Model stimulations to estimate malaria risk under climate change

Area of Science:

• Medical Entomology
• Epidemiology
• Climate Science

Background:

• Malaria's current geographic range is smaller than its potential, with some areas exhibiting "Anophelism without malaria" despite vector presence.
• Vectorial capacity is a key parameter for estimating malaria susceptibility, but a dynamic approach may offer better predictions.

Purpose of the Study:

• To utilize a dynamic concept of vectorial capacity with global climatological data as a risk indicator for malaria distribution.
• To assess the impact of temperature increases on malaria epidemic potential, particularly in regions with existing vectors but limited parasite development.

Main Methods:

• Global climatological data were used to compute a dynamic vectorial capacity.
• Sensitivity analysis was performed in three distinct geographic areas to evaluate changes in epidemic potential due to temperature increases.
• Climate scenarios were employed to predict future malaria risk.

Main Results:

• Dynamic vectorial capacity effectively predicts the current extent and distribution of malarious regions globally.
• Areas with the largest increase in epidemic potential under rising temperatures are those where mosquitoes are present but parasite development is temperature-limited.
• A 2-4 degrees C temperature increase is predicted to elevate malaria risk in bordering regions and higher altitudes within endemic zones.

Conclusions:

• Dynamic vectorial capacity serves as a valuable comparative risk indicator for malaria.
• Climate change, specifically rising temperatures, is projected to expand malaria risk into new areas and higher altitudes.
• Understanding these dynamics is crucial for predicting and managing future malaria distribution.