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Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination
SIMPLE SUMMARY: Costa Rica is near malaria elimination. However, sporadic outbreaks still occur, and while control strategies have been focused on delivering efficient treatments for infected patients, an open question is whether control measures targeting the dominant vector, Anopheles albimanus, a...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955261/ https://www.ncbi.nlm.nih.gov/pubmed/35323519 http://dx.doi.org/10.3390/insects13030221 |
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author | 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. Chaves, Luis Fernando |
author_facet | 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. Chaves, Luis Fernando |
author_sort | Rhodes, Charlotte G. |
collection | PubMed |
description | SIMPLE SUMMARY: Costa Rica is near malaria elimination. However, sporadic outbreaks still occur, and while control strategies have been focused on delivering efficient treatments for infected patients, an open question is whether control measures targeting the dominant vector, Anopheles albimanus, are appropriately designed given their ecology and distribution. Here, we illustrate the use of an ensemble species distribution model (SDM) as a tool to assess the potential exposure to An. albimanus in palm and pineapple plantations, and to also assess the potential involvement of this mosquito vector in transmission foci where entomological surveillance is not feasible. We found that both oil palm and pineapple plantations are very likely to harbor An. albimanus. By contrast, environments at the Crucitas open-pit gold mine, the epicenter of malaria transmission in 2018 and 2019, have low suitability for this mosquito species. Our results suggest that medium to high resolution SDMs can be used to plan vector control activities. Finally, we discuss the high suitability of oil palm and pineapple plantations for An. albimanus in reference to recently developed social science theory about the Plantationocene. ABSTRACT: 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. |
format | Online Article Text |
id | pubmed-8955261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89552612022-03-26 Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination 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. Chaves, Luis Fernando Insects Article SIMPLE SUMMARY: Costa Rica is near malaria elimination. However, sporadic outbreaks still occur, and while control strategies have been focused on delivering efficient treatments for infected patients, an open question is whether control measures targeting the dominant vector, Anopheles albimanus, are appropriately designed given their ecology and distribution. Here, we illustrate the use of an ensemble species distribution model (SDM) as a tool to assess the potential exposure to An. albimanus in palm and pineapple plantations, and to also assess the potential involvement of this mosquito vector in transmission foci where entomological surveillance is not feasible. We found that both oil palm and pineapple plantations are very likely to harbor An. albimanus. By contrast, environments at the Crucitas open-pit gold mine, the epicenter of malaria transmission in 2018 and 2019, have low suitability for this mosquito species. Our results suggest that medium to high resolution SDMs can be used to plan vector control activities. Finally, we discuss the high suitability of oil palm and pineapple plantations for An. albimanus in reference to recently developed social science theory about the Plantationocene. ABSTRACT: 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. MDPI 2022-02-22 /pmc/articles/PMC8955261/ /pubmed/35323519 http://dx.doi.org/10.3390/insects13030221 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article 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. Chaves, Luis Fernando Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination |
title | Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination |
title_full | Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination |
title_fullStr | Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination |
title_full_unstemmed | Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination |
title_short | Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination |
title_sort | anopheles albimanus (diptera: culicidae) ensemble distribution modeling: applications for malaria elimination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955261/ https://www.ncbi.nlm.nih.gov/pubmed/35323519 http://dx.doi.org/10.3390/insects13030221 |
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