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A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak

BACKGROUND: Since the first cases reported in Wuhan, China, in December 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread worldwide. In Indonesia, the first case was reported in early March 2020, and the numbers of confirmed infections have been increasing until now....

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Autores principales: Aisyah, Dewi Nur, Mayadewi, Chyntia Aryanti, Diva, Haniena, Kozlakidis, Zisis, Siswanto, Adisasmito, Wiku
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755207/
https://www.ncbi.nlm.nih.gov/pubmed/33351801
http://dx.doi.org/10.1371/journal.pone.0243703
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author Aisyah, Dewi Nur
Mayadewi, Chyntia Aryanti
Diva, Haniena
Kozlakidis, Zisis
Siswanto,
Adisasmito, Wiku
author_facet Aisyah, Dewi Nur
Mayadewi, Chyntia Aryanti
Diva, Haniena
Kozlakidis, Zisis
Siswanto,
Adisasmito, Wiku
author_sort Aisyah, Dewi Nur
collection PubMed
description BACKGROUND: Since the first cases reported in Wuhan, China, in December 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread worldwide. In Indonesia, the first case was reported in early March 2020, and the numbers of confirmed infections have been increasing until now. Efforts to contain the virus globally and in Indonesia are ongoing. This is the very first manuscript using a spatial-temporal model to describe the SARS-CoV-2 transmission in Indonesia, as well as providing a patient profile for all confirmed COVID-19 cases. METHOD: Data was collected from the official website of the Indonesia National Task Force for the Acceleration of COVID-19, from the period of 02 March 2020–02 August 2020. The data from RT-PCR confirmed, SARS-CoV-2 positive patients was categorized according to demographics, symptoms and comorbidities based on case categorization (confirmed, recovered, dead). The data collected provides granular and thorough information on time and geographical location for all 34 Provinces across Indonesia. RESULTS: A cumulative total of 111,450 confirmed cases of were reported in Indonesia during the study period. Of those confirmed cases 67.79% (75,551/111,450) were shown as recovered and 4.83% (5,382/111,450) of them as died. Patients were mostly male (50.52%; 56,300/111,450) and adults aged 31 to 45 years old (29.73%; 33,132/111,450). Overall patient presentation symptoms of cough and fever, as well as chronic disease comorbidities were in line with previously published data from elsewhere in South-East Asia. The data reported here, shows that from the detection of the first confirmed case and within a short time period of 40 days, all the provinces of Indonesia were affected by COVID-19. CONCLUSIONS: This study is the first to provide detailed characteristics of the confirmed SARS-CoV-2 patients in Indonesia, including their demographic profile and COVID-19 presentation history. It used a spatial-temporal analysis to present the epidemic spread from the very beginning of the outbreak throughout all provinces in the country. The increase of new confirmed cases has been consistent during this time period for all provinces, with some demonstrating a sharp increase, in part due to the surge in national diagnostic capacity. This information delivers a ready resource that can be used for prediction modelling, and is utilized continuously by the current Indonesian Task Force in order to advise on potential implementation or removal of public distancing measures, and on potential availability of healthcare capacity in their efforts to ultimately manage the outbreak.
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spelling pubmed-77552072021-01-05 A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak Aisyah, Dewi Nur Mayadewi, Chyntia Aryanti Diva, Haniena Kozlakidis, Zisis Siswanto, Adisasmito, Wiku PLoS One Research Article BACKGROUND: Since the first cases reported in Wuhan, China, in December 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread worldwide. In Indonesia, the first case was reported in early March 2020, and the numbers of confirmed infections have been increasing until now. Efforts to contain the virus globally and in Indonesia are ongoing. This is the very first manuscript using a spatial-temporal model to describe the SARS-CoV-2 transmission in Indonesia, as well as providing a patient profile for all confirmed COVID-19 cases. METHOD: Data was collected from the official website of the Indonesia National Task Force for the Acceleration of COVID-19, from the period of 02 March 2020–02 August 2020. The data from RT-PCR confirmed, SARS-CoV-2 positive patients was categorized according to demographics, symptoms and comorbidities based on case categorization (confirmed, recovered, dead). The data collected provides granular and thorough information on time and geographical location for all 34 Provinces across Indonesia. RESULTS: A cumulative total of 111,450 confirmed cases of were reported in Indonesia during the study period. Of those confirmed cases 67.79% (75,551/111,450) were shown as recovered and 4.83% (5,382/111,450) of them as died. Patients were mostly male (50.52%; 56,300/111,450) and adults aged 31 to 45 years old (29.73%; 33,132/111,450). Overall patient presentation symptoms of cough and fever, as well as chronic disease comorbidities were in line with previously published data from elsewhere in South-East Asia. The data reported here, shows that from the detection of the first confirmed case and within a short time period of 40 days, all the provinces of Indonesia were affected by COVID-19. CONCLUSIONS: This study is the first to provide detailed characteristics of the confirmed SARS-CoV-2 patients in Indonesia, including their demographic profile and COVID-19 presentation history. It used a spatial-temporal analysis to present the epidemic spread from the very beginning of the outbreak throughout all provinces in the country. The increase of new confirmed cases has been consistent during this time period for all provinces, with some demonstrating a sharp increase, in part due to the surge in national diagnostic capacity. This information delivers a ready resource that can be used for prediction modelling, and is utilized continuously by the current Indonesian Task Force in order to advise on potential implementation or removal of public distancing measures, and on potential availability of healthcare capacity in their efforts to ultimately manage the outbreak. Public Library of Science 2020-12-22 /pmc/articles/PMC7755207/ /pubmed/33351801 http://dx.doi.org/10.1371/journal.pone.0243703 Text en © 2020 Aisyah et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Aisyah, Dewi Nur
Mayadewi, Chyntia Aryanti
Diva, Haniena
Kozlakidis, Zisis
Siswanto,
Adisasmito, Wiku
A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak
title A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak
title_full A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak
title_fullStr A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak
title_full_unstemmed A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak
title_short A spatial-temporal description of the SARS-CoV-2 infections in Indonesia during the first six months of outbreak
title_sort spatial-temporal description of the sars-cov-2 infections in indonesia during the first six months of outbreak
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755207/
https://www.ncbi.nlm.nih.gov/pubmed/33351801
http://dx.doi.org/10.1371/journal.pone.0243703
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