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A striking figure from @meyerslab new modeling report. They plot IHME's projections for daily deaths in Italy and Spain in blue, with the real counts in black. Note the overconfidence of the projections, with a slower decline in deaths than predicted.
These figures were created using IHME's method. Importantly, the projections are unreliable even in populations where the peak in daily deaths has been clearly observed (Spain, Italy). Now think about trying to make projections in a place where the curve is still only rising.
Find a summary of the group's proposed alternative statistical model, with a link to the technical report.

cns.utexas.edu/news/new-model…
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Natalie E. Dean, PhD
@nataliexdean
I completely agree with @kj_seung (a great person to follow by the way). Pessimistic takes on the value of #TestTraceIsolate are easily interpreted as "don't bother." But there are so many reasons why it is a critical feature of our response. A thread. 1/11
First and foremost, conversations tend to focus only on tracking down contacts to break chains of transmission. This is too narrow a view of its value. What else does it achieve? Targeted education & testing, symptom monitoring, helping people isolate, gathering data. 2/11
The core of the strategy is hiring and training teams of community health workers, whose value goes beyond the detective work of tracing. Want people with confirmed infections to stay home? Make sure they have food and medicine. 3/11
Read 11 tweets
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Natalie E. Dean, PhD
@nataliexdean
THINK LIKE AN EPIDEMIOLOGIST: There are more new confirmed cases each day in the US than at any time during the earlier April peak. But is it really meaningful to compare those numbers? How do epidemiologists decide when to sound the alarm? A thread. 1/11
At the peak of NYC's epidemic, over 50% of tests came back positive. Compare that to Florida where positivity is still below 20%. 2/11
Sources: www1.nyc.gov/site/doh/covid…
wtsp.com/article/news/h…
We hear a lot about test positivity being an important metric to track, but I think it's helpful to remind ourselves why. When I think about testing, I tend to imagine dividing the population into tiers. The center is most likely to have COVID. The outer layers less so. 3/11
Read 11 tweets
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Natalie E. Dean, PhD
@nataliexdean
Japan is using big teams of public health nurses to perform "cluster busting" contact tracing. A thread summarizing their approach, as described in this translated (almost official) guidance document now on the web. 1/11
drive.google.com/file/d/1RxLGyR…
bloomberg.com/news/articles/…
The approach is based on their observation that many individuals do not infect others, but this is balanced by superspreading events. This is known as overdispersion in the number of secondary cases. R0 is an average and masks a lot of heterogeneity. 2/11
Japanese scientists were also the first to highlight the importance of close conversation in crowded, closed (indoor) environments for transmission. This is known as the 3Cs. Cluster occurrence risk is highest in these settings. 3/11
Read 11 tweets

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