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

Christiansen-Jucht C, Erguler K, Shek CY, Basáñez MG, Parham PE - Int J Environ Res Public Health (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Infectious Disease Epidemiology, Faculty of Medicine, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London W2 1PG, UK. celine.jucht@imperial.ac.uk.

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.

No MeSH data available.


Related in: MedlinePlus

Fit of constant- (blue lines) and time (age) dependent (red lines) hazard functions to the laboratory mortality data in [34] at 27 °C (a,c) and 31 °C (b,d). Here, (a,b) are for larvae, while (c,d) are for adults. The constant hazard corresponds to the exponential model, whilst the age-dependent hazard corresponds to the gamma distribution of survival times.
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ijerph-12-05975-f006: Fit of constant- (blue lines) and time (age) dependent (red lines) hazard functions to the laboratory mortality data in [34] at 27 °C (a,c) and 31 °C (b,d). Here, (a,b) are for larvae, while (c,d) are for adults. The constant hazard corresponds to the exponential model, whilst the age-dependent hazard corresponds to the gamma distribution of survival times.

Mentions: A constant (time-independent) hazard rate, derived from the exponential model fit of S(t) to the survival data in [34], was fitted to the laboratory mortality data (Figure 5 and Figure 6, blue lines). In addition, the temperature dependence of the hazard functions μLc and μAc was plotted and a functional form fitted (Figure 7 and Table 2) to obtain the larval and adult age-independent mortality rates (μLc and μAc respectively). In order to model more realistically age-dependent mortality, the gamma distribution was fitted to the laboratory survival data in [34] (Figure 5 and Figure 6, red lines).


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

Christiansen-Jucht C, Erguler K, Shek CY, Basáñez MG, Parham PE - Int J Environ Res Public Health (2015)

Fit of constant- (blue lines) and time (age) dependent (red lines) hazard functions to the laboratory mortality data in [34] at 27 °C (a,c) and 31 °C (b,d). Here, (a,b) are for larvae, while (c,d) are for adults. The constant hazard corresponds to the exponential model, whilst the age-dependent hazard corresponds to the gamma distribution of survival times.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4483682&req=5

ijerph-12-05975-f006: Fit of constant- (blue lines) and time (age) dependent (red lines) hazard functions to the laboratory mortality data in [34] at 27 °C (a,c) and 31 °C (b,d). Here, (a,b) are for larvae, while (c,d) are for adults. The constant hazard corresponds to the exponential model, whilst the age-dependent hazard corresponds to the gamma distribution of survival times.
Mentions: A constant (time-independent) hazard rate, derived from the exponential model fit of S(t) to the survival data in [34], was fitted to the laboratory mortality data (Figure 5 and Figure 6, blue lines). In addition, the temperature dependence of the hazard functions μLc and μAc was plotted and a functional form fitted (Figure 7 and Table 2) to obtain the larval and adult age-independent mortality rates (μLc and μAc respectively). In order to model more realistically age-dependent mortality, the gamma distribution was fitted to the laboratory survival data in [34] (Figure 5 and Figure 6, red lines).

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Infectious Disease Epidemiology, Faculty of Medicine, School of Public Health, Imperial College London St Mary's Campus, Norfolk Place, London W2 1PG, UK. celine.jucht@imperial.ac.uk.

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.

No MeSH data available.


Related in: MedlinePlus