Please use this identifier to cite or link to this item:
https://doi.org/10.3390/healthcare9091220
DC Field | Value | |
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dc.title | Early spatiotemporal patterns and population characteristics of the covid-19 pandemic in southeast asia | |
dc.contributor.author | Zhu, Mingjian | |
dc.contributor.author | Kleepbua, Jirapat | |
dc.contributor.author | Guan, Zhou | |
dc.contributor.author | Chew, Sien Ping | |
dc.contributor.author | Tan, Joanna Wei hui | |
dc.contributor.author | Shen, Jian | |
dc.contributor.author | Latthitham, Natthjija | |
dc.contributor.author | Hu, Jianxiong | |
dc.contributor.author | Law, Jia Xian | |
dc.contributor.author | Li, Lanjuan | |
dc.date.accessioned | 2022-10-12T10:04:13Z | |
dc.date.available | 2022-10-12T10:04:13Z | |
dc.date.issued | 2021-09-16 | |
dc.identifier.citation | Zhu, Mingjian, Kleepbua, Jirapat, Guan, Zhou, Chew, Sien Ping, Tan, Joanna Wei hui, Shen, Jian, Latthitham, Natthjija, Hu, Jianxiong, Law, Jia Xian, Li, Lanjuan (2021-09-16). Early spatiotemporal patterns and population characteristics of the covid-19 pandemic in southeast asia. Healthcare (Switzerland) 9 (9) : 1220. ScholarBank@NUS Repository. https://doi.org/10.3390/healthcare9091220 | |
dc.identifier.issn | 2227-9032 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/232640 | |
dc.description.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. | |
dc.publisher | MDPI | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Scopus OA2021 | |
dc.subject | Basic reproduction number (R0) | |
dc.subject | COVID-19 | |
dc.subject | Demographic risk factor | |
dc.subject | Epidemic pattern | |
dc.subject | Exponential growth | |
dc.subject | Observational study | |
dc.subject | Public health | |
dc.subject | Southeast Asia (SEA) | |
dc.subject | Spatio-temporal analysis | |
dc.type | Article | |
dc.contributor.department | SOCIOLOGY | |
dc.description.doi | 10.3390/healthcare9091220 | |
dc.description.sourcetitle | Healthcare (Switzerland) | |
dc.description.volume | 9 | |
dc.description.issue | 9 | |
dc.description.page | 1220 | |
Appears in Collections: | Students Publications |
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