COVID-19 susceptibility and severity risks in a cross-sectional survey of over 500 000 US adults

BMJ Open. 2022 Oct 12;12(10):e049657. doi: 10.1136/bmjopen-2021-049657.

Abstract

Objectives: The enormous toll of the COVID-19 pandemic has heightened the urgency of collecting and analysing population-scale datasets in real time to monitor and better understand the evolving pandemic. The objectives of this study were to examine the relationship of risk factors to COVID-19 susceptibility and severity and to develop risk models to accurately predict COVID-19 outcomes using rapidly obtained self-reported data.

Design: A cross-sectional study.

Setting: AncestryDNA customers in the USA who consented to research.

Participants: The AncestryDNA COVID-19 Study collected self-reported survey data on symptoms, outcomes, risk factors and exposures for over 563 000 adult individuals in the USA in just under 4 months, including over 4700 COVID-19 cases as measured by a self-reported positive test.

Results: We replicated previously reported associations between several risk factors and COVID-19 susceptibility and severity outcomes, and additionally found that differences in known exposures accounted for many of the susceptibility associations. A notable exception was elevated susceptibility for men even after adjusting for known exposures and age (adjusted OR=1.36, 95% CI=1.19 to 1.55). We also demonstrated that self-reported data can be used to build accurate risk models to predict individualised COVID-19 susceptibility (area under the curve (AUC)=0.84) and severity outcomes including hospitalisation and critical illness (AUC=0.87 and 0.90, respectively). The risk models achieved robust discriminative performance across different age, sex and genetic ancestry groups within the study.

Conclusions: The results highlight the value of self-reported epidemiological data to rapidly provide public health insights into the evolving COVID-19 pandemic.

Keywords: COVID-19; Epidemiology; Public health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • COVID-19* / epidemiology
  • Cross-Sectional Studies
  • Humans
  • Male
  • Pandemics
  • Risk Factors
  • SARS-CoV-2