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Year : 2022  |  Volume : 9  |  Issue : 2  |  Page : 177-181

Community mapping of COVID-19 cases admitted from April to June 2020 at a tertiary health care hospital in Raigad district in Maharashtra, India

Department of Community Medicine, MGM Medical College and Hospital, Navi Mumbai, Maharashtra, India

Correspondence Address:
Dr. Saili Jadhav
Department of Community Medicine, MGM Medical College and Hospital, Kamothe, Navi Mumbai 410209, Maharashtra
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/mgmj.mgmj_22_22

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Introduction: At end of 2019, a novel coronavirus caused severe acute respiratory syndrome, which emerged in Wuhan, Hubei province of China. Health professionals have always used conventional mapping (in recent times geographic information systems [GIS] mapping) as a useful tool for better tracking which further facilitated better management of deadly contagions such as SARS-CoV 2. This study aimed to map geographically the positive patients admitted in a dedicated COVID-19 hospital which is a tertiary care hospital from April to June 2020 to gain insight into the local viral transmission and pattern of geographical spread because of ongoing cluster transmission. Objectives: The aims of this study were (1) to locate geographically the COVID-19 cases admitted from April to June 2020 at a tertiary health-care facility, (2) to study trends and patterns of geographical spread, and (3) to identify geographical clustering of cases, if any. Materials and Methods: This was an observational, cross-sectional, secondary data-based study. The study was conducted at MGM Medical College Hospital, Kamothe. The data were collected from existing surveillance and lab data records. The data were analyzed in Excel and Epi info. Specialized GIS software was used for mapping to Taluka level based on patients’ addresses using standard “.shp” files for the local area. Results: There were a total of 968 cases. The majority of which were from Raigad district (839, 87%). The Panvel taluka in Raigad District having Panvel as a major city and the thickly populated urban area has shown clustering of cases extending to neighboring Uran taluka. Conclusion: For better preparedness, we need to keep tracking new outbreaks through GIS and promote further advances in mapping technologies.

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