Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival
Author(s)
Christiansen-Jucht, C
Erguler, K
Shek, CY
Basanez, M-G
Parham, PE
Type
Journal Article
Abstract
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.
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.
Date Issued
2015-05-28
Date Acceptance
2015-05-21
Citation
International Journal of Environmental Research and Public Health, 2015, 12 (6), pp.5975-6005
ISSN
1660-4601
Publisher
MDPI
Start Page
5975
End Page
6005
Journal / Book Title
International Journal of Environmental Research and Public Health
Volume
12
Issue
6
Copyright Statement
© 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/).
distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/4.0/).
License URL
Subjects
Science & Technology
Life Sciences & Biomedicine
Environmental Sciences
Environmental Sciences & Ecology
mathematical modelling
climate change
mosquito population dynamics
Anopheles gambiae s
s
senescence
malaria
vector-borne diseases
VECTOR-BORNE DISEASES
AEDES-AEGYPTI DIPTERA
MALARIA TRANSMISSION
CLIMATE-CHANGE
CONTROL INTERVENTIONS
MATHEMATICAL-MODELS
AQUATIC STAGES
HUMAN BLOOD
CULICIDAE
MOSQUITOS
Publication Status
Published