Cargando…
Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS)
OBJECTIVES: Geographical Information Surveillance (GIS) is an advanced digital technology tool that maps location-based data and helps in epidemiological modeling. We applied GIS to analyze patterns of spread and hotspots of COVID-19 cases in the Vellore district in South India. METHODS: Laboratory-...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263687/ https://www.ncbi.nlm.nih.gov/pubmed/35811075 http://dx.doi.org/10.1016/j.ijid.2022.07.010 |
_version_ | 1784742793940303872 |
---|---|
author | Murugesan, Malathi Venkatesan, Padmanaban Kumar, Senthil Thangavelu, Premkumar Rose, Winsley John, Jacob Castro, Marx Manivannan, T. Mohan, Venkata Raghava Rupali, Priscilla |
author_facet | Murugesan, Malathi Venkatesan, Padmanaban Kumar, Senthil Thangavelu, Premkumar Rose, Winsley John, Jacob Castro, Marx Manivannan, T. Mohan, Venkata Raghava Rupali, Priscilla |
author_sort | Murugesan, Malathi |
collection | PubMed |
description | OBJECTIVES: Geographical Information Surveillance (GIS) is an advanced digital technology tool that maps location-based data and helps in epidemiological modeling. We applied GIS to analyze patterns of spread and hotspots of COVID-19 cases in the Vellore district in South India. METHODS: Laboratory-confirmed COVID-19 cases from the Vellore district and neighboring taluks from March 2020 to June 2021 were geocoded and spatial maps were generated. Time trends exploring urban-rural burden with an age-sex distribution of cases and other variables were correlated with outcomes. RESULTS: A total of 45,401 cases of COVID-19 were detected, with 20,730 cases during the first wave and 24,671 cases during the second wave. The overall incidence rates of COVID-19 were 462.8 and 588.6 per 100,000 population during the first and second waves, respectively. The spread pattern revealed epicenters in densely populated urban areas with radial spread sparing rural areas in the first wave. The case fatality rate was 1.89% and 1.6% during the first and second waves, which increased with advancing age. CONCLUSIONS: Modern surveillance systems like GIS can accurately predict the trends and spread patterns during future pandemics. In addition, real-time mapping can help design risk mitigation strategies, thereby preventing the spread to rural areas. |
format | Online Article Text |
id | pubmed-9263687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92636872022-07-08 Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) Murugesan, Malathi Venkatesan, Padmanaban Kumar, Senthil Thangavelu, Premkumar Rose, Winsley John, Jacob Castro, Marx Manivannan, T. Mohan, Venkata Raghava Rupali, Priscilla Int J Infect Dis Article OBJECTIVES: Geographical Information Surveillance (GIS) is an advanced digital technology tool that maps location-based data and helps in epidemiological modeling. We applied GIS to analyze patterns of spread and hotspots of COVID-19 cases in the Vellore district in South India. METHODS: Laboratory-confirmed COVID-19 cases from the Vellore district and neighboring taluks from March 2020 to June 2021 were geocoded and spatial maps were generated. Time trends exploring urban-rural burden with an age-sex distribution of cases and other variables were correlated with outcomes. RESULTS: A total of 45,401 cases of COVID-19 were detected, with 20,730 cases during the first wave and 24,671 cases during the second wave. The overall incidence rates of COVID-19 were 462.8 and 588.6 per 100,000 population during the first and second waves, respectively. The spread pattern revealed epicenters in densely populated urban areas with radial spread sparing rural areas in the first wave. The case fatality rate was 1.89% and 1.6% during the first and second waves, which increased with advancing age. CONCLUSIONS: Modern surveillance systems like GIS can accurately predict the trends and spread patterns during future pandemics. In addition, real-time mapping can help design risk mitigation strategies, thereby preventing the spread to rural areas. The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2022-09 2022-07-08 /pmc/articles/PMC9263687/ /pubmed/35811075 http://dx.doi.org/10.1016/j.ijid.2022.07.010 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Murugesan, Malathi Venkatesan, Padmanaban Kumar, Senthil Thangavelu, Premkumar Rose, Winsley John, Jacob Castro, Marx Manivannan, T. Mohan, Venkata Raghava Rupali, Priscilla Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) |
title | Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) |
title_full | Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) |
title_fullStr | Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) |
title_full_unstemmed | Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) |
title_short | Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS) |
title_sort | epidemiological investigation of the covid-19 outbreak in vellore district in south india using geographic information surveillance (gis) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263687/ https://www.ncbi.nlm.nih.gov/pubmed/35811075 http://dx.doi.org/10.1016/j.ijid.2022.07.010 |
work_keys_str_mv | AT murugesanmalathi epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT venkatesanpadmanaban epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT kumarsenthil epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT thangavelupremkumar epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT rosewinsley epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT johnjacob epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT castromarx epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT manivannant epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT mohanvenkataraghava epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis AT rupalipriscilla epidemiologicalinvestigationofthecovid19outbreakinvelloredistrictinsouthindiausinggeographicinformationsurveillancegis |