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RISS 인기검색어
- 검색키워드
- 저자 : Atre Nitin M. (검색결과 2 건)
- 무료
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Shil Pratip,Atre Nitin M.,Patil Avinash A.,Tandale Babasaheb V.,Abraham Priya 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2
SARS-CoV-2 or COVID-19 was introduced into India by multiple sources generating local clusters and leading to the nationwide spread. A retrospective study has been conducted on the epidemiological features and spatial spread of COVID-19 in India during February 2020–March 2021. For each district, the cumulative number of confirmed COVID-19 cases were fitted to exponential growth model for the initial phase of the outbreak (the first 7–15 days). From the estimated growth rate, epidemiological parameters like the Basic reproduction number (R0) and epidemic doubling time (s) were determined. Using Q-GIS software, we have generated the all India distribution maps for R0 and s. COVID-19 spread rapidly covering majority of the districts of India between March and June 2020. As on 1st March 2021, a total of 715 out of 717 districts have been affected. The R0 range is at par with the global average. A few districts, where outbreaks were caused by migrant workers coming home, intense transmission was recorded R0[7. We also found that the spread of COVID-19 was not uniform across the different districts of India. The methodology developed in the study can be used by researchers and public health professionals to analyze and study epidemics in future.
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Shil Pratip,Atre Nitin M.,Patil Avinash A.,Tandale Babasaheb V.,Abraham Priya 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1
SARS-CoV-2 or COVID-19 was introduced into India by multiple sources generating local clusters and leading to the nationwide spread. A retrospective study has been conducted on the epidemiological features and spatial spread of COVID-19 in India during February 2020–March 2021. For each district, the cumulative number of confirmed COVID-19 cases were fitted to exponential growth model for the initial phase of the outbreak (the first 7–15 days). From the estimated growth rate, epidemiological parameters like the Basic reproduction number (R0) and epidemic doubling time (s) were determined. Using Q-GIS software, we have generated the all India distribution maps for R0 and s. COVID-19 spread rapidly covering majority of the districts of India between March and June 2020. As on 1st March 2021, a total of 715 out of 717 districts have been affected. The R0 range is at par with the global average. A few districts, where outbreaks were caused by migrant workers coming home, intense transmission was recorded R0[7. We also found that the spread of COVID-19 was not uniform across the different districts of India. The methodology developed in the study can be used by researchers and public health professionals to analyze and study epidemics in future.
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