Abstract

Background Health disparities have emerged with the COVID-19 epidemic because the risk of exposure to infection and the prevalence of risk factors for severe outcomes given infection vary within and between populations. However, estimated epidemic quantities such as rates of severe illness and death, the case fatality rate (CFR), and infection fatality rate (IFR), are often expressed in terms of aggregated population-level estimates due to the lack of epidemiological data at the refined subpopulation level. For public health policy makers to better address the pandemic, stratified estimates are necessary to investigate the potential outcomes of policy scenarios targeting specific subpopulations. Methods We develop a framework for using available data on the prevalence of COVID-19 risk factors (age, comorbidities, BMI, smoking status) in subpopulations, and epidemic dynamics at the population level and stratified …

Date

2020

Authors

David V. Conti Abigail L. Horn, Lai Jiang, Faith Washburn, Emil Hvitfeldt, Kayla de la Haye, William Nicholas, Paul Simon, Maryann Pentz, Wendy Cozen, Neeraj Sood

Source

medRxiv

Report_number

COVID-19 SARS-CoV-2 preprints

Publisher

medRxiv