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

Strategies 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 spat...

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Main Authors: Daniel A M Villela, Claudia T Codeço, Felipe Figueiredo, Gabriela A Garcia, Rafael Maciel-de-Freitas, Claudio J Struchiner
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4408040?pdf=render
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spelling doaj-af3abd28579d490781e1fc6c6eda2fed2020-11-24T21:23:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01104e012379410.1371/journal.pone.0123794A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.Daniel A M VillelaClaudia T CodeçoFelipe FigueiredoGabriela A GarciaRafael Maciel-de-FreitasClaudio J StruchinerStrategies 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.http://europepmc.org/articles/PMC4408040?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Daniel A M Villela
Claudia T Codeço
Felipe Figueiredo
Gabriela A Garcia
Rafael Maciel-de-Freitas
Claudio J Struchiner
spellingShingle Daniel A M Villela
Claudia T Codeço
Felipe Figueiredo
Gabriela A Garcia
Rafael Maciel-de-Freitas
Claudio J Struchiner
A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
PLoS ONE
author_facet Daniel A M Villela
Claudia T Codeço
Felipe Figueiredo
Gabriela A Garcia
Rafael Maciel-de-Freitas
Claudio J Struchiner
author_sort Daniel A M Villela
title A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
title_short A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
title_full A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
title_fullStr A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
title_full_unstemmed A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
title_sort bayesian hierarchical model for estimation of abundance and spatial density of aedes aegypti.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description Strategies 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.
url http://europepmc.org/articles/PMC4408040?pdf=render
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