Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis
Abstract
) 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.
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
- FWCI
- 42.64
- Percentile
- 100%
- References
- 71
Authors
72Topics & 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
- Good health and well-being
Funding
- NSNational Science FoundationAward: 2031096
- BABill and Melinda Gates Foundation
- NYNew York State Department of Health
- QHQueensland Health
- SASouth African Medical Research Council
- MOMinistry of Education, Culture, Sports, Science and Technology
- CDCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorAward: 88887.507149/2020-00
- QGQueensland Government
- CNConselho Nacional de Desenvolvimento Científico e TecnológicoAwards: 465518/2014-1, 310679/2016-8
- FDFundação de Amparo à Pesquisa do Estado de Minas GeraisAwards: PPM-00428-17, RED-00081-16
- NHNational Health and Medical Research CouncilAward: APP1121516