Climate Change and Risk Projection: Dynamic Spatial Models of Tsetse and African Trypanosomiasis in Kenya.

Area of Science:

• Parasitology
• Vector-borne diseases
• Climate change impact on disease ecology

Background:

• African trypanosomiasis (sleeping sickness/nagana) is transmitted by tsetse flies across Africa.
• Current control efforts are challenged by dynamic vector distribution and climate change.
• Tsetse flies are predicted to expand into new areas due to climate change.

Purpose of the Study:

• To develop and present the ATcast modeling framework for predicting tsetse fly populations.
• To forecast potential exposure to tsetse flies and associated diseases in Kenya.
• To inform future public health interventions and planning.

Main Methods:

• Integrated a dynamically downscaled regional climate model with a species distribution model.
• Modeled spatio-temporal tsetse populations.
• Combined model outputs with Kenyan population data for exposure assessment.

Main Results:

• Predicted tsetse fly exposure potential across Kenya for 2050-2059.
• Identified areas at risk of increased tsetse fly presence and disease transmission.
• Highlighted the need for proactive disease management strategies.

Conclusions:

• The ATcast model provides a robust tool for predicting tsetse fly distribution under climate change.
• Anticipated changes in tsetse populations pose a significant risk to unprepared Kenyan populations.
• Integrated modeling approaches are crucial for effective vector-borne disease control.