Demographic and initial outbreak patterns of COVID-19 in Thailand.
Demographic and initial outbreak patterns of COVID-19 in Thailand.
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DOI：
10.1007/s12546-021-09276-y
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Wongboonsin P
中科院分区：
文献类型：
--
作者：
Jindahra P;Wongboonsin K;Wongboonsin P
本研究调查了 COVID-19 感染的人口异质性，以揭示年龄结构和性别对 COVID-19 传播模式的作用，证明感染在年龄、性别和爆发时间之间分布不均匀。基于聚类分析，我们分析了2020年1月12日至5月12日泰国4个月的COVID-19疫情数据（N = 3017），涵盖了第一波疫情的早期到晚期。结果显示，有 7 个相关的 COVID-19 疫情集群。感染风险按年龄、性别和确诊感染时期进行分类。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。当传播变得普遍时，工作年龄的男性、年轻女性和老年男性群体是控制传播的关键群体。该浪潮结束时解决的相关群体包括普通公众和较年轻的群体。有趣的是，与其他地区不同，泰国年轻群体和男性人群的感染风险更高。尽管老年人比其他群体更容易受到感染，但感染比例较低。这些发现为了解 COVID-19 感染风险提供了新的见解。
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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影响因子：
15.1
作者：
Liu, Yang;Gu, Zhonglei;Liu, Jiming
通讯作者：
Liu, Jiming
影响因子：
3.7
作者：
Dudel, Christian;Riffe, Tim;Myrskyla, Mikko
通讯作者：
Myrskyla, Mikko
DOI：
10.1073/pnas.2004911117
发表时间：
2020-05-05
影响因子：
11.1
作者：
Dowd, Jennifer Beam;Andriano, Liliana;Mills, Melinda C.
通讯作者：
Mills, Melinda C.
影响因子：
33.9
作者：
Czeisler, Mark E.;Tynan, Michael A.;Czeisler, Charles A.
通讯作者：
Czeisler, Charles A.
DOI：
10.15585/mmwr.mm6939e1
发表时间：
2020-10-02
期刊：
MMWR. Morbidity and mortality weekly report
影响因子：
--
作者：
Boehmer TK;DeVies J;Caruso E;van Santen KL;Tang S;Black CL;Hartnett KP;Kite-Powell A;Dietz S;Lozier M;Gundlapalli AV
通讯作者：
Gundlapalli AV