An Economist's Guide to Epidemiology Models of Infectious Disease
Bossert et al provide some useful information on the structure and use of epidemiology models of disease transmission, with an emphasis on the susceptible/infected/recovered (SIR) model. And they discuss high-profile forecasts of cases and deaths that have been based on these models, what went wrong with the early forecasts, and how they have adapted to the current COVID pandemic.
Understanding the process by which these models’ predictions and insights can be accessed by policymakers has also gained importance. The normal process of writing, vetting, and publishing scientific and economic research is being stretched to its limits given the urgency of the pandemic. Direct and wide dissemination can work for certain types of knowledge: detailed predictions from empirical models lend themselves to the now ubiquitous COVID “dashboards” that make those predictions available to policy-makers and others with just a click or two. There is no reason to believe that the models which have the best designed websites and interfaces are the ones producing the most careful and accurate predictions, though. Conveying more subtle insights, such as how government policies might interact with endogenous social distancing, seems substantially more difficult but no less important. One would hope that robust lines of communication and established respectful relationships between experts and policy-makers could facilitate such dialogues.
