Officials looking for COVID-19 statistics to help make public health decisions — such as when to open or close schools, businesses, and community facilities — have plenty data to choose from, including confirmed cases, deaths, hospitalizations, intensive care unit occupancy, emergency room visits, antibody tests, nasal-swab tests, the ratio of positive test results, and more. But interpreting those data can be challenging.
Adrian Raftery, professor of statistics and sociology, is lead author on a new guide published by the National Academies of Sciences, Engineering and Medicine, designed to help officials nationwide make sense of different COVID-19 data sources when making public health decisions.
“We intend for this guide to help these decision-makers and their advisors interpret the data on COVID-19 and understand the upsides and downsides of each data source,” says Raftery, who has worked extensively on statistical methods to measure and estimate the prevalence of other viruses, including HIV in Africa.
The guide is the inaugural project of the National Academies’ Societal Experts Action Network.
Read the complete UW News story about the new guide.