Timely, accurate, and comprehensive estimates of SARS-CoV-2 daily infection rates, cumulative infections, the proportion of the population that has been infected at least once, and the effective reproductive number (Reffective) 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.

Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis / Barber, Ryan M; Sorensen, Reed J D; Pigott, David M; Bisignano, Catherine; Carter, Austin; Amlag, Joanne O; Collins, James K; Abbafati, Cristiana; Adolph, Christopher; Allorant, Adrien; Aravkin, Aleksandr Y; Bang-Jensen, Bree L; Castro, Emma; Chakrabarti, Suman; Cogen, Rebecca M; Combs, Emily; Comfort, Haley; Cooperrider, Kimberly; Dai, Xiaochen; Daoud, Farah; Deen, Amanda; Earl, Lucas; Erickson, Megan; Ewald, Samuel B; Ferrari, Alize J; Flaxman, Abraham D; Frostad, Joseph Jon; Fullman, Nancy; Giles, John R; Guo, Gaorui; He, Jiawei; Helak, Monika; Hulland, Erin N; Huntley, Bethany M; Lazzar-Atwood, Alice; Legrand, Kate E; Lim, Stephen S; Lindstrom, Akiaja; Linebarger, Emily; Lozano, Rafael; Magistro, Beatrice; Malta, Deborah Carvalho; Månsson, Johan; Mantilla Herrera, Ana M; Mokdad, Ali H; Monasta, Lorenzo; Naghavi, Mohsen; Nomura, Shuhei; Odell, Christopher M; Olana, Latera Tesfaye; Ostroff, Samuel M; Pasovic, Maja; Pease, Spencer A; Reiner Jr, Robert C; Reinke, Grace; Ribeiro, Antonio Luiz P; Santomauro, Damian F; Sholokhov, Aleksei; Spurlock, Emma E; Syailendrawati, Ruri; Topor-Madry, Roman; Vo, Anh Truc; Vos, Theo; Walcott, Rebecca; Walker, Ally; Wiens, Kirsten E; Wiysonge, Charles Shey; Worku, Nahom Alemseged; Zheng, Peng; Hay, Simon I; Gakidou, Emmanuela; Murray, Christopher J L. - In: THE LANCET. - ISSN 1474-547X. - 399:10344(2022), pp. 2351-2380. [10.1016/S0140-6736(22)00484-6]

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

Abbafati, Cristiana;
2022

Abstract

Timely, accurate, and comprehensive estimates of SARS-CoV-2 daily infection rates, cumulative infections, the proportion of the population that has been infected at least once, and the effective reproductive number (Reffective) 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.
2022
SARS_COVID_2; DALY; cumulative infections;
01 Pubblicazione su rivista::01a Articolo in rivista
Estimating global, regional, and national daily and cumulative infections with SARS-CoV-2 through Nov 14, 2021: a statistical analysis / Barber, Ryan M; Sorensen, Reed J D; Pigott, David M; Bisignano, Catherine; Carter, Austin; Amlag, Joanne O; Collins, James K; Abbafati, Cristiana; Adolph, Christopher; Allorant, Adrien; Aravkin, Aleksandr Y; Bang-Jensen, Bree L; Castro, Emma; Chakrabarti, Suman; Cogen, Rebecca M; Combs, Emily; Comfort, Haley; Cooperrider, Kimberly; Dai, Xiaochen; Daoud, Farah; Deen, Amanda; Earl, Lucas; Erickson, Megan; Ewald, Samuel B; Ferrari, Alize J; Flaxman, Abraham D; Frostad, Joseph Jon; Fullman, Nancy; Giles, John R; Guo, Gaorui; He, Jiawei; Helak, Monika; Hulland, Erin N; Huntley, Bethany M; Lazzar-Atwood, Alice; Legrand, Kate E; Lim, Stephen S; Lindstrom, Akiaja; Linebarger, Emily; Lozano, Rafael; Magistro, Beatrice; Malta, Deborah Carvalho; Månsson, Johan; Mantilla Herrera, Ana M; Mokdad, Ali H; Monasta, Lorenzo; Naghavi, Mohsen; Nomura, Shuhei; Odell, Christopher M; Olana, Latera Tesfaye; Ostroff, Samuel M; Pasovic, Maja; Pease, Spencer A; Reiner Jr, Robert C; Reinke, Grace; Ribeiro, Antonio Luiz P; Santomauro, Damian F; Sholokhov, Aleksei; Spurlock, Emma E; Syailendrawati, Ruri; Topor-Madry, Roman; Vo, Anh Truc; Vos, Theo; Walcott, Rebecca; Walker, Ally; Wiens, Kirsten E; Wiysonge, Charles Shey; Worku, Nahom Alemseged; Zheng, Peng; Hay, Simon I; Gakidou, Emmanuela; Murray, Christopher J L. - In: THE LANCET. - ISSN 1474-547X. - 399:10344(2022), pp. 2351-2380. [10.1016/S0140-6736(22)00484-6]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1652618
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