Spatial mapping of the incidence, case-fatality ratio and recovery rate of COVID-19 in West Bengal: A situational analysis | ||||
| Microbes and Infectious Diseases | ||||
| Article 4, Volume 4, Issue 2, May 2023, Page 357-369 PDF (1.23 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mid.2023.164770.1387 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Buddhadev Hembram  1; Ratan Pal2; N.C. Jana2
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| 1Department of Geography,The Uniersity of Burdwan, West Bengal, India. | ||||
| 2Department of Geography, The University of Burdwan, West Bengal, India. | ||||
| Abstract | ||||
| Information on the spatial and temporal distributions of COVID-19 cases is important for improved control, social distancing strategies and developing targeted prevention strategies. Towards this objective, we analyzed the spatial and temporal growth pattern of COVID-19 incidence and death counts in districts of West Bengal. This paper also analyzes the current trend or pattern of COVID-19 transmission in West Bengal. For this approach, COVID-19 data have been compiled from several sources, including the WHO, Ministry of Health and Family Welfare (MoHFW), and demographic data from Census of India (2011). This analytical study was conducted based on detailed data from 23 districts of West Bengal from May 31, 2020, till December 31, 2021. We used ArcGIS Software for map-making and different formulas to measure Incidence, CFR, and CRR, considering all possible scenarios. Up to December 31, 2021, Kolkata, the origin of the COVID-19 epidemic, had reported 337767 COVID-19 cases, while the confirmed cases in the surrounding districts North 24 Parganas, South 24 Parganas, and Howrah were 337091, 104268, and 102048, respectively. The top five districts with the highest incidence were Kolkata (7.51%), Darjeeling (3.66%), North 24 Parganas (3.36%), Kalimpong (2.85%), and Jalpaiguri (1.79%), had high risks of COVID-19. Therefore, identification of the case fatality, recovery rates, and spatiotemporal trends should be the first step to evaluate disease severity and develop effective policies to manage and control any new epidemic. These results are informative locally and useful for the rest of the world. | ||||
| Keywords | ||||
| COVID-19; Incidence; Case-Fatality Ratio; Case recovery rates; Trend Analysis | ||||
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