Thursday, September 3, 2020

Doing the Maths

Environmental & Science Education
Mathematics Education
Edward Hessler

The fallback position for President Trump with respect to Covid-19 testing "makes us look bad" and/or "When you test, you create cases." The math equation is a simple one: increase testing for COVID19 = increase cases of COVID19.

As Sharon Begley, reporting for STAT put it, "Basically, the president was arguing that the U.S. had just as many new cases in June and July as it did in May but, with fewer tests being done in May, they weren’t being detected; with more testing now, they are."

In that article Begley reports on a STAT analysis of testing date for all 50 states and the District of Columbia showed that President's claim is wrong. The spread of the COVID-19 virus explains the increase. The disease is more prevalent.

The report covers cases from mid-May to mid-July. There are seven exceptions about which Begley writes "Colorado, Indiana, Michigan, Missouri, North Carolina, Ohio meet the three criteria needed to support Trump's claim... The criteria are doing more tests in July than in May, finding more cases on a typical day in July than May, but seeing the number of cases per 1,000 tests decline or remain unchanged from May to June."

Begley describes these exceptions as "fascinating" and one of the many questions epidemiologists have ahead will be developing evidence-based reasons for the differences. This task will be complicated and there is not enough evidence currently to do that.

Begley continues, noting that on the other hand "New York tells the opposite story: more testing found fewer cases. The site nearly doubled its daily tests from May 13 (33,794) to July 12 (62,418). But its cases fell from 2,176 to 557. If the case rate had not dropped (by 86%), New York's expanded testing would have found 3,995 cases on July 12."

Begley's splendid article provides more details but most importantly and useful to most of us is that it includes a link to the STAT analysis (a summary chart). I include it here to ensure that you don't miss it although it is hardly buried in Ms. Begley's essay. The number of cases per 1000 is important because it is independent of the number of tests.

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