Using species distribution models to optimize vector control in the framework of the tsetse eradication campaign in Senegal
Author(s) -
Ahmadou Dicko,
Renaud Lancelot,
Momar Talla Seck,
Laure Guerrini,
Baba Sall,
Mbargou Lo,
Marc J. B. Vreysen,
Thierry Lefrançois,
William M. Fonta,
Steven L. Peck,
Jérémy Bouyer
Publication year - 2014
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1407773111
Subject(s) - vector (molecular biology) , vector control , distribution (mathematics) , tsetse fly , constraint (computer aided design) , sterile insect technique , control (management) , trypanosomiasis , geography , african trypanosomiasis , biology , pest analysis , ecology , computer science , engineering , mathematics , virology , voltage , recombinant dna , gene , mathematical analysis , induction motor , artificial intelligence , botany , electrical engineering , mechanical engineering , biochemistry
Tsetse flies are vectors of human and animal trypanosomoses in sub-Saharan Africa and are the target of the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). Glossina palpalis gambiensis (Diptera: Glossinidae) is a riverine species that is still present as an isolated metapopulation in the Niayes area of Senegal. It is targeted by a national eradication campaign combining a population reduction phase based on insecticide-treated targets (ITTs) and cattle and an eradication phase based on the sterile insect technique. In this study, we used species distribution models to optimize control operations. We compared the probability of the presence of G. p. gambiensis and habitat suitability using a regularized logistic regression and Maxent, respectively. Both models performed well, with an area under the curve of 0.89 and 0.92, respectively. Only the Maxent model predicted an expert-based classification of landscapes correctly. Maxent predictions were therefore used throughout the eradication campaign in the Niayes to make control operations more efficient in terms of deployment of ITTs, release density of sterile males, and location of monitoring traps used to assess program progress. We discuss how the models' results informed about the particular ecology of tsetse in the target area. Maxent predictions allowed optimizing efficiency and cost within our project, and might be useful for other tsetse control campaigns in the framework of the PATTEC and, more generally, other vector or insect pest control programs.
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