Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS)

被引:4
|
作者
Murugesan, Malathi [1 ,2 ]
Venkatesan, Padmanaban [3 ]
Kumar, Senthil [4 ]
Thangavelu, Premkumar [5 ]
Rose, Winsley [6 ]
John, Jacob [4 ]
Castro, Marx
Manivannan, T.
Mohan, Venkata Raghava [4 ]
Rupali, Priscilla [5 ]
机构
[1] Christian Med Coll & Hosp, Dept Clin Microbiol, Vellore, Tamil Nadu, India
[2] Christian Med Coll & Hosp, Hosp Infect Control Comm, Vellore, Tamil Nadu, India
[3] Christian Med Coll & Hosp, Dept Biochem, Vellore, Tamil Nadu, India
[4] Christian Med Coll & Hosp, Dept Community Hlth, Vellore, Tamil Nadu, India
[5] Christian Med Coll & Hosp, Dept Infect Dis, Vellore, Tamil Nadu, India
[6] Christian Med Coll & Hosp, Dept Pediat, Vellore, Tamil Nadu, India
关键词
COVID-19; GIS; Spatial analysis; Mapping; CHALLENGES; HEALTH;
D O I
10.1016/j.ijid.2022.07.010
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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 100,00 0 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. (c) 2022 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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页码:669 / 675
页数:7
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