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Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective
BACKGROUND: The outbreak of coronavirus 2019 (COVID-19) which emerged in December 2019 spread rapidly and created a public health emergency. Geospatial records of case data are needed in real time to monitor and anticipate the spread of infection. METHODS: This study aimed to identify the emerging h...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
S. Karger AG
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805079/ http://dx.doi.org/10.1159/000520206 |
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author | Ashok, S. Zaka Ullah, Malik Vadivelu, Nandakumar Islam, Mohammed Tariqul Nasereddin, Safa Zafar Khan, Wajahat |
author_facet | Ashok, S. Zaka Ullah, Malik Vadivelu, Nandakumar Islam, Mohammed Tariqul Nasereddin, Safa Zafar Khan, Wajahat |
author_sort | Ashok, S. |
collection | PubMed |
description | BACKGROUND: The outbreak of coronavirus 2019 (COVID-19) which emerged in December 2019 spread rapidly and created a public health emergency. Geospatial records of case data are needed in real time to monitor and anticipate the spread of infection. METHODS: This study aimed to identify the emerging hotspots of COVID-19 using a geographic information system (GIS)-based approach. Data of laboratory-confirmed COVID-19 patients from March 15 to June 12, 2020, who visited the emergency department of a tertiary specialized academic hospital in Dubai were evaluated using ArcGIS Pro 2.5. Spatiotemporal analysis, including optimized hotspot analysis, was performed at the community level. RESULTS: The cases were spatially concentrated mostly over the inner city of Dubai. Moreover, the optimized hotspot analysis showed statistically significant hotspots (p < 0.01) in the north of Dubai. Waxing and waning hotspots were also observed in the southern and central regions of Dubai. Finally, there were nonsustaining hotspots in communities with a very low population density. CONCLUSION: This study identified hotspots of COVID-19 using geospatial analysis. It is simple and can be easily reproduced to identify disease outbreaks. In the future, more attention is needed in creating a wider geodatabase and identifying hotspots with more intense transmission intensity. |
format | Online Article Text |
id | pubmed-8805079 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | S. Karger AG |
record_format | MEDLINE/PubMed |
spelling | pubmed-88050792022-02-02 Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective Ashok, S. Zaka Ullah, Malik Vadivelu, Nandakumar Islam, Mohammed Tariqul Nasereddin, Safa Zafar Khan, Wajahat Dubai Medical Journal Research Article BACKGROUND: The outbreak of coronavirus 2019 (COVID-19) which emerged in December 2019 spread rapidly and created a public health emergency. Geospatial records of case data are needed in real time to monitor and anticipate the spread of infection. METHODS: This study aimed to identify the emerging hotspots of COVID-19 using a geographic information system (GIS)-based approach. Data of laboratory-confirmed COVID-19 patients from March 15 to June 12, 2020, who visited the emergency department of a tertiary specialized academic hospital in Dubai were evaluated using ArcGIS Pro 2.5. Spatiotemporal analysis, including optimized hotspot analysis, was performed at the community level. RESULTS: The cases were spatially concentrated mostly over the inner city of Dubai. Moreover, the optimized hotspot analysis showed statistically significant hotspots (p < 0.01) in the north of Dubai. Waxing and waning hotspots were also observed in the southern and central regions of Dubai. Finally, there were nonsustaining hotspots in communities with a very low population density. CONCLUSION: This study identified hotspots of COVID-19 using geospatial analysis. It is simple and can be easily reproduced to identify disease outbreaks. In the future, more attention is needed in creating a wider geodatabase and identifying hotspots with more intense transmission intensity. S. Karger AG 2021-12-10 /pmc/articles/PMC8805079/ http://dx.doi.org/10.1159/000520206 Text en Copyright © 2021 by S. Karger AG, Basel https://creativecommons.org/licenses/by-nc/4.0/This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements. |
spellingShingle | Research Article Ashok, S. Zaka Ullah, Malik Vadivelu, Nandakumar Islam, Mohammed Tariqul Nasereddin, Safa Zafar Khan, Wajahat Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective |
title | Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective |
title_full | Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective |
title_fullStr | Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective |
title_full_unstemmed | Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective |
title_short | Surveillance of COVID-19 Using Geospatial Data: An Emergency Department Perspective |
title_sort | surveillance of covid-19 using geospatial data: an emergency department perspective |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805079/ http://dx.doi.org/10.1159/000520206 |
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