articleThe LancetApr 8, 2022HYBRID OA

Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis

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Abstract

Background

) are essential for understanding the determinants of past infection, current transmission patterns, and a population's susceptibility to future infection with the same variant. Although several studies have estimated cumulative SARS-CoV-2 infections in select locations at specific points in time, all of these analyses have relied on biased data inputs that were not adequately corrected for. In this study, we aimed to provide a novel approach to estimating past SARS-CoV-2 daily infections, cumulative infections, and the proportion of the population infected, for 190 countries and territories from the start of the pandemic to Nov 14, 2021. This approach combines data from reported cases, reported deaths, excess deaths attributable to COVID-19, hospitalisations, and seroprevalence surveys to produce more robust estimates that minimise constituent biases.

Methods

by location and day based on assumptions of duration from infection to infectiousness and time an individual spent being infectious. For each of these quantities, we estimated a distribution based on an ensemble framework that captured uncertainty in data sources, model design, and parameter assumptions.

Citation impact

316
total citations
FWCI
42.64
Percentile
100%
References
71
Citations per year

Authors

72

Topics & keywords

Keywords
  • Coronavirus disease 2019 (COVID-19)
  • Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
  • 2019-20 coronavirus outbreak
  • Virology
  • Statistical analysis
  • Medicine
  • Geography
  • Biology
UN Sustainable Development Goals
  • Good health and well-being
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