An agent-based model to simulate tsetse fly distribution and control techniques: a case study in Nguruman, Kenya

Area of Science:

• Vector-borne disease ecology
• Ecological modeling
• Parasitology

Background:

• African trypanosomiasis (sleeping sickness/nagana) is a significant vector-borne disease in Sub-Saharan Africa.
• Control strategies primarily target the tsetse fly vector (Glossina spp.).
• Accurate tsetse population and distribution models are crucial for effective control planning, but traditional methods are limited by sparse field data.

Purpose of the Study:

• To develop an Agent-Based Model (ABM) for predicting tsetse fly populations and distribution.
• To provide timing and location guidance for tsetse fly control interventions.
• To overcome limitations of traditional statistical models that require presence/absence data.

Main Methods:

• Developed an Agent-Based Model (ABM) driven by daily, remotely-sensed environmental data.
• The ABM links environmental changes to individual tsetse fly biology.
• The model analyzes various tsetse control methods, including insecticide spraying, animal population control, sterile insect release, and land use modification.

Main Results:

• The ABM provides timing and location information for tsetse fly control without requiring presence/absence training data.
• The model simulates tsetse populations with greater accuracy compared to traditional statistical models.
• It offers a flexible framework for assessing the impact of different control strategies.

Conclusions:

• The developed ABM is a bottom-up, process-based model utilizing freely available data.
• Its design allows for easy transferability to new geographical areas.
• The model serves as a valuable tool for enhancing tsetse fly control planning and implementation.