Mixed effects modelling of excess mortality and COVID-19 lockdowns in Thailand.

ABSTRACT: Accurate mortality data are critical for understanding the impact of COVID-19 and learning lessons from crisis responses. But published statistics risk misrepresenting deaths due to limited testing, underreporting, and lack of subnational data, especially in developing countries. Thailand experienced four COVID-19 waves between January 2020 and December 2021, and used a color-coded, province-level system for lockdowns. To account for deaths directly and indirectly caused by COVID-19, this paper uses mixed effects modelling to estimate counterfactual deaths for 2020-2021 and construct a monthly time series of provincial excess mortality. A fixed effects negative binomial and mixed effects Poisson model both substantiate other studies' estimates of excess deaths using subnational data for th

SUBMITTER: De Padua Durante AC 

PROVIDER: S-EPMC11001903 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature