Modeling spatial PM2.5 risk dynamics and projecting disease burden in Pakistan

Abstract

Air pollution, especially small particulate matter (PM₂.₅), has emerged as a significant public health crisis in Pakistan, yet its long-term health impacts remain understudied. There is a critical lack of high-resolution spatiotemporal analysis that captures the changing exposure levels and associated mortality trends over extended periods. This study investigates this gap by addressing the spatiotemporal variations in PM_2.5 exposure and its associated mortality burden from 2000 to 2021. Additionally, it projects possible spatiotemporal changes in mortality for two scenarios, business-as-usual and PM_2.5 mitigation. The Global Exposure Mortality Model (GEMM) was applied on 0.01° resolution gridded PM_2.5 and population concentration data to quantify PM_2.5-attributed mortality for major diseases: ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lower respiratory infection (LRI) and lung cancer (LC). The results showed escalating levels and expanded geographical spread of PM_2.5 and mortality in Pakistan. Population exposure estimates reveal high-risk zones with over 80 μg/m³ concentrations engulfing densely inhabited areas far exceeding the WHO annual limit of 5 μg/m³. The number of PM_2.5 -related deaths increased from 57,100 in 2000 to 157,762 in 2021. IHD showed the highest sensitivity to PM_2.5, marked by over three times higher hazard ratio at 150 μg/m³ exposure. Spatial mapping revealed IHD and LRI mortality hotspots corresponding to settlers near the Indus River basin. Notably, central parts recorded over 2 μg/m³ annual PM_2.5 increase. Future projections based on growth trajectories forecast that the uncontrolled increase in PM_2.5 could inflate ischemic heart disease deaths from 14,248 to 142,903 by 2030, leading to a total PM_2.5 -related mortality burden exceeding 290,000 deaths. However, stabilizing PM_2.5 levels under a mitigation scenario could significantly reduce mortality to 29,062 by 2030. This study provides critical insights into demographic vulnerabilities, high-risk zones, and future mortality trends, emphasizing the urgency for mitigation policies to safeguard millions facing existential risk.