Evidence map›Paper›PMID 41223235›Full record

ArticlePloS one2025

Geographical and climatic risk factors for COVID-19 in southwest Iran during the 2020-2021 epidemic.

Koorosh Nikaein, Zahra Kanannejad, Mohammad Amin Ghatee

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Koorosh NikaeinStudent Research Committee, Yasuj University of Medical Sciences, Yasuj, Iran.
Zahra KanannejadAllergy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad Amin GhateeProfessor Alborzi Clinical Microbiology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.ORCID https://orcid.org/0000-0001-6325-038X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has had a devastating impact worldwide, with Iran being one of the hardest-hit countries in the Middle East. Understanding the factors that influence the spread of the virus is crucial for developing effective mitigation strategies. This study aims to investigate the geographical and climatic risk factors associated with COVID-19 incidence in the Kohgiluyeh and Boyer-Ahmad Province of southwest Iran during the 2020-2021 epidemic period. The study involved mapping the residential addresses of 15,585 patients with COVID-19 during 2020-2021. Geographical Information System (GIS) evaluated the effects of geographical and climatic determinants, including temperature, rainfall, humidity, evaporation, elevation, slope, and land cover, on COVID-19 occurrence. The data were analyzed using univariate and multivariate binary logistic regression. In the univariate model, significant climatic factors affecting COVID-19 susceptibility included elevation (p < 0.001, OR=0.617), evaporation (p < 0.001, OR=0.635), dusty days (p < 0.001, OR=1.050), humidity (p = 0.005, OR=1.013), and rainfall (p = 0.032, OR=0.998). Additionally, urban areas (p < 0.001, OR=65), irrigated farms (p < 0.001, OR=5.723), dry farms (p < 0.001, OR=3.101), thin forests (p = 0.009, OR=2.975), and thin rangeland (p = 0.030, OR=2.571) demonstrated the highest impact on the disease distribution. In the multivariate analysis, urban areas (p < 0.001 and OR=47.123), irrigated farms (p < 0.001, OR=4.510), dry farms (p = 0.006, OR=3.002), evaporation (p < 0.001, OR=0.999), and elevation (p < 0.001, OR=0.999) were found to be the main factors related to COVID-19 occurrence. Based on the study results, individuals living in urban areas, irrigated and dry farms, as well as in regions with lower elevation and lower evaporation, have a higher risk of contracting COVID-19.

Indexed as

ClimateCOVID-19AdultFemaleGeographic Information SystemsHumansHumidityIncidenceIranMaleMiddle AgedPandemicsRisk FactorsSARS-CoV-2

Identifiers

PMID41223235
PMCPMC12611132

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.