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        Spatial prediction and mapping of the COVID-19 hotspot in India using geostatistical technique

        Parvin Farhana,Ali Sk Ajim,Hashmi S. Najmul Islam,Ateeque Ahmad 대한공간정보학회 2021 Spatial Information Research Vol.29 No.4

        The world has now facing a health crisis due to outbreak of novel coronavirus 2019 (COVID-19). The numbers of infection and death have been rapidly increasing which result in a serious threat to the social and economic crisis. India as the second most populous nation of the world has also running with a serious health crisis, where more than 8,300,500 people have been infected and 123,500 deaths due to this deadly pandemic. Therefore, it is urgent to highlight the spatial vulnerability to identify the area under risk. Taking India as a study area, a geospatial analysis was conducted to identify the hotspot areas of the COVID-19. In the present study, four factors naming total population, population density, foreign tourist arrivals to India and reported confirmed cases of the COVID-19 were taken as responsible factors for detecting hotspot of the novel coronavirus. The result of spatial autocorrelation showed that all four factors considered for hotspot analysis were clustered and the results were statistically significant (p value \0.01). The result of GetisOrd Gi* statistics revealed that the total population and reported COVID-19 cases have got high priority for considering hotspot with greater z-score ([ 3 and [ 0.7295 respectively). The present analysis reveals that the reported cases of COVID-19 are higher in Maharashtra, followed by Tamil Nadu, Gujarat, Delhi, Uttar Pradesh, and West Bengal. The spatial result and geospatial methodology adopted for detecting COVID-19 hotspot in the Indian subcontinent can help implement strategies both at the macro and micro level. In this regard, social distancing, avoiding social meet, staying at home, avoiding public transport, self-quarantine and isolation are suggested in hotspot zones; together with, the international support is also required in the country to work jointly for mitigating the spread of COVID-19.

      • KCI등재

        Accessibility and site suitability for healthcare services using GISbased hybrid decision-making approach: a study in Murshidabad, India

        Parvin Farhana,Ali Sk Ajim,Hashmi S. Najmul Islam,Khatoon Aaisha 대한공간정보학회 2021 Spatial Information Research Vol.29 No.1

        Healthcare accessibility and site suitability analysis is an elongated and complex task that requires evaluation of different decision factors. The main objective of the present study was to develop a hybrid decisionmaking approach with geographic information systems to integrate spatial and non-spatial data to form a weighted result. This study involved three-tier analyses for assessing accessibility and selecting suitable sites for healthcare facilities, and analysing shortest-path network. The first tier of analysis stressed the spatial distance, density and proximity from existing healthcare to find more deprived and inaccessible areas in term of healthcare facilities. The result revealed that spatial discrepancy exists in the study area in term of access to healthcare facilities and for achieving equal healthcare access, it is essential to propose new plans. Thus, require finding suitable sites for put forward new healthcare service, which was highlighted in the second tier of analysis based on land use land cover, distancing to road and rail, proximity to residential areas, and weighted overlay of accessibility as decision factors. Finally, in the third tier of analysis, the most suitable site among the proposed healthcare was identified using the technique for order of preference by similarity to ideal solution. The road network analysis was also performed in this study to determine the shortest and fastest route from these healthcare facilities to connect with district medical hospital. The present study found some suitable sites throughout the district on inaccessible zones where people are deprived from better healthcare facilities. This attempt will highly helpful for preparing a spatial decision support system which assists the health authorities regarding the healthcare services in inaccessible, underprivileged, and rural areas.

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