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Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia

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...

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Autores principales: Zhu, Mingjian, Kleepbua, Jirapat, Guan, Zhou, Chew, Sien Ping, Tan, Joanna Weihui, Shen, Jian, Latthitham, Natthjija, Hu, Jianxiong, Law, Jia Xian, Li, Lanjuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466219/
https://www.ncbi.nlm.nih.gov/pubmed/34574997
http://dx.doi.org/10.3390/healthcare9091220
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author Zhu, Mingjian
Kleepbua, Jirapat
Guan, Zhou
Chew, Sien Ping
Tan, Joanna Weihui
Shen, Jian
Latthitham, Natthjija
Hu, Jianxiong
Law, Jia Xian
Li, Lanjuan
author_facet Zhu, Mingjian
Kleepbua, Jirapat
Guan, Zhou
Chew, Sien Ping
Tan, Joanna Weihui
Shen, Jian
Latthitham, Natthjija
Hu, Jianxiong
Law, Jia Xian
Li, Lanjuan
author_sort Zhu, Mingjian
collection PubMed
description 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 (R(0)) 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 = 0.30e(0.13x) (p < 0.01, R(2) = 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.
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spelling pubmed-84662192021-09-27 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 Weihui Shen, Jian Latthitham, Natthjija Hu, Jianxiong Law, Jia Xian Li, Lanjuan Healthcare (Basel) Article 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 (R(0)) 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 = 0.30e(0.13x) (p < 0.01, R(2) = 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. MDPI 2021-09-16 /pmc/articles/PMC8466219/ /pubmed/34574997 http://dx.doi.org/10.3390/healthcare9091220 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhu, Mingjian
Kleepbua, Jirapat
Guan, Zhou
Chew, Sien Ping
Tan, Joanna Weihui
Shen, Jian
Latthitham, Natthjija
Hu, Jianxiong
Law, Jia Xian
Li, Lanjuan
Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia
title Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia
title_full Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia
title_fullStr Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia
title_full_unstemmed Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia
title_short Early Spatiotemporal Patterns and Population Characteristics of the COVID-19 Pandemic in Southeast Asia
title_sort early spatiotemporal patterns and population characteristics of the covid-19 pandemic in southeast asia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8466219/
https://www.ncbi.nlm.nih.gov/pubmed/34574997
http://dx.doi.org/10.3390/healthcare9091220
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