The Impact of Climate Change on the Transmission of Malaria
A recent study suggests that a novel model for forecasting the influence of climate change on malaria transmission in Africa might pave the way for more precise interventions aimed at controlling the disease.
Previous techniques relied on rainfall measurements to infer the presence of surface water conducive to mosquito breeding. However, a study led by the University of Leeds employed multiple climatic and hydrological models, incorporating real-world processes like evaporation, infiltration, and river flow.
This method offers a more comprehensive understanding of malaria-favorable conditions across Africa.
Amplifying the Role of Water Bodies
Furthermore, it sheds light on the significance of water bodies such as the Zambezi River in disease transmission. The study reveals that nearly four times the previously estimated population resides in areas suitable for malaria transmission for up to nine months annually.
The findings, presented in the journal Science under the title “Future malaria environmental suitability in Africa is sensitive to hydrology,” underscore the sensitivity of malaria risk to hydrological factors.
Dr. Mark Smith, an Associate Professor in Water Research at Leeds’ School of Geography and the lead author of the study, emphasized, “This approach provides a more realistic estimation of areas in Africa that will experience changes in malaria prevalence. With increasingly precise data on water flows, we can utilize this understanding to prioritize and tailor malaria interventions more effectively. This is particularly crucial given the limited healthcare resources often available.”
Implications of Climate Sensitivity and Regional Burden
Malaria, a climate-sensitive disease transmitted by vectors, resulted in 608,000 fatalities out of 249 million cases in 2022. Africa reported 95% of global cases, yet progress in reducing cases has slowed or reversed, partly due to stagnating investments in global malaria control efforts.
The researchers anticipate that the hot and arid conditions due to climate change will lead to a general decline in areas conducive to malaria transmission from 2025 onward.
Their hydrology-driven method reveals that changes in malaria suitability vary across regions and are more responsive to future greenhouse gas emissions than previously believed.
For instance, forecasted decreases in malaria suitability in West Africa extend further eastward than models based solely on rainfall indicated, reaching as far as South Sudan. Conversely, projected increases in suitability in South Africa are now linked to watercourses like the Orange River.
Professor Chris Thomas, a co-author of the study from the University of Lincoln, highlighted, “The significant progress lies in these models considering that not all precipitation remains in situ, thereby expanding the areas where breeding conditions favorable for malaria mosquitoes occur, particularly along major river floodplains in the arid, savanna regions typical of many African regions. What’s striking in the new modeling is the impact of climate change on the length of seasons, which can profoundly affect disease transmission.”
Facilitating Water Modeling Experiments
Co-author Professor Simon Gosling, specializing in Climate Risks & Environmental Modeling at the University of Nottingham, contributed to coordinating the water modeling experiments for the study.
He stated, “Our research underscores the intricate manner in which changes in surface water flows influence malaria transmission risk across Africa. This was made feasible through a substantial research endeavor by the global hydrological modeling community, which compiled and provided estimates of climate change effects on water flows worldwide. Although a general reduction in future malaria risk may seem positive, it comes with the trade-off of diminished water availability and an increased risk of another significant disease, dengue.”
The researchers aim to further refine their models to capture finer details of waterbody dynamics, which could enhance national malaria control strategies.
Dr. Smith added, “We are nearing a stage where globally available data can not only identify potential habitats but also predict which mosquito species are likely to thrive in specific locations, enabling targeted interventions against these insects.”
Read the original article on: Phys Org
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