ArticleSustainable cities and society2020
Examining the association between socio-demographic composition and COVID-19 fatalities in the European region using spatial regression approach.
Article in Sustainable cities and society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 1 of them a synthesis that pooled it.
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Who cites it
129 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Capturing the spatiotemporal spread of COVID-19 in 30 European countries during 2020 - 2022.BMC public health · 2025Article
- Modeling the spatial spread of COVID-19 in Kenya.BMC public health · 2025Article
- Examining spatial variations in the relationship between domestic energy consumption and its driving factors using multiscale geographically weighted regression: a case study in Nottingham, England.Energy, sustainability and society · 2025Article
- Exploring the Spatial and Temporal Patterns of Children and Adolescents with COVID-19 Infections in Slovakia during March 2020 to July 2022.Medicina (Kaunas, Lithuania) · 2024Article
- Temporal trends in disparities in COVID-19 seropositivity among Canadian blood donors.International journal of epidemiology · 2024Article
- Social and economic variables explain COVID-19 diffusion in European regions.Scientific reports · 2024Article
- Association between area deprivation index and concerns to COVID-19: A multi-level analysis of individual and area factors.SSM - population health · 2024Article
- Spatiotemporal modeling of COVID-19 spread: unveiling socioeconomic disparities and patterns, across social classes in the urban population of Kermanshah, Iran.Frontiers in public health · 2024Article
- Exploring demographic, healthcare, and socio-economic factors as predictors of COVID-19 incidence rate: A spatial regression analysis.PloS one · 2024Article
- Article
- Mapping the pandemic: a review of Geographical Information Systems-based spatial modeling of Covid-19.Journal of public health in Africa · 2023Article
- Study on the spatial decomposition of the infection probability of COVID-19.Scientific reports · 2023Article
- COVID-19 spread prediction using socio-demographic and mobility-related data.Cities (London, England) · 2023Article
- Risk perception of compound emergencies: A household survey on flood evacuation and sheltering behavior during the COVID-19 pandemic.Sustainable cities and society · 2023Article
- Impact of social and demographic factors on the spread of the SARS-CoV-2 epidemic in the town of Nice.BMC public health · 2023Article
- Predicting onset risk of COVID-19 symptom to support healthy travel route planning in the new normal of long-term coexistence with SARS-CoV-2.Environment and planning. B, urban analytics and city science · 2023Article
- Associations between institutional-social-ecological factors and COVID -19 case-fatality: Evidence from 134 countries using multiscale geographically weighted regression (MGWR).One health (Amsterdam, Netherlands) · 2023Article
- Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland.International journal of environmental research and public health · 2023Article
- Using generalized structured additive regression models to determine factors associated with and clusters for COVID-19 hospital deaths in South Africa.BMC public health · 2023Article
69 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
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Abstract
The socio-demographic factors have a substantial impact on the overall casualties caused by the Coronavirus (COVID-19). In this study, the global and local spatial association between the key socio-demographic variables and COVID-19 cases and deaths in the European regions were analyzed using the spatial regression models. A total of 31 European countries were selected for modelling and subsequent analysis. From the initial 28 socio-demographic variables, a total of 2 (for COVID-19 cases) and 3 (for COVID-19 deaths) key variables were filtered out for the regression modelling. The spatially explicit regression modelling and mapping were done using four spatial regression models such as Geographically Weighted Regression (GWR), Spatial Error Model (SEM), Spatial Lag Model (SLM), and Ordinary Least Square (OLS). Additionally, Partial Least Square (PLS) and Principal Component Regression (PCR) was performed to estimate the overall explanatory power of the regression models. For the COVID cases, the local R
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