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

Authored by Shengpan Lin, Mark H DeVisser, Joseph P Messina

Date Published: 2015

DOI: 10.1016/j.ecolmodel.2015.07.015

Sponsors: United States National Institutes of Health (NIH) United States Agency for International Development

Platforms: NetLogo

Model Documentation: ODD Flow charts

Model Code URLs: Model code not found

Abstract

Background: African trypanosomiasis, also known as ``sleeping sickness{''} in humans and ``nagana{''} in livestock is an important vector-borne disease in Sub-Saharan Africa. Control of trypanosomiasis has focused on eliminating the vector, the tsetse fly (Glossina, spp.). Effective tsetse fly control planning requires models to predict tsetse population and distribution changes over time and space. Traditional planning models have used statistical tools to predict tsetse distributions and have been hindered by limited field survey data. Methodology/results: We developed an Agent-Based Model (ABM) to provide timing and location information for tsetse fly control without presence/absence training data. The model is driven by daily remotely-sensed environment data. The model provides a flexible tool linking environmental changes with individual biology to analyze tsetse control methods such as aerial insecticide spraying, wild animal control, releasing irradiated sterile tsetse males, and land use and cover modification. Significance: This is a bottom-up process-based model with freely available data as inputs that can be easily transferred to a new area. The tsetse population simulation more closely approximates real conditions than those using traditional statistical models making it a useful tool in tsetse fly control planning. (C) 2015 Elsevier B.V. All rights reserved.

Tags

behavior cattle movement sleeping sickness Populations Protocol African trypanosomiasis Glossinidae Diptera Flies