Quantifying previous SARS-CoV-2 infection through mixture modelling of antibody levels.
Nat Commun
; 12(1): 6196, 2021 10 26.
Article
en En
| MEDLINE
| ID: mdl-34702829
ABSTRACT
As countries decide on vaccination strategies and how to ease movement restrictions, estimating the proportion of the population previously infected with SARS-CoV-2 is important for predicting the future burden of COVID-19. This proportion is usually estimated from serosurvey data in two steps:
first the proportion above a threshold antibody level is calculated, then the crude estimate is adjusted using external estimates of sensitivity and specificity. A drawback of this approach is that the PCR-confirmed cases used to estimate the sensitivity of the threshold may not be representative of cases in the wider population-e.g., they may be more recently infected and more severely symptomatic. Mixture modelling offers an alternative approach that does not require external data from PCR-confirmed cases. Here we illustrate the bias in the standard threshold-based approach by comparing both approaches using data from several Kenyan serosurveys. We show that the mixture model analysis produces estimates of previous infection that are often substantially higher than the standard threshold analysis.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
SARS-CoV-2
/
COVID-19
/
Anticuerpos Antivirales
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
País/Región como asunto:
Africa
Idioma:
En
Revista:
Nat Commun
Asunto de la revista:
BIOLOGIA
/
CIENCIA
Año:
2021
Tipo del documento:
Article