A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti

dc.creatorVillela, Daniel A. M.
dc.creatorCodeço, Claudia T.
dc.creatorFigueiredo, Felipe
dc.creatorGarcia, Gabriela A.
dc.creatorFreitas, Rafael Maciel de
dc.creatorStruchiner, Claudio J.
dc.date2016-02-11T12:51:58Z
dc.date2016-02-11T12:51:58Z
dc.date2015
dc.date.accessioned2023-09-26T20:48:01Z
dc.date.available2023-09-26T20:48:01Z
dc.identifierVILLELA, Daniel A. M. et al. A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti. Plos One, v. 10, n. 4, p. 1-17, Apr. 2015.
dc.identifier1932-6203
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/12713
dc.identifier10.1371/journal.pone.0123794
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8864119
dc.descriptionStrategies to minimize dengue transmission commonly rely on vector control, which aims to maintain Ae. aegypti density below a theoretical threshold. Mosquito abundance is traditionally estimated from mark-release-recapture (MRR) experiments, which lack proper analysis regarding accurate vector spatial distribution and population density. Recently proposed strategies to control vector-borne diseases involve replacing the susceptible wild population by genetically modified individuals’ refractory to the infection by the pathogen. Accurate measurements of mosquito abundance in time and space are required to optimize the success of such interventions. In this paper, we present a hierarchical probabilistic model for the estimation of population abundance and spatial distribution from typical mosquito MRR experiments, with direct application to the planning of these new control strategies. We perform a Bayesian analysis using the model and data from two MRR experiments performed in a neighborhood of Rio de Janeiro, Brazil, during both low- and high-dengue transmission seasons. The hierarchical model indicates that mosquito spatial distribution is clustered during the winter (0.99 mosquitoes/premise 95% CI: 0.80–1.23) and more homogeneous during the high abundance period (5.2 mosquitoes/premise 95% CI: 4.3–5.9). The hierarchical model also performed better than the commonly used Fisher-Ford’s method, when using simulated data. The proposed model provides a formal treatment of the sources of uncertainty associated with the estimation of mosquito abundance imposed by the sampling design. Our approach is useful in strategies such as population suppression or the displacement of wild vector populations by refractory Wolbachia-infected mosquitoes, since the invasion dynamics have been shown to follow threshold conditions dictated by mosquito abundance. The presence of spatially distributed abundance hotspots is also formally addressed under this modeling framework and its knowledge deemed crucial to predict the fate of transmission control strategies based on the replacement of vector populations.
dc.formatapplication/pdf
dc.languageeng
dc.publisherPublic Library of Science
dc.rightsopen access
dc.subjectAedes aegypti
dc.subjectDengue
dc.subjectBayesian Hierarchical Model
dc.subjectAedes
dc.subjectDengue
dc.subjectTeorema de Bayes
dc.titleA Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti
dc.typeArticle


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