Summary
The study models how climate change and stratospheric aerosol injection (GLENS‑SAI) could reshape malaria transmission across seven South Asian countries. Under high emissions, warming and increased rainfall intensify mosquito habitats, raising vector density, entomological inoculation rates (EIR), and malaria cases. GLENS‑SAI cools the region and reduces rainfall, lowering overall transmission, especially in India, Bangladesh and Nepal. However, localised increases appear in Iran, Pakistan and Afghanistan, indicating that SAI shifts, rather than eliminates, malaria risk.
Abstract
Background
Climate change is expected to reshape malaria transmission dynamics in tropical and subtropical regions. Stratospheric Aerosol Injection (SAI), a proposed solar geoengineering strategy to reduce global warming, could have unintended consequences for vector-borne diseases such as malaria. This study investigates how SAI, through the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS-SAI) scenario, could alter malaria transmission patterns across seven South Asian countries—Afghanistan, Bangladesh, Bhutan, Iran, India, Nepal, and Pakistan—compared with an unmitigated warming scenario over coming decades.
Methods
Using the VECTRI malaria model, malaria transmission dynamics were simulated from 2020 to 2097 under two climate pathways: the GLENS-SAI simulations, designed to stabilize global temperatures at 2020 levels, and the high-emissions Representative Concentration Pathway (RCP) 8.5—the control scenario (CTRL), representing unmitigated climate change. The model incorporated climatic and demographic factors to simulate vector density, Entomological Inoculation Rate (EIR), and malaria cases. Spatial patterns were assessed using distribution maps, while temporal variability was examined through time-series analysis. Statistical comparisons employed regional averages, anomaly detection, and significance testing.
Results
The findings reveal a redistribution of malaria transmission dynamics under the GLENS-SAI scenario, reflected in variations in vector density, EIR, and malaria cases. Compared to CTRL, the GLENS-SAI scenario reduces malaria transmission intensity across South Asia, though spatial heterogeneity persists. Significant declines in EIR are observed in India, Nepal, Bangladesh, northern Pakistan, southern Iran, and the Afghanistan-Pakistan border region, indicating the suppressive effect of the GLENS-SAI scenario on malaria transmission. However, localized increases in EIR are projected in southeastern Pakistan, western Afghanistan, north-central and eastern Iran, and northern Nepal. These shifts are likely driven by SAI-induced changes in temperature and precipitation, influencing mosquito survival and reproductive dynamics. Additionally, the annual malaria transmission cycle shortens in amplitude and duration across several endemic areas, suggesting a shift in seasonal transmission patterns and altered windows of disease risk throughout South Asia.
Conclusions
While the GLENS-SAI scenario may reduce malaria transmission across much of South Asia, localized increases highlight the need for region-specific public health strategies. These findings underscore the importance of incorporating GLENS-SAI scenario impacts into malaria control planning to address spatially varied effects.
