Improving the representativeness of UK's national COVID-19 Infection Survey through spatio-temporal regression and post-stratification.

ABSTRACT: Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we used spatio-temporal regression and post-stratification models to UK's national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody

SUBMITTER: Pouwels KB 

PROVIDER: S-EPMC11196632 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature