Covid-19 Research and Resources
HRDAG is identifying and interpreting the best science we can find to shed light on the global crisis brought on by the novel coronavirus, about which we still know so little. Right now, most of the data on the virus SARS-CoV-2 and Covid-19, the condition caused by the virus, are incomplete and unrepresentative, which means that there is a great deal of uncertainty. But making sense of imperfect datasets is what we do. HRDAG is contributing to a better understanding with explainers, essays, and original research, and we are highlighting trustworthy resources for those who want to dig deeper.
Papers and articles by HRDAG
This Harvard Data Science Review article uses the least unreliable source of pandemic data: reported deaths.
Given a positive test result, what is the probability that an individual has antibodies? This HRDAG-authored Granta article explains the science.
Selected resources from the statistical and health community
A Guide for Understanding the Statistics about Covid-19
Why it’s so freaking hard to build a good Covid-19 model
StatsChat: Professor Thomas Lumley’s blog on statistical thinking
The World Health Organization Covid-19 Dashboard