Abstract
Introduction: COVID-19 represents an unprecedented challenge to policy makers as well as those entrusted with capturing, monitoring, and analyzing COVID-19 data. Effective public policy is data-informed policy. This requires a liaison between public health scientists and public officials.
Objective: This article details the experience, challenges, and lessons learned advising public officials in a large metropolitan area from March to October 2020.
Methods: To effectively do this, an R Markdown report was created to iteratively monitor the number of COVID-19 tests performed, positive tests obtained, COVID-19 hospitalization census, intensive care unit census, the number of patients with COVID-19 on ventilators, and the number of deaths due to COVID-19.
Results: These reports were presented and discussed at meetings with policy makers to further comprehension.
Discussion: To facilitate the fullest understanding by both the general public and policy makers alike, we advocate for greater centralization of public health surveillance data, objective operational definitions of metrics, and greater interagency communication to best guide and inform policy makers. Through consistent data reporting methods, parsimonious and consistent analytic methods, a clear line of communication with policy makers, transparency, and the ability to navigate unforeseen externalities such as "data dumps" and reporting delays, scientists can use information to best support policy makers in times of crises.