been immunized, but whose immune system didn’t “take” the vaccine are too low in number to make an impact. The vaccine is really quite good, giving immunity to 99.7% of those who get their two doses and to 95% of those who get at least one dose.) That little quip about 15% norovirus? It’s a GUIDELINE on when to call an elevated number of cases of norovirus symptoms on a cruiseship an outbreak. (It appears that Dr. Gordon wants to go with one guideline but not another.)

    Not a dangerous epidemic? Would he say that to the mothers of those sick children?

    TELEVISION AND REALITY

    I don’t know about you folks, but I have never based an epidemiological decision or observation on a television show. I am yet to hear anything on television (or in any other media) and take it as gospel. What I have done is look at books about epidemiology that build upon a couple of centuries of knowledge and scientific experimentation. Maybe the Brady Bunch didn’t succumb to measles because – and I’m only taking a wild guess here – THEY WERE A FICTIONAL FAMILY! Moreover, they were a fictional family that caught measles in 1969 and then mumps in 1973. I would NEVER take my medical or epidemiological advice from such a careless bunch.


    The guy isn’t even wearing gloves!

    I’d never use them as an example for such a serious situation. Heck, if I used stuff on television to justify my thinking on epidemiological matters, I would be laughed out of a profession… I mean, imagine if I advocated to call in the US Army to wipe out a town because they had an outbreak of hemorrhagic fever? (“Outbreak“, 1995)

    RECAP

    Alright, so we learned that an outbreak is defined by person, place, and time. (If you remember one of the first lessons of the night school was descriptive epidemiology, and the example there was learning to recognize an outbreak.) There are certain situations where you have a group of people who are sick at the same time, but they were never in the same place. We call that a cluster in time.


    Not to be confused with a cluster OF time.

    There are other situations when a group of people who live in the same area get sick from the same pathogen (or condition) but at different times. We call that a cluster in space.


    We call this “Lost in Space”

    To be an outbreak, you need to establish associations between person, place, and time. Sure, the cluster in time may turn out to be an outbreak once you find out through questionnaires and interviews that they all bought the same brand of milk, albeit from different retailers. Or the cluster in space may turn out to be an outbreak once you notice that something has been leaking into the environment over a long period of time.

    So, when trying to determine if something is an outbreak, consider how many cases you’re looking at compared to previous years (or other periods of time), consider their geographic spread, consider common exposures of attributes (like gender, race, ethnicity, social status, grade in school, etc.), and consider them all human beings worthy of your caring and best honest effort to bring the outbreak under control and prevent it from ever happening again – like with vaccines and stuff.

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