1. 6

This is the result of a simulation of a COVID-19 outbreak in the US Congress under a variety of experimental conditions:

https://www.dolthub.com/blog/2020-03-27-whos-at-risk-of-covid19-in-congress/#results

Black X’s represent losses of legislators of the illustrated house and party. The blog post goes into detail about the data and simulation used.

Data sources: US Congress demographics: https://www.dolthub.com/repositories/Liquidata/us-congress COVID19 mortality: https://www.dolthub.com/repositories/Liquidata/corona-virus

Tools used: Dolt (https://github.com/liquidata-inc/dolt) Perl Google Drawings

  1.  

  2. 4

    One big oversight in reaching the conclusion is that the mortality rates are based on the observed cases of contamination. This is likely to be a much smaller number than the actual contamination count since not the full population is tested, but only hospital patients or other people directly related to the health care system. This means a much lower actual risk of decease.

    1. 3

      CFR is hard to estimate. Assuming that there are many uncounted cases is just that: an assumption. There is by definition no evidence to support that claim. For places that have sampled entire populations (a few Italian towns, Iceland), they haven’t found evidence that the virus is substantially widespread in the population, or at least not in numbers that would be necessary to drive down CFR substantially. At this point in the epidemic curve, something like 85% of cases are less than 2 weeks old, which means that currently measured fatalities are probably an underestimate. Most people who will eventually die haven’t yet.

      1. 2

        Agreed. I do believe though that it’s important to at least mention this consideration when presenting a rather alarming visual as is done in this article.

    2. 2

      I’m getting a 404 on the first link.

      1. 1

        Thanks for the heads up, fixed

      2. 0

        Results in a sentence, please? Not just for me but for others who don’t have the time to sift through your well-detailed post :) Great job on it.

        1. 3

          Mortality outcomes for Congress are very sensitive to assumptions about spread and mortality. At the low end for each parameter, we can expect to lose 2 members of the house on average, and no senators. At the high end, we lose 6 senators and 20 house members. The age and sex distribution of the two parties means that on average the Republicans are slightly more at risk in the Senate, and the Democrats are dramatically more at risk in the House. In the worst case, these losses are:

          Senate republicans: 3 Senate democrats: 3 House republicans: 6 House democrats: 14

          1. 3

            They have a link to the results in the second sentence of the post..