Excess mortality and COVID-19 lockdowns: Results from mixed-effects modelling for Thailand

Abstract

Accurate mortality data are critical for understanding the impact of COVID-19 and learning lessons from crisis responses. But official statistics risk undercounting deaths due to limited testing and underreporting, especially in developing countries. Thailand has experienced four COVID-19 waves 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 from January 2020 to December 2021 and construct a monthly time series of provincial excess mortality. The model reveals that excess mortality was much higher than official figures, with the largest undercounting for males and the elderly. Then, recently developed panel regression methods are used to characterize the correlations among restrictions, mobility, and excess mortality. The findings suggest that lockdowns stemmed excess mortality with a three-month lag.