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Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia
Epidemiological surveillance is an essential component of public health practice especially during infectious disease outbreaks. It is critical to offer transparent epidemiological information in a rigorous manner at different regional levels in countries for managing the outbreak situations. The ob...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872239/ https://www.ncbi.nlm.nih.gov/pubmed/35206818 http://dx.doi.org/10.3390/healthcare10020204 |
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author | Barsasella, Diana Iman, Arief Tarmansyah Fadly, Fery Uddin, Mohy Mohammed, Arshad Shaik, Tazeem Saputra, Hermawan Malwade, Shwetambara Dhar, Eshita Zakiah, Nurhadi, Jonnagaddala, Jitendra Syed-Abdul, Shabbir |
author_facet | Barsasella, Diana Iman, Arief Tarmansyah Fadly, Fery Uddin, Mohy Mohammed, Arshad Shaik, Tazeem Saputra, Hermawan Malwade, Shwetambara Dhar, Eshita Zakiah, Nurhadi, Jonnagaddala, Jitendra Syed-Abdul, Shabbir |
author_sort | Barsasella, Diana |
collection | PubMed |
description | Epidemiological surveillance is an essential component of public health practice especially during infectious disease outbreaks. It is critical to offer transparent epidemiological information in a rigorous manner at different regional levels in countries for managing the outbreak situations. The objectives of this research are to better understand the information flow of COVID-19 health monitoring systems and to determine the data gaps of COVID-19 incidence at the national and provincial levels in Indonesia. COVID-19 information flow was researched using government websites at the national and various provincial levels. To find the disparities, we assessed the number of cases reported at both levels at the same time and displayed the absolute and relative differences. The findings revealed that out of a total of 34 provinces in Indonesia, data differences were seen in 25 (73.52%) provinces in terms of positive cases, 31 (91.18%) provinces in terms of cured cases, and 28 (82.35%) provinces of the number of deaths. Our results showed a pressing need for high-quality, transparent, and timely information. The integration of COVID-19 data in Indonesia has not been optimal, implying that the reported COVID-19 incidence rate may be biased or delayed. COVID-19 incidents must be better monitored to disrupt the disease’s transmission chain. |
format | Online Article Text |
id | pubmed-8872239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88722392022-02-25 Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia Barsasella, Diana Iman, Arief Tarmansyah Fadly, Fery Uddin, Mohy Mohammed, Arshad Shaik, Tazeem Saputra, Hermawan Malwade, Shwetambara Dhar, Eshita Zakiah, Nurhadi, Jonnagaddala, Jitendra Syed-Abdul, Shabbir Healthcare (Basel) Article Epidemiological surveillance is an essential component of public health practice especially during infectious disease outbreaks. It is critical to offer transparent epidemiological information in a rigorous manner at different regional levels in countries for managing the outbreak situations. The objectives of this research are to better understand the information flow of COVID-19 health monitoring systems and to determine the data gaps of COVID-19 incidence at the national and provincial levels in Indonesia. COVID-19 information flow was researched using government websites at the national and various provincial levels. To find the disparities, we assessed the number of cases reported at both levels at the same time and displayed the absolute and relative differences. The findings revealed that out of a total of 34 provinces in Indonesia, data differences were seen in 25 (73.52%) provinces in terms of positive cases, 31 (91.18%) provinces in terms of cured cases, and 28 (82.35%) provinces of the number of deaths. Our results showed a pressing need for high-quality, transparent, and timely information. The integration of COVID-19 data in Indonesia has not been optimal, implying that the reported COVID-19 incidence rate may be biased or delayed. COVID-19 incidents must be better monitored to disrupt the disease’s transmission chain. MDPI 2022-01-20 /pmc/articles/PMC8872239/ /pubmed/35206818 http://dx.doi.org/10.3390/healthcare10020204 Text en © 2022 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 Barsasella, Diana Iman, Arief Tarmansyah Fadly, Fery Uddin, Mohy Mohammed, Arshad Shaik, Tazeem Saputra, Hermawan Malwade, Shwetambara Dhar, Eshita Zakiah, Nurhadi, Jonnagaddala, Jitendra Syed-Abdul, Shabbir Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia |
title | Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia |
title_full | Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia |
title_fullStr | Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia |
title_full_unstemmed | Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia |
title_short | Information Flow and Data Gaps in COVID-19 Recording and Reporting at National and Provincial Levels in Indonesia |
title_sort | information flow and data gaps in covid-19 recording and reporting at national and provincial levels in indonesia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872239/ https://www.ncbi.nlm.nih.gov/pubmed/35206818 http://dx.doi.org/10.3390/healthcare10020204 |
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