GIS and multiple-criteria evaluation for the optimisation of tsetse fly eradication programmes

Area of Science:

• Veterinary Entomology
• Environmental Management
• Geographic Information Systems

Background:

• Tsetse flies transmit trypanosomiasis, a disease impacting livestock and human populations across Africa.
• Tsetse fly control offers potential economic benefits through expanded livestock-keeping but poses environmental risks like habitat degradation and biodiversity loss.
• Integrated pest management strategies are crucial to balance disease control with ecological sustainability.

Purpose of the Study:

• To develop a decision support system integrating remote sensing and environmental data for effective tsetse fly control programming.
• To identify priority areas for tsetse control in Zambia, mitigating potential negative environmental consequences.
• To demonstrate the economic viability of integrated disease control over localized eradication efforts.

Main Methods:

• Development of a tree-based decision-support approach combined with Multiple-Criteria Evaluation (MCE).
• Utilisation of a Geographical Information System (GIS) to spatially analyse environmental data and target control efforts.
• Integration of remotely sensed data with other environmental variables for comprehensive risk and priority assessment.

Main Results:

• Clear differentiation of priority areas for tsetse control was achieved under various hypothetical scenarios.
• Specific regions, such as northwest of Petauke in Zambia's Eastern Province, were consistently identified as high-priority control zones.
• Analysis indicated that priority areas are not isolated, supporting the feasibility of integrated, rather than localized, control strategies.

Conclusions:

• A GIS-based decision support system effectively identifies optimal areas for tsetse control, balancing disease management with environmental considerations.
• Integrated tsetse control programs are likely more economically sustainable than eradication efforts, especially when targeting non-isolated populations.
• This methodology provides a framework for informed decision-making in tsetse control, minimizing adverse environmental impacts and maximizing socio-economic benefits.