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Generalizability of anti-SARS-CoV-2 seroprevalence estimates to the Montréal pediatric population: a comparison between two weighting methods.
Saucier, Adrien; Nasri, Bouchra; McKinnon, Britt; Carabali, Mabel; Pierce, Laura; Charland, Katia; Zinszer, Kate.
Afiliação
  • Saucier A; Université de Montréal, Centre de recherche en santé publique, Montréal.
  • Nasri B; Université de Montréal, Centre de recherche en santé publique, Montréal.
  • McKinnon B; Université de Montréal, Centre de recherche en santé publique, Montréal.
  • Carabali M; Université de Montréal, Centre de recherche en santé publique, Montréal.
  • Pierce L; Université de Montréal, Centre de recherche en santé publique, Montréal.
  • Charland K; Université de Montréal, Centre de recherche en santé publique, Montréal.
  • Zinszer K; Université de Montréal, Centre de recherche en santé publique, Montréal.
Am J Epidemiol ; 2024 Aug 12.
Article em En | MEDLINE | ID: mdl-39136208
ABSTRACT
Seroprevalence studies on SARS-CoV-2 infections have been often based on study populations with non-random and non-representative samples, limiting the generalizability of their results. In this study, we investigated the representativity and the generalizability of the baseline (collected from October 16th, 2020, to April 18th, 2021) estimate of a pediatric seroprevalence study based in Montréal. We compared the change in the estimates of seroprevalence for two different weighting

methods:

marginal standardization and raking. The target population was the general pediatric population of Montréal and was based on 2016 Canadian census data. Study results show variation across the multiple weighting scenarios although both weighting methods performed similarly, each possessing its own strengths and weaknesses. However, we prefer raking due to its capacity to simultaneously weight for multiple underrepresented study population characteristics.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article