Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination

 

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Detalles Bibliográficos
Autores: Rhodes, Charlotte G., Loaiza, Jose R., Romero, Luis Mario, Gutiérrez Alvarado, José Manuel, Delgado, Gabriela, Rojas Salas, Obdulio, Ramírez Rojas, Melissa, Aguilar Avendaño, Carlos, Maynes, Ezequías, Valerín Cordero, José A., Soto Mora, Alonso, Rigg, Chystrie A., Zardkoohi, Aryana, Prado, Monica, Friberg, Mariel D., Bergmann, Luke R., Marín Rodríguez, Rodrigo, Hamer, Gabriel L., Fernando Chaves, Luis
Formato: artículo
Fecha de Publicación:2022
Descripción:In the absence of entomological information, tools for predicting Anopheles spp. presence can help evaluate the entomological risk of malaria transmission. Here, we illustrate how species distribution models (SDM) could quantify potential dominant vector species presence in malaria elimination settings. We fitted a 250 m resolution ensemble SDM for Anopheles albimanus Wiedemann. The ensemble SDM included predictions based on seven different algorithms, 110 occurrence records and 70 model projections. SDM covariates included nine environmental variables that were selected based on their importance from an original set of 28 layers that included remotely and spatially interpolated locally measured variables for the land surface of Costa Rica. Goodness of fit for the ensemble SDM was very high, with a minimum AUC of 0.79. We used the resulting ensemble SDM to evaluate differences in habitat suitability (HS) between commercial plantations and surrounding landscapes, finding a higher HS in pineapple and oil palm plantations, suggestive of An. albimanus presence, than in surrounding landscapes. The ensemble SDM suggested a low HS for An. albimanus at the presumed epicenter of malaria transmission during 2018–2019 in Costa Rica, yet this vector was likely present at the two main towns also affected by the epidemic. Our results illustrate how ensemble SDMs in malaria elimination settings can provide information that could help to improve vector surveillance and control.
País:Repositorio UNA
Institución:Universidad Nacional de Costa Rica
Repositorio:Repositorio UNA
Lenguaje:Inglés
OAI Identifier:oai:null:11056/25848
Acceso en línea:http://hdl.handle.net/11056/25848
https://doi.org/10.3390/insects13030221
Palabra clave:gold mining; Costa Rica; Plasmodium; vivax malaria; productive landscapes; oil palms; pineapples; plantationocene; Schmalhausen’s law
MALARIA
ENFERMEDADES INFECCIOSAS
INFECTIOUS DISEASES
PALMA ACEITERA
DIPTERA
COSTA RICA
OIL PALMS
PINEAPPLESS