Evidence mapPaperPMID 39910401Full record

ArticleBMC public health2025

Spatiotemporal clusters of acute respiratory infections associated with socioeconomic, meteorological, and air pollution factors in South Punjab, Pakistan.

Munazza Fatima, Ibtisam Butt, Shahab MohammadEbrahimi, Behzad Kiani, Oliver Gruebner

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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

5 authors.

Munazza FatimaDepartment of Geography, The Islamia University of Bahawalpur, Bahawalpur, Pakistan. munazza.fatima@iub.edu.pk.
Ibtisam ButtInstitute of Geography, University of The Punjab, Lahore, Pakistan.
Shahab MohammadEbrahimiDepartment of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Behzad KianiCentre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
Oliver GruebnerFaculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn Pakistan, acute respiratory infections (ARI) continue to be a major public health problem. However, there is still a lack of scholarly work regarding different environmental and socioeconomic influencing factors and how they interact with respiratory infections. Furthermore, we do not know much about geographic variation in this context. Therefore, our study examines the ecological-level spatial and temporal patterns of acute respiratory infection incidence (ARI) and their geographic relationship with selected socio-economic, meteorological, and air pollution factors in Pakistan.

methodsWe applied the spatiotemporal scan statistics to examine the purely temporal, spatial, and spatiotemporal clusters of ARI in South Punjab, Pakistan for five years (2016-2020). Generalized Linear Model (GLM) and geographically weighted regression (GWR) were also applied to model the linear and non-linear spatial relationships between selected variables and ARI.

resultsOur results indicate that in the central and northern regions of Pakistan, two spatial clusters of ARI were present, accounting for 28.5% of the total cases. A spatiotemporal cluster with a relative risk of 1.57 was discovered in the northeastern area. The results obtained from the season-based GLM highlighted the significance of climatic factors (temperature, fog, dust storms) and air pollutants (NO

conclusionsOur study provides evidence about environmental and socio-economic factors significantly associated with ARI incidence. In addition, this study provides the first baseline of ARI cases in Pakistan to plan for intervention and adaptation strategies and may be replicated in other regions of comparable settings worldwide.

Indexed as

Air PollutionMeteorological ConceptsRespiratory Tract InfectionsAcute DiseaseFemaleHumansIncidenceMalePakistanRisk FactorsSocioeconomic FactorsSpatio-Temporal AnalysisWeatherAcute respiratory infectionsGeneralized linear modelGeographically weighted regressionPakistanSpace–time clustering

Identifiers

PMID39910401
PMCPMC11800423

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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 Socratic graph.