Derivation and Internal Validation of a Model to Predict the Probability of Severe Acute Respiratory Syndrome Coronavirus-2 Infection in Community People.

ABSTRACT:

Background

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 disease. There are concerns regarding limited testing capacity and the exclusion of cases from unproven screening criteria. Knowing COVID-19 risks can inform testing. This study derived and assessed a model to predict risk of SARS-CoV-2 in community-based people.

Methods

All people presenting to a community-based COVID-19 screening center answered questions regarding symptoms, possible exposure, travel, and occupation. These data were anonymously linked to SARS-CoV-2 testing results. Logistic regression was used to derive a model to predict SARS-CoV-2 infection. Bootstrap sampling evaluated the model.

Results

A total of 9172 consecutive people were studied. Overall infection ra

SUBMITTER: van Walraven C 

PROVIDER: S-EPMC7587546 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature