Women in Healthcare Epidemiology

Dr. Janet Lane-Claypon

I'm not a big fan of National [fill-in-the-blank] Days—to me they imply we can ignore the topic on the 364 days that we aren’t supposed to celebrate it. So on National Women Physicians Day, we should vow to better recognize the huge contributions women physicians make every day. That way we might not even need a “day” in the future, and can thus focus instead on preparing for National Lima Bean Respect Day (April 20).

In the field of healthcare epidemiology and infection prevention, the list of women leaders is long--and for me to produce one would be very dangerous because I’m sure it’d be incomplete. Instead I’ll point out that the last two SHEA presidents were women, and the 2019 SHEA president will be our esteemed fellow blogger, Hilary Babcock (congrats again, Hilary!).

This also seems like a good day to point interested readers to this piece about Dr. Janet Lane-Claypon, a pioneering physician-epidemiologist who was the first to employ the now-ubiquitous cohort and case-control study designs we use so often in infection prevention. The paper was published in 2004 but I only recent stumbled on it, and found it a fascinating story about a person I clearly should have learned about during my epidemiology coursework (but didn’t!).

I recognize the irony of me posting this from a blog that has a 5:1 male:female ratio. We’ve tried over the years to recruit women to the blog, mostly unsuccessfully. One possible reason (besides the obvious—that we haven’t tried hard enough), is that women physicians put up with substantially more bullshit each day than their male counterparts, and thus have less time for blogging.

To our female readership: if you’re interested in contributing to the blog (either with periodic guest posts, or joining the group), please contact one of us. This isn’t limited to physicians: infection preventionists, non-physician epidemiologists, microbiologists, nurses…pretty much anybody with expertise and strong opinions about infection prevention and healthcare epidemiology!

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Move over London, here comes Flint

Epidemiologists are drawn to London for its role in the etiological tale or origins of their field. It's hard to discount the importance of John Snow's investigation of the Broad Street cholera outbreak of 1854 and its role in advancing public health. Even when looking at the simple case-control study, many are first taught about the methodology using Doll and Hill's famous 1947 study linking smoking and lung cancer, which was completed in London hospitals.

Digging even deeper, we see that the initial case-control study was thought to be Janet Lane-Claypon's report comparing 500 women with and 500 women without breast cancer admitted to London and Glasgow hospitals published in 1926. However, as in many historical investigations, claims of "firsts" in epidemiology are often overturned upon further review. And while London will always have a special place in epidemiologists' hearts, it turns out that another city needs to be recognized; a city we often ignore...

For those of you not familiar with US or automotive history, Flint Michigan is best known as the birthplace of General Motors and like many industrial midwest towns, it has fallen on hard times. Beside GM, it is also the birthplace of Sandra Bernhard, Bob Eubanks, Michael Moore, Grand Funk Railroad, Glen Rice and, apparently, the Case-Control Study.

In a paper published in the December issue of the American Journal of Epidemiology, Alfredo Morabia uncovered an old case-control study by George Ramsey buried in a 1925 issue of the American Journal of Hygiene. In July 1924, there were 41 cases of Scarlet Fever; a high rate in the summer. A dairy inspector soon learned of an employee at an ice cream plant who had continued to work even after he developed a sore throat and rash (presenteeism!!). However, an investigation of the case patients with scarlet fever did not identify a specific risk factor, including ingestion of ice cream from a single dairy. Then the investigation was "supplemented" by histories taken from 117 controls, who did not have scarlet fever. The questioning revealed very few differences between cases and controls except that cases with scarlet fever were much more like to frequently eat ice cream (60%) compared to controls without scarlet fever (24%). When the investigators looked specifically where cases bought their ice cream, they identified a specific factory as the culprit (see Figure below).  It turned out that Factory A was where the sick worker had worked! Further testing revealed hemolytic streptococcus in ice cream samples from Factory A.

The Discussion section of this recent paper points out that most of the advancements in epidemiological methods occurred in cancer and heart disease. Apparently, there was not another case-control study used in infectious disease epidemiology until 1940. What is amazing is that it appears the Dr. Ramsey and the Michigan Department of Health hit upon the case-control design all by themselves. The paper concludes: "Flint, Michigan, the cradle of General Motors and of recognized labor unions in the United States, appears to have also been a birthplace of case-control studies."  Merry Christmas Flint - hold your heads up high!

image source: missourireview.com

Influenza Vaccine Effectiveness Study Author Responds

Late last week, Dr. Jackson, one of the co-authors of the recent MMWR influenza vaccine effectiveness report, sent me an email response to my posts discussing how and why they measure influenza vaccine effectiveness the way they do. I thought that in the interest of fairness, I should post his full email, rather than pasting his response into a largely hidden comment section. I will likely post a follow-up to this at some point. Additionally, I want to thank Dr. Jackson publicly for responding in this fashion, both professionally and academically. The intent of my posts was academic, and I am pleased that he responded the way he did.

Dear Dr. Perencevich,

I am one of the co-authors on the MMWR article on influenza vaccine effectiveness, and I read your blog posts about that article. I believe I can clear up some of your questions. I tried posting this as a comment on the blog, but the website wouldn't let me, so my apologies for e-mailing you instead. Feel free to post this as comment on the website if you are able.

 (1) Regarding your first point, this study used what is known as a “test-negative” design. In the test-negative design, we enroll patients with a medically attended acute respiratory illness (MAARI). We then test these enrollees for influenza, and assess who was previously vaccinated and who was not. The test-negative design is based on an assumption that the rate of MAARI caused by pathogens other than influenza is the same in both vaccinated and unvaccinated persons. If this assumption is true, than our test-negative subjects are representative of the population from which the influenza-positive cases came, and our study does give an estimate of how well the vaccine reduces the risk of getting sick enough to visit the doctor.

 Although the paper refers to cases and controls, this is not a true case-control study, since a true case-control study requires that we know who is a case and who is not before we sample them. The design is closer to the “indirect cohort” method proposed by Claire Broome for studying pneumococcal vaccine effectiveness [NEJM 1980; 303:549-52]. The real advantage of the test-negative design is that it controls for differences in healthcare-seeking behavior. If we did the full cohort study you proposed, there would be variation among the cohort members in how often they seek healthcare, and these variations would be related both to their likelihood of being vaccinated and to their likelihood of going to the doctor if they got influenza. By only sampling people who come to the doctor, we control for those differences.

(2) Regarding your second point and third points, the relative risk (RR) is not an appropriate measure of association for this study design. The RR is (obviously) a measure of risk, which would be based on the cumulative incidence of disease in some defined cohort. In this study, we do not sample the full cohort; we simply use the influenza negative subjects to estimate the frequency of vaccination in the cohort. Using the RR in this setting would give a biased estimate of vaccine effectiveness, which is seen in the sample calculations you provided.

Sampling in a test-negative design is conceptually similar to incidence density sampling in a case-control study. When using incidence density sampling, the exposure odds ratio is a direct estimate of the incidence rate ratio and not an approximation to the RR. 

(3) Finally, regarding your final question about including the flu B cases in the estimate of VE against flu A: As mentioned above, the test-negative design assumes that the rate of non-flu MAARI is the same in vaccinated and unvaccinated persons. If we included flu B in the non-case group, we would be violating this assumption, because the vaccine does protect against B, and the rate of non-flu A MAARI would no longer be the same in vaccinated and unvaccinated persons.

 I hope this clears up your questions!
~Mike Jackson, Group Health Research Institute