Pulled from the Infectious Economics archives, these articles provide recommendations for the design and development of robust mathematical models of COVID-19 epidemiology and economics to reduce uncertainty in decision-making and inform evidence-based public policy. Associations are easy; valid causal inference is hard If we want to be honest in evaluating the winners and losers in…
Incredible new research from Harvard and Kaiser contributed two substantial leaps forward this summer: first in the useful application of machine learning predictions using electronic health records and second in the accurate targeting of people who can benefit the most from HIV pre-exposure prophylaxis. This paper in Lancet HIV by Marcus and colleagues is so good…
Remember the good old days, when professors let you bring to an exam one 8.5″x11″ single-sided cheat sheet crammed with your tiniest scrawled notes about what you expected could be on the test? The landscape of immuno-oncology is changing so rapidly that in January I longed for a “cheat sheet” to keep up with the…
Data scientists younger than Taylor Swift can do everyone a favor by reading “Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hope, and Wastes Billions” by NPR journalist Richard Harris. It sparks uncomfortable conversations about the broken incentives in our research system. Read my full book review “Difficult Choices Between What is Best for…