tetano
Editor, Senior Moderator
Epidemiology
. 2021 Apr 2.
doi: 10.1097/EDE.0000000000001361. Online ahead of print.
Estimating the cumulative incidence of SARS-CoV-2 infection and the infection fatality ratio in light of waning antibodies
Kayoko Shioda[SUP] 1 [/SUP], Max Sy Lau, Alicia Nm Kraay, Kristin N Nelson, Aaron J Siegler, Patrick S Sullivan, Matthew H Collins, Joshua S Weitz, Benjamin A Lopman
Affiliations
Abstract
Background: Serology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serologic assays (which is not necessarily equivalent to the duration of protective immunity). We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City and Connecticut.
Methods: We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March to October 2020 and population-level cross-sectional seroprevalence data from April to August 2020 in New York City and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection.
Results: The estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval: 1.0-1.2%) in New York City and 1.4% (1.1-1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2-29.7%) at the end of September in New York City and 8.8% (7.1-11.3%) in Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively.
Conclusions: The cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.
. 2021 Apr 2.
doi: 10.1097/EDE.0000000000001361. Online ahead of print.
Estimating the cumulative incidence of SARS-CoV-2 infection and the infection fatality ratio in light of waning antibodies
Kayoko Shioda[SUP] 1 [/SUP], Max Sy Lau, Alicia Nm Kraay, Kristin N Nelson, Aaron J Siegler, Patrick S Sullivan, Matthew H Collins, Joshua S Weitz, Benjamin A Lopman
Affiliations
- PMID: 33935138
- DOI: 10.1097/EDE.0000000000001361
Abstract
Background: Serology tests can identify previous infections and facilitate estimation of the number of total infections. However, immunoglobulins targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported to wane below the detectable level of serologic assays (which is not necessarily equivalent to the duration of protective immunity). We estimate the cumulative incidence of SARS-CoV-2 infection from serology studies, accounting for expected levels of antibody acquisition (seroconversion) and waning (seroreversion), and apply this framework using data from New York City and Connecticut.
Methods: We estimated time from seroconversion to seroreversion and infection fatality ratio (IFR) using mortality data from March to October 2020 and population-level cross-sectional seroprevalence data from April to August 2020 in New York City and Connecticut. We then estimated the daily seroprevalence and cumulative incidence of SARS-CoV-2 infection.
Results: The estimated average time from seroconversion to seroreversion was 3-4 months. The estimated IFR was 1.1% (95% credible interval: 1.0-1.2%) in New York City and 1.4% (1.1-1.7%) in Connecticut. The estimated daily seroprevalence declined after a peak in the spring. The estimated cumulative incidence reached 26.8% (24.2-29.7%) at the end of September in New York City and 8.8% (7.1-11.3%) in Connecticut, higher than maximum seroprevalence measures (22.1% and 6.1%), respectively.
Conclusions: The cumulative incidence of SARS-CoV-2 infection is underestimated using cross-sectional serology data without adjustment for waning antibodies. Our approach can help quantify the magnitude of underestimation and adjust estimates for waning antibodies.