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Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran

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, t...

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Autores principales: Nasiri, R., Akbarpour, S., Zali, AR., Khodakarami, N., Boochani, MH., Noory, AR., Soori, H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114020/
https://www.ncbi.nlm.nih.gov/pubmed/33994652
http://dx.doi.org/10.1007/s10708-021-10438-x
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author Nasiri, R.
Akbarpour, S.
Zali, AR.
Khodakarami, N.
Boochani, MH.
Noory, AR.
Soori, H.
author_facet Nasiri, R.
Akbarpour, S.
Zali, AR.
Khodakarami, N.
Boochani, MH.
Noory, AR.
Soori, H.
author_sort Nasiri, R.
collection PubMed
description 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(2) were interesting among patients and underlying disorders; the local R(2) between hypertension and neurological diseases was 0.91 and 0.79, respectively, which was higher than other disorders. The highest rates of local R(2) for diabetes and heart disease were 0.67 and 0.55, respectively. From this study, it can be concluded the restrictions must be considered especially, in areas densely populated for all people.
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spelling pubmed-81140202021-05-12 Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran Nasiri, R. Akbarpour, S. Zali, AR. Khodakarami, N. Boochani, MH. Noory, AR. Soori, H. GeoJournal Article 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(2) were interesting among patients and underlying disorders; the local R(2) between hypertension and neurological diseases was 0.91 and 0.79, respectively, which was higher than other disorders. The highest rates of local R(2) for diabetes and heart disease were 0.67 and 0.55, respectively. From this study, it can be concluded the restrictions must be considered especially, in areas densely populated for all people. Springer Netherlands 2021-05-12 2022 /pmc/articles/PMC8114020/ /pubmed/33994652 http://dx.doi.org/10.1007/s10708-021-10438-x Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Nasiri, R.
Akbarpour, S.
Zali, AR.
Khodakarami, N.
Boochani, MH.
Noory, AR.
Soori, H.
Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran
title Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran
title_full Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran
title_fullStr Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran
title_full_unstemmed Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran
title_short Spatio-temporal analysis of COVID-19 incidence rate using GIS: a case study—Tehran metropolitan, Iran
title_sort spatio-temporal analysis of covid-19 incidence rate using gis: a case study—tehran metropolitan, iran
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8114020/
https://www.ncbi.nlm.nih.gov/pubmed/33994652
http://dx.doi.org/10.1007/s10708-021-10438-x
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