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Endemic and zoonotic cycles of cutaneous leishmaniasis depend on vector feeding preferences: An epidemiological model
Gerardo Martín1, Edgar J González2, Elsy Nallelli Loría-Cervera3
1Departamento de Sistemas y Procesos Naturales, Escuela Nacional de Estudios Superiores unidad Mérida, Universidad Nacional Autónoma de México, Mérida, México.
Introduction:
Cutaneous leishmaniasis (CL) is a neglected tropical disease caused by Leishmania spp. parasites. It poses significant public health challenges among economically marginalized communities in endemic regions like Southeastern Mexico. Here, we developed a mathematical model to describe the transmission dynamics of CL in the Yucatan Peninsula region, focusing on two key sand fly vectors: Lutzomyia cruciata and Bichromomyia olmeca.
Methods:
Transmission was modelled as frequency dependent with Susceptible-Infected dynamics for vectors and rodents, and Susceptible-Exposed-Infected-Susceptible for humans, and accounts for the impact of available blood meals on vector populations. The model was parameterized from published literature for vector and reservoir growth rates and carrying capacities, transmission efficiency, and vector feeding preferences.
Result:
The simulations highlight the importance of both vector species in CL transmission, with Lu. cruciata showing a higher preference for human blood, while Bi. olmeca is more frequently associated with rodents. Sensitivity and scenario analyses reveal that the system is highly sensitive to transmission rates and vector feeding preferences, suggesting that Bi. olmeca is necessary to maintain infection among reservoirs, while Lu. cruciata contributes to zoonotic transmission.
Conclusions:
Overall, we emphasize that vector species have different roles on leishmaniasis epidemiology due to feeding preferences. Therefore, roviding funding to improve basic knowledge into the epidemiology of this disease, will improve our understanding of its dynamics. Once achieved, policymakers can develop targeted interventions to reduce CL incidence in affected regions to improve the outcomes of public health interventions.
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