Early spatiotemporal patterns and population characteristics of the covid-19 pandemic in southeast asia
Zhu, Mingjian Kleepbua, Jirapat Guan, Zhou Chew, Sien Ping Tan, Joanna Wei hui Shen, Jian Latthitham, Natthjija Hu, Jianxiong Law, Jia Xian Li, Lanjuan
Zhu, Mingjian
Kleepbua, Jirapat
Guan, Zhou
Chew, Sien Ping
Tan, Joanna Wei hui
Shen, Jian
Latthitham, Natthjija
Hu, Jianxiong
Law, Jia Xian
Li, Lanjuan
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Alternative Title
Abstract
This observational study aims to investigate the early disease patterns of coronavirus disease 2019 (COVID-19) in Southeast Asia, consequently providing historical experience for further interventions. Data were extracted from official websites of the WHO and health authorities of relevant countries. A total of 1346 confirmed cases of COVID-19, with 217 recoveries and 18 deaths, were reported in Southeast Asia as of 16 March 2020. The basic reproductive number (R0 ) of COVID-19 in the region was estimated as 2.51 (95% CI:2.31 to 2.73), and there were significant geographical variations at the subregional level. Early transmission dynamics were examined with an exponential regression model: y = 0.30e0.13x (p < 0.01, R2 = 0.96), which could help predict short-term incidence. Country-level disease burden was positively correlated with Human Development Index (r = 0.86, p < 0.01). A potential early shift in spatial diffusion patterns and a spatiotemporal cluster occurring in Malaysia and Singapore were detected. Demographic analyses of 925 confirmed cases indicated a median age of 44 years and a sex ratio (male/female) of 1.25. Age may play a significant role in both susceptibilities and outcomes. The COVID-19 situation in Southeast Asia is challenging and unevenly geographically distributed. Hence, enhanced real-time surveillance and more efficient resource allocation are urgently needed. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Keywords
Basic reproduction number (R0), COVID-19, Demographic risk factor, Epidemic pattern, Exponential growth, Observational study, Public health, Southeast Asia (SEA), Spatio-temporal analysis
Source Title
Healthcare (Switzerland)
Publisher
MDPI
Series/Report No.
Collections
Rights
Attribution 4.0 International
Date
2021-09-16
DOI
10.3390/healthcare9091220
Type
Article