Abstract
This study investigated the demographic heterogeneity of COVID-19 infection to reveal the role of age structure and gender on COVID-19 diffusion patterns, demonstrating that the infection is distributed unevenly across ages, genders, and outbreak times. Based on cluster analysis, we analysed the 4-month COVID-19 outbreak data (N = 3017) in Thailand from January 12 to May 12, 2020, covering the early to late outbreak period of the initial wave. Results revealed that there are 7 pertinent clusters of COVID-19 outbreaks. Infection risk was classified by age, sex, and confirmed infection period. Results showed that elderly and young male clusters were at risk of becoming infected at the very beginning of the wave. Working-age male, young female, and elderly male clusters were key clusters controlling transmission when spreading became pervasive. Relevant clusters addressed at the end of the wave included general public and younger age clusters. Unlike other regions, the infection risk in Thailand is interestingly stronger among younger age clusters and male populations. Even though elderly individuals are at risk of becoming infected earlier than other clusters, the infection proportion was low. The findings provide new insights into the risk for COVID-19 infection.
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