Modelling the influence of temperature and rainfall on the population dynamics of Anopheles arabiensis

Abstract

Background: Malaria continues to be one of the most devastating diseases in the world, killing more humans than any other infectious disease. Malaria parasites are entirely dependent on Anopheles mosquitoes for transmission. For this reason, vector population dynamics is a crucial determinant of malaria risk. Consequently, it is important to understand the biology of malaria vector mosquitoes in the study of malaria transmission. Temperature and precipitation also play a significant role in both aquatic and adult stages of the Anopheles.

Methods: In this study, a climate-based, ordinary-differential-equation model is developed to analyse how temperature and the availability of water affect mosquito population size. In the model, the influence of ambient temperature on the development and the mortality rate of Anopheles arabiensis is considered over a region in KwaZulu-Natal Province, South Africa. In particular, the model is used to examine the impact of climatic factors on the gonotrophic cycle and the dynamics of mosquito population over the study region.

Results: The results fairly accurately quantify the seasonality of the population of An. arabiensis over the region and also demonstrate the influence of climatic factors on the vector population dynamics. The model simulates the population dynamics of both immature and adult An. arabiensis. The simulated larval density produces a curve which is similar to observed data obtained from another study.

Conclusion: The model is efficiently developed to predict An. arabiensis population dynamics, and to assess the efficiency of various control strategies. In addition, the model framework is built to accommodate human population dynamics with the ability to predict malaria incidence in future.

Keywords: Anopheles arabiensis; Mathematical model; Population dynamics; Rainfall; Temperature.

Fig. 1

Map showing the location of Dondotha in KwaZulu-Natal Province. Source: GIS unit of the Medical Research Council of South Africa

Fig. 2

Daily rainfall over calibration period. Showing the daily rainfall of the study area; Dondotha village in KwaZulu Natal Province, South Africa between January 2002 and December 2004

Fig. 3

Daily mean temperature over calibration period. Showing the daily mean temperature of the study area; Dondotha village in KwaZulu Natal Province, South Africa between January 2002 and December 2004

Fig. 4

Flow diagram of mosquito population model

Fig. 5

Parameter estimates and curves fit for a larvae development rate, b larvae mortality rate of An. arabiensis. see Additional file 1 for other parameters

Fig. 6

Model validation and climate monthly data of New Halfa town, eastern Sudan. a Monthly rainfall, b mean monthly temperature, and (c) showing the simulated and observed collected larvae over the study area and period

Fig. 7

Model sensitivity to parameters. This highlights the sensitivity of the model to parameters when a ρ_Ah = 0.3, b ρ_Ah = 0.5, and c ρ_Ah = 0.9. See main text for details

Fig. 8

Sensitivity of aquatic-stage mosquito population dynamics to temperature. Effect of constant temperature on a eggs, b larvae, and c pupa of An. arabiensis

Fig. 9

Sensitivity of adult mosquito population dynamics to temperature. Effect of constant temperature on adult An. arabiensis a searching for host, b resting, and c searching for oviposition site

Fig. 10

Simulated population of immature An. arabiensis. Simulations of a eggs, b larvae, and c pupae population dynamics with climate variables

Fig. 11

Simulated population of adult An. arabiensis. Simulations of adult mosquitoes a searching for mating, b searching for host, c resting, and d searching for oviposition site with climate variables

Fig. 12

Spatial distribution of temperature and oviposition rate over South Africa. This highlights the spatial distribution of A observed temperature, and B simulated oviposition rate over South Africa