While the COVID-19 pandemic underscores the centrality of good data to sound public policy making, the pandemic's more subtle lesson may be about the frequent elusiveness of truly meaningful data.
Indeed, the difficulty of determining both what to count and how to count it has been with us since the pandemic's earliest days. Initially this meant questions of how to measure cases of illness and model the course of disease spread. Subsequent discussions have focused on evaluating racial and ethnic groups’ differential disease burdens, assessing case positivity and fatality rates across space and time, and analyzing the evidence surrounding a range of public health interventions, medical treatments, and vaccines. Following the introduction of successful vaccines, even the question of what to count as a meaningful infection rests unsettled (Khullar 2021).
All of which is to say that Deborah Stone's important new book, Counting: How We Use Numbers to Decide...
