| Literature DB >> 33529565 |
Hélène Cecilia1, Sandie Arnoux1, Sébastien Picault1, Ahmadou Dicko2, Momar Talla Seck3, Baba Sall4, Mireille Bassène3, Marc Vreysen5, Soumaïla Pagabeleguem6,7, Augustin Bancé8, Jérémy Bouyer2,5,9, Pauline Ezanno1.
Abstract
Spatio-temporally heterogeneous environments may lead to unexpected population dynamics. Knowledge is needed on local properties favouring population resilience at large scale. For pathogen vectors, such as tsetse flies transmitting human and animal African trypanosomosis, this is crucial to target management strategies. We developed a mechanistic spatio-temporal model of the age-structured population dynamics of tsetse flies, parametrized with field and laboratory data. It accounts for density- and temperature-dependence. The studied environment is heterogeneous, fragmented and dispersal is suitability-driven. We confirmed that temperature and adult mortality have a strong impact on tsetse populations. When homogeneously increasing adult mortality, control was less effective and induced faster population recovery in the coldest and temperature-stable locations, creating refuges. To optimally select locations to control, we assessed the potential impact of treating them and their contribution to the whole population. This heterogeneous control induced a similar population decrease, with more dispersed individuals. Control efficacy was no longer related to temperature. Dispersal was responsible for refuges at the interface between controlled and uncontrolled zones, where resurgence after control was very high. The early identification of refuges, which could jeopardize control efforts, is crucial. We recommend baseline data collection to characterize the ecosystem before implementing any measures.Entities:
Keywords: disease vector; experimental and field data; mechanistic modelling; mortality scenario; spatio-temporal dynamics
Mesh:
Year: 2021 PMID: 33529565 PMCID: PMC7893214 DOI: 10.1098/rspb.2020.2810
Source DB: PubMed Journal: Proc Biol Sci ISSN: 0962-8452 Impact factor: 5.349