How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19.

ABSTRACT: In response to the coronavirus disease (COVID-19) pandemic, public health scientists have produced a large and rapidly expanding body of literature that aims to answer critical questions, such as the proportion of the population in a geographic area that has been infected; the transmissibility of the virus and factors associated with high infectiousness or susceptibility to infection; which groups are the most at risk of infection, morbidity and mortality; and the degree to which antibodies confer protection to re-infection. Observational studies are subject to a number of different biases, including confounding, selection bias, and measurement error, that may threaten their validity or influence the interpretation of their results. To assist in the critical evaluation of a vast body of li

SUBMITTER: Accorsi EK 

PROVIDER: S-EPMC7906244 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature