ArticleGeoJournal2022
Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study-Tehran metropolitan, Iran.
Article in GeoJournal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
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Who cites it
11 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review.The Science of the total environment · 2022Pooled 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
- Potential physical distance in the open urban grey space of city counties in Poland and COVID-19 cases and deaths throughout the pandemic.Archives of public health = Archives belges de sante publique · 2025Article
- Assessing eco-geographic influences on COVID-19 transmission: a global analysis.Scientific reports · 2024Article
- Review
- The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis.Tropical medicine and infectious disease · 2023Article
- Modelling Impact of High-Rise, High-Density Built Environment on COVID-19 Risks: Empirical Results from a Case Study of Two Chinese Cities.International journal of environmental research and public health · 2023Article
- Cost-benefit analysis of Intensive Care Unit with Activity-Based Costing approach in the era COVID-19 pandemic: A case study from Iran.PloS one · 2023Article
- Spatiotemporal pattern of Covid-19 outbreak in Turkey.GeoJournal · 2023Article
- Factors that most expose countries to COVID-19: a composite indicators-based approach.GeoJournal · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 has been distinguished as a zoonotic coronavirus, like SARS coronavirus and MERS coronavirus. Tehran metropolis, as the capital of Iran, has a high density of residents that experienced a high incidence and mortality rates which daily increase the number of death and cases. In this study, the IDW (Inverse Distance Weight), Hotspots, and GWR (Geography Weighted Regression) Model are used as methods for analyzing big data COVID-19 in Tehran. The results showed that the majority of patients and deaths were men, but the death rate was higher in women than in men; also was observed a direct relationship between the area of the houses, and the infected rate, to COVID-19. Also, the results showed a disproportionate distribution of patients in Tehran, although in the eastern regions the number of infected people is higher than in other districts; the eastern areas have a high population density as well as residential land use, and there is a high relationship between population density in residential districts and administrative-commercial and the number of COVID-19 cases in all regions. The outputs of local R
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