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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.
  • Murugesan M; Department of Clinical Microbiology & Hospital Infection Control Committee, Christian Medical College, Vellore, Tamil Nadu, India.
  • Venkatesan P; Department of Biochemistry, Christian Medical College, Vellore, Tamil Nadu, India.
  • Kumar S; Department of Community Health, Christian Medical College, Vellore, Tamil Nadu, India.
  • Thangavelu P; Department of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India.
  • Rose W; Department of Pediatrics, Christian Medical College, Vellore, Tamil Nadu, India.
  • John J; Department of Community Health, Christian Medical College, Vellore, Tamil Nadu, India.
  • Castro M; Deputy Director of Health Services, Vellore, Tamil Nadu, India.
  • Manivannan T; Deputy Director of Health Services, Vellore, Tamil Nadu, India.
  • Mohan VR; Department of Community Health, Christian Medical College, Vellore, Tamil Nadu, India. Electronic address: venkat@cmcvellore.ac.in.
  • Rupali P; Department of Infectious Diseases, Christian Medical College, Vellore, Tamil Nadu, India. Electronic address: prisci@cmcvellore.ac.in.
Int J Infect Dis ; 122: 669-675, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2015432
ABSTRACT

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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: J.ijid.2022.07.010

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Int J Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: J.ijid.2022.07.010