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Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation

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Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation. / Sedda, Luigi; Taylor, Benjamin; Eiras, Álvaro Eduardo et al.
In: Acta Tropica, Vol. 208, 105519, 19.05.2020.

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Sedda L, Taylor B, Eiras ÁE, Marques JT, Dillon R. Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation. Acta Tropica. 2020 May 19;208:105519. Epub 2020 May 8. doi: 10.1016/j.actatropica.2020.105519

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Sedda, Luigi ; Taylor, Benjamin ; Eiras, Álvaro Eduardo et al. / Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation. In: Acta Tropica. 2020 ; Vol. 208.

Bibtex

@article{ce589fbfe0f84c52b878334a936348ac,
title = "Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation",
abstract = "Understanding geographic population dynamics of mosquitoes is an essential requirement for estimating the risk of mosquito-borne disease transmission and geographically targeted interventions. However, the use of population dynamics measures, such as the intrinsic growth rate, as predictors in spatio-temporal point processes has not been investigated before. In this work we compared the predictive accuracy of four spatio-temporal log-Gaussian Cox models: (i) With no predictors; (ii) mosquito abundance as predictor; (iii) intrinsic growth rate as predictor; (iv) intrinsic growth rate and mosquito abundance as predictors. This analysis is based on Aedes aegypti mosquito surveillance and human dengue data obtained from the urban area of Caratinga, Brazil. We used a statistical Moran Curve approach to estimate the intrinsic growth rate and a zero inflated Poisson kriging model for estimating mosquito abundance at locations of dengue cases. The incidence of dengue cases was positively associated with mosquito intrinsic growth rate and this model outperformed, in terms of predictive accuracy, the abundance and the null models. The latter includes only the spatio-temporal random effect but no predictors. In the light of these results we suggest that the intrinsic growth rate should be investigated further as a potential tool for predicting the risk of dengue transmission and targeting health interventions for vector-borne diseases.",
keywords = "Moran curve, Ricker model, Density dependent and independent mortalities, Log-Gaussian cox process, Dengue, Aedes aegypti",
author = "Luigi Sedda and Benjamin Taylor and Eiras, {{\'A}lvaro Eduardo} and Marques, {Jo{\~a}o Trindade} and Rod Dillon",
year = "2020",
month = may,
day = "19",
doi = "10.1016/j.actatropica.2020.105519",
language = "English",
volume = "208",
journal = "Acta Tropica",
issn = "0001-706X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation

AU - Sedda, Luigi

AU - Taylor, Benjamin

AU - Eiras, Álvaro Eduardo

AU - Marques, João Trindade

AU - Dillon, Rod

PY - 2020/5/19

Y1 - 2020/5/19

N2 - Understanding geographic population dynamics of mosquitoes is an essential requirement for estimating the risk of mosquito-borne disease transmission and geographically targeted interventions. However, the use of population dynamics measures, such as the intrinsic growth rate, as predictors in spatio-temporal point processes has not been investigated before. In this work we compared the predictive accuracy of four spatio-temporal log-Gaussian Cox models: (i) With no predictors; (ii) mosquito abundance as predictor; (iii) intrinsic growth rate as predictor; (iv) intrinsic growth rate and mosquito abundance as predictors. This analysis is based on Aedes aegypti mosquito surveillance and human dengue data obtained from the urban area of Caratinga, Brazil. We used a statistical Moran Curve approach to estimate the intrinsic growth rate and a zero inflated Poisson kriging model for estimating mosquito abundance at locations of dengue cases. The incidence of dengue cases was positively associated with mosquito intrinsic growth rate and this model outperformed, in terms of predictive accuracy, the abundance and the null models. The latter includes only the spatio-temporal random effect but no predictors. In the light of these results we suggest that the intrinsic growth rate should be investigated further as a potential tool for predicting the risk of dengue transmission and targeting health interventions for vector-borne diseases.

AB - Understanding geographic population dynamics of mosquitoes is an essential requirement for estimating the risk of mosquito-borne disease transmission and geographically targeted interventions. However, the use of population dynamics measures, such as the intrinsic growth rate, as predictors in spatio-temporal point processes has not been investigated before. In this work we compared the predictive accuracy of four spatio-temporal log-Gaussian Cox models: (i) With no predictors; (ii) mosquito abundance as predictor; (iii) intrinsic growth rate as predictor; (iv) intrinsic growth rate and mosquito abundance as predictors. This analysis is based on Aedes aegypti mosquito surveillance and human dengue data obtained from the urban area of Caratinga, Brazil. We used a statistical Moran Curve approach to estimate the intrinsic growth rate and a zero inflated Poisson kriging model for estimating mosquito abundance at locations of dengue cases. The incidence of dengue cases was positively associated with mosquito intrinsic growth rate and this model outperformed, in terms of predictive accuracy, the abundance and the null models. The latter includes only the spatio-temporal random effect but no predictors. In the light of these results we suggest that the intrinsic growth rate should be investigated further as a potential tool for predicting the risk of dengue transmission and targeting health interventions for vector-borne diseases.

KW - Moran curve

KW - Ricker model

KW - Density dependent and independent mortalities

KW - Log-Gaussian cox process

KW - Dengue

KW - Aedes aegypti

U2 - 10.1016/j.actatropica.2020.105519

DO - 10.1016/j.actatropica.2020.105519

M3 - Journal article

VL - 208

JO - Acta Tropica

JF - Acta Tropica

SN - 0001-706X

M1 - 105519

ER -