Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disea...

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Main Authors:	Christiansen-Jucht, Céline, Erguler, Kamil, Shek, Chee Yan, Basáñez, María-Gloria, Parham, Paul E.
Format:	Online
Language:	English
Published:	MDPI 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4483682/

id	pubmed-4483682
recordtype	oai_dc
spelling	pubmed-44836822015-06-30 Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival Christiansen-Jucht, Céline Erguler, Kamil Shek, Chee Yan Basáñez, María-Gloria Parham, Paul E. Article Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors. MDPI 2015-05-28 2015-06 /pmc/articles/PMC4483682/ /pubmed/26030468 http://dx.doi.org/10.3390/ijerph120605975 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Christiansen-Jucht, Céline Erguler, Kamil Shek, Chee Yan Basáñez, María-Gloria Parham, Paul E.
spellingShingle	Christiansen-Jucht, Céline Erguler, Kamil Shek, Chee Yan Basáñez, María-Gloria Parham, Paul E. Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
author_facet	Christiansen-Jucht, Céline Erguler, Kamil Shek, Chee Yan Basáñez, María-Gloria Parham, Paul E.
author_sort	Christiansen-Jucht, Céline
title	Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
title_short	Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
title_full	Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
title_fullStr	Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
title_full_unstemmed	Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
title_sort	modelling anopheles gambiae s.s. population dynamics with temperature- and age-dependent survival
description	Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors.
publisher	MDPI
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4483682/
_version_	1613241231303770112

Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

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