Assessing the impact of socio-economic and environmental factors on COVID-19 spread in urban neighborhoods: evidence from Urmia, Iran DOI
Javad Imani Shamloo, Farzad Dargahi,

Mohammadreza Ezzati Mehr

et al.

Cities & Health, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: Nov. 6, 2024

The majority of the world's population has been living in cities for past two decades, making these areas particularly vulnerable to various stressors, including natural and man-made disasters. A growing literature suggests that socio-economic environmental indicators significantly affect epidemic. As a result, this research aims investigate effect on rate infection with COVID-19 neighborhoods Urmia City Iran. This study uses Moran's analysis, cluster outlier analysis identify high-risk low-risk areas, as well weighted spatial regression analysis. results indicate number employees, elderly people, construction density, road density have significant relationship predicting Based variables patients Iran, predicted values coronavirus risk contracting southern part western is higher than northern northeastern areas.

Language: Английский

The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis DOI Creative Commons

Laura Houweling,

Anke H. Maitland‐van der Zee, Judith C.S. Holtjer

et al.

Environmental Research, Journal Year: 2023, Volume and Issue: 240, P. 117351 - 117351

Published: Oct. 17, 2023

The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims synthesize findings from ecological non-ecological studies investigate the impact multiple urban-related features on a variety COVID-19 health outcomes.On December 5, 2022, PubMed was searched identify all types observational that examined one or more exposome characteristics in relation outcomes such as infection severity, need for hospitalization, ICU admission, COVID pneumonia, mortality.A total 38 241 were included this review. Non-ecological highlighted significant effects population density, urbanization, pollutants, particularly PM2.5. meta-analyses revealed 1 μg/m3 increase PM2.5 higher likelihood hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) death 1.06 CI:1.03-1.09)). Ecological studies, addition confirming also indicated nitrogen dioxide (NO2), ozone (O3), sulphur (SO2), carbon monoxide (CO), well lower temperature, humidity, ultraviolet (UV) radiation, less green blue space exposure, increased morbidity mortality.This identified several key vulnerability related areas context recent pandemic. underscore importance improving policies exposures implementing measures protect individuals these harmful environmental stressors.

Language: Английский

Citations

5
Geospatial analysis of Covid-19 mortality linked to environmental risk factors in Iran- 2019-2021 DOI Creative Commons
Laleh R. Kalankesh,

Khalil Golamnia,

Alireza Hajighasemkhani

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: April 1, 2024

Abstract Objectives This study aims to investigate the impact of various demographic, environmental, and topographical factors on COVID-19 mortality rates in different geographical provinces Iran. Methods The research utilized data from DATASUS (Ministry Health), International Classification Diseases (ICD-10), WorldClimV1, Sentinel-5P TROPOMI-based datasets, Open Street Map (OSM), Shuttle Radar Topography Mission satellite (SRTM) gather mortality, data, evaluating them by sex, age group, province. analysis employed Geographic Information Systems methodology logistic regression. Results Higher were observed central southern regions, with West Azerbaijan Sistan-Baluchestan showing elevated compared their population sizes. Additionally, South Khorasan, Sistan-Baluchestan, Semnan, Bushehr, Ilam exhibited higher ratios relative mean temperature. displayed a ratio air pollution concerning Covid-19 notably around Uremia Lake, significant correlation. Logistic regression revealed positive correlations NO 2 O 3 while CO SO showed negative correlations. Furthermore, population, density, area emerged as most influential affecting rate. Conclusions findings this offer valuable insights for policymakers public health officials develop targeted interventions reducing virus's high-risk areas enhancing healthcare resources infrastructure urban settings.

Language: Английский

Citations

0
Assessing the impact of socio-economic and environmental factors on COVID-19 spread in urban neighborhoods: evidence from Urmia, Iran DOI
Javad Imani Shamloo, Farzad Dargahi,

Mohammadreza Ezzati Mehr

et al.

Cities & Health, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: Nov. 6, 2024

The majority of the world's population has been living in cities for past two decades, making these areas particularly vulnerable to various stressors, including natural and man-made disasters. A growing literature suggests that socio-economic environmental indicators significantly affect epidemic. As a result, this research aims investigate effect on rate infection with COVID-19 neighborhoods Urmia City Iran. This study uses Moran's analysis, cluster outlier analysis identify high-risk low-risk areas, as well weighted spatial regression analysis. results indicate number employees, elderly people, construction density, road density have significant relationship predicting Based variables patients Iran, predicted values coronavirus risk contracting southern part western is higher than northern northeastern areas.

Language: Английский

Citations

0