Using informatics to guide public health policy during the COVID-19 pandemic in the USA

Abstract

Background: Current and future pandemics will require informatics solutions to assess the risks, resources and policies to guide better public health decision-making. Methods: Cross-sectional study of all COVID-19 cases and deaths in the USA on a population- and resource-adjusted basis (as of 24 April 2020) by applying biomedical informatics and data visualization tools to several public and federal government datasets, including analysis of the impact of statewide stay-at-home orders. Results: There were 2753.2 cases and 158.0 deaths per million residents, respectively, in the USA with variable distributions throughout divisions, regions and states. Forty-two states and Washington, DC, (84.3%) had statewide stay-at-home orders, with the remaining states having population-adjusted characteristics in the highest risk quartile. Conclusions: Effective national preparedness requires clearly understanding states' ability to predict, manage and balance public health needs through all stages of a pandemic. This will require leveraging data quickly, correctly and responsibly into sound public health policies.