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.

本研究调查了 COVID-19 感染的人口统计学异质性，以揭示年龄结构和性别对 COVID-19 扩散模式的作用，表明感染在年龄、性别和爆发时间之间分布不均。基于聚类分析，我们分析了 2020 年 1 月 12 日至 5 月 12 日在泰国的 4 个月 COVID-19 爆发数据（N = 3017），涵盖了初始波的早期到晚期爆发期。结果显示，有 7 个相关的 COVID-19 爆发集群。感染风险按年龄、性别和确诊感染期进行分类。结果显示，老年和年轻男性群体在浪潮一开始就有被感染的风险。工作年龄男性，年轻女性，当传播变得普遍时，老年男性集群是控制传播的关键集群。浪潮结束时处理的相关集群包括公众和年轻群体。与其他地区不同，泰国的感染风险在年轻群体和男性人群中更为明显。尽管老年人比其他人群更早被感染，但感染比例很低。这些发现为了解 COVID-19 感染的风险提供了新的见解。