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Spatial differentiation and determinants of COVID-19 in Indonesia

BACKGROUND: The spread of the coronavirus disease 2019 (COVID-19) has increasingly agonized daily lives worldwide. As an archipelagic country, Indonesia has various physical and social environments, which implies that each region has a different response to the pandemic. This study aims to analyze t...

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Autores principales: Widiawaty, Millary Agung, Lam, Kuok Choy, Dede, Moh, Asnawi, Nur Hakimah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125018/
https://www.ncbi.nlm.nih.gov/pubmed/35606710
http://dx.doi.org/10.1186/s12889-022-13316-4
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author Widiawaty, Millary Agung
Lam, Kuok Choy
Dede, Moh
Asnawi, Nur Hakimah
author_facet Widiawaty, Millary Agung
Lam, Kuok Choy
Dede, Moh
Asnawi, Nur Hakimah
author_sort Widiawaty, Millary Agung
collection PubMed
description BACKGROUND: The spread of the coronavirus disease 2019 (COVID-19) has increasingly agonized daily lives worldwide. As an archipelagic country, Indonesia has various physical and social environments, which implies that each region has a different response to the pandemic. This study aims to analyze the spatial differentiation of COVID-19 in Indonesia and its interactions with socioenvironmental factors. METHODS: The socioenvironmental factors include seven variables, namely, the internet development index, literacy index, average temperature, urban index, poverty rate, population density (PD) and commuter worker (CW) rate. The multiple linear regression (MLR) and geographically weighted regression (GWR) models are used to analyze the impact of the socioenvironmental factors on COVID-19 cases. COVID-19 data is obtained from the Indonesian Ministry of Health until November 30th 2020. RESULTS: Results show that the COVID-19 cases in Indonesia are concentrated in Java, which is a densely populated area with high urbanization and industrialization. The other provinces with numerous confirmed COVID-19 cases include South Sulawesi, Bali, and North Sumatra. This study shows that the socioenvironmental factors, simultaneously, influence the increasing of confirmed COVID-19 cases in the 34 provinces of Indonesia. Spatial interactions between the variables in the GWR model are relatively better than those between the variables in the MLR model. The highest spatial tendency is observed outside Java, such as in East Nusa Tenggara, West Nusa Tenggara, and Bali. CONCLUSION: Priority for mitigation and outbreak management should be high in areas with high PD, urbanized spaces, and CW.
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spelling pubmed-91250182022-05-23 Spatial differentiation and determinants of COVID-19 in Indonesia Widiawaty, Millary Agung Lam, Kuok Choy Dede, Moh Asnawi, Nur Hakimah BMC Public Health Research BACKGROUND: The spread of the coronavirus disease 2019 (COVID-19) has increasingly agonized daily lives worldwide. As an archipelagic country, Indonesia has various physical and social environments, which implies that each region has a different response to the pandemic. This study aims to analyze the spatial differentiation of COVID-19 in Indonesia and its interactions with socioenvironmental factors. METHODS: The socioenvironmental factors include seven variables, namely, the internet development index, literacy index, average temperature, urban index, poverty rate, population density (PD) and commuter worker (CW) rate. The multiple linear regression (MLR) and geographically weighted regression (GWR) models are used to analyze the impact of the socioenvironmental factors on COVID-19 cases. COVID-19 data is obtained from the Indonesian Ministry of Health until November 30th 2020. RESULTS: Results show that the COVID-19 cases in Indonesia are concentrated in Java, which is a densely populated area with high urbanization and industrialization. The other provinces with numerous confirmed COVID-19 cases include South Sulawesi, Bali, and North Sumatra. This study shows that the socioenvironmental factors, simultaneously, influence the increasing of confirmed COVID-19 cases in the 34 provinces of Indonesia. Spatial interactions between the variables in the GWR model are relatively better than those between the variables in the MLR model. The highest spatial tendency is observed outside Java, such as in East Nusa Tenggara, West Nusa Tenggara, and Bali. CONCLUSION: Priority for mitigation and outbreak management should be high in areas with high PD, urbanized spaces, and CW. BioMed Central 2022-05-23 /pmc/articles/PMC9125018/ /pubmed/35606710 http://dx.doi.org/10.1186/s12889-022-13316-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Widiawaty, Millary Agung
Lam, Kuok Choy
Dede, Moh
Asnawi, Nur Hakimah
Spatial differentiation and determinants of COVID-19 in Indonesia
title Spatial differentiation and determinants of COVID-19 in Indonesia
title_full Spatial differentiation and determinants of COVID-19 in Indonesia
title_fullStr Spatial differentiation and determinants of COVID-19 in Indonesia
title_full_unstemmed Spatial differentiation and determinants of COVID-19 in Indonesia
title_short Spatial differentiation and determinants of COVID-19 in Indonesia
title_sort spatial differentiation and determinants of covid-19 in indonesia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125018/
https://www.ncbi.nlm.nih.gov/pubmed/35606710
http://dx.doi.org/10.1186/s12889-022-13316-4
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