May 28, 2021

Evaluating Data Types: A Guide for Decision Makers Using Data to Understand the Extent and Spread of COVID-19

Category: Article Summary

Topic: Public Health Policy and Practice

Keywords (Tags): public health

• A rapid consultation produced by a panel of experts from the National Academies of Sciences, Engineering and Medicine identified 7 data types used as indicators for evaluating local course of COVID-19 and 5 criteria to assess the reliability and validity of each data type. The 7 data types include confirmed cases, hospitalizations, emergency department visits, confirmed COVID-19 deaths, excess deaths, positive test fraction, and prevalence surveys. The 5 criteria include representativeness, bias, sampling error, lag time, and spatial differences in measurement. The authors encourage policy makers to consider small case counts, systematic over- and under-estimation, disproportionate impact against certain populations, importance of qualitative data, and transparency while analyzing the different data types.

National Academies Press. (May 28, 2021). Evaluating Data Types: A Guide for Decision Makers Using Data to Understand the Extent and Spread of COVID-19. National Academies Press. https://doi.org/10.17226/25826