ArticleEnvironmental challenges (Amsterdam, Netherlands)2021
Spatial analysis of COVID-19 incidence and its determinants using spatial modeling: A study on India.
Article in Environmental challenges (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Respiratory syncytial virus disease burden in adults aged ≥50 years old: A retrospective national surveillance database analysis in Mexico (2015-2023).Human vaccines & immunotherapeutics · 2026Article
- Mapping the COVID-19 pandemic in Burkina Faso: spatial patterns, socioeconomic factors, and public health implications.International journal of health geographics · 2026Article
- Bayesian uncertainty quantification to identify population level vaccine hesitancy behaviours.PloS one · 2026Article
- Spatiotemporal dynamics and associated drivers of COVID-19 incidence in Nepal.Tropical medicine and health · 2025Article
- Outlier detection in spatial error models using modified thresholding-based iterative procedure for outlier detection approach.BMC medical research methodology · 2024Article
- Harnessing AI for public health: India's roadmap.Frontiers in public health · 2024Article
- Mapping the pandemic: a review of Geographical Information Systems-based spatial modeling of Covid-19.Journal of public health in Africa · 2023Article
- Spatiotemporal pattern of COVID-19 mortality and its relationship with socioeconomic and environmental factors in England.Spatial and spatio-temporal epidemiology · 2023Article
- The impact of Covid-19 containment lockdowns on MSMEs in India and resilience of exporting firms.Journal of economic behavior & organization · 2023Article
- Regional differences in health screening participation between before and during COVID-19 pandemic.Environmental health and preventive medicine · 2023Article
- Effects of Vaccination and the Spatio-Temporal Diffusion of Covid-19 Incidence in Turkey.Geographical analysis · 2022Article
- Spatiotemporal clustering patterns and sociodemographic determinants of COVID-19 (SARS-CoV-2) infections in Helsinki, Finland.Spatial and spatio-temporal epidemiology · 2022Article
- Are spatial patterns of Covid-19 changing? Spatiotemporal analysis over four waves in the region of Cantabria, Spain.Transactions in GIS : TG · 2022Article
- Spatial analysis of socio-economic factors and their relationship with the cases of COVID-19 in Pernambuco, Brazil.Tropical medicine & international health : TM & IH · 2022Article
- Characterizing COVID-19 waves in urban and rural districts of India.npj urban sustainability · 2022Article
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3 authors.
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Abstract
The first incident of COVID-19 case in India was recorded on 30th January, 2020 which turns to 100,000 marks on May 19th and by June 3rd it was over 200,000 active cases and 5,800 deaths. Geographic Information System (GIS) based spatial models can be helpful for better understanding of different factors that have triggered COVID-19 spread at district level in India. In the present study, 19 variables were considered that can explain the variability of the disease. Different spatial statistical techniques were used to describe the spatial distribution of COVID-19 and identify significant clusters. Spatial lag and error models (SLM and SEM) were employed to examine spatial dependency, geographical weighted regression (GWR) and multi-scale GWR (MGWR) were employed to examine at local level. The results show that the global models perform poorly in explaining the factors for COVID-19 incidences. MGWR shows the best-fit-model to explain the variables affecting COVID-19 (R2= 0.75) with lowest AICc value. Population density, urbanization and bank facility were found to be most susceptible for COVID-19 cases. These indicate the necessity of effective policies related to social distancing, low mobility. Mapping of different significant variables using MGWR can provide significant insights for policy makers for taking necessary actions.
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