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
Author Information
  1. Munazza Fatima: Department of Geography, The Islamia University of Bahawalpur, Bahawalpur, Pakistan. munazza.fatima@iub.edu.pk.
  2. Ibtisam Butt: Institute of Geography, University of The Punjab, Lahore, Pakistan.
  3. Shahab MohammadEbrahimi: Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
  4. Behzad Kiani: Centre for Clinical Research, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
  5. Oliver Gruebner: Faculty of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland.

Abstract

BACKGROUND: In 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.
METHODS: We 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.
RESULTS: Our 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) in influencing ARI incidence, while socio-economic variables (rural population, literacy) had limited impact. In addition, GWR revealed that the relationships between predictors and ARI incidence varied across locations, emphasizing the importance of considering local settings. Season-based non-stationary GLM revealed a multifaceted interaction among socio-economic, meteorological, and air pollution factors.
CONCLUSIONS: Our 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.

Keywords

References

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MeSH Term

Pakistan
Humans
Air Pollution
Respiratory Tract Infections
Socioeconomic Factors
Incidence
Spatio-Temporal Analysis
Male
Acute Disease
Adult
Female
Child
Adolescent
Meteorological Concepts
Child, Preschool
Cluster Analysis
Infant

Word Cloud

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