Ecological Niche Modeling of Aedes and Culex Mosquitoes: A Risk Map for Chikungunya and West Nile Viruses in Zambia

Abstract

The circulation of both West Nile Virus (WNV) and Chikungunya Virus (CHIKV) in humans and animals, coupled with a favorable tropical climate for mosquito proliferation in Zambia, call for the need for a better understanding of the ecological and epidemiological factors that govern their transmission dynamics in this region. This study aimed to examine the contribution of climatic variables to the distribution of Culex and Aedes mosquito species, which are potential vectors of CHIKV, WNV, and other arboviruses of public-health concern. Mosquitoes collected from Lusaka as well as from the Central and Southern provinces of Zambia were sorted by species within the Culex and Aedes genera, both of which have the potential to transmit viruses. The MaxEnt software was utilized to predict areas at risk of WNV and CHIKV based on the occurrence data on mosquitoes and environmental covariates. The model predictions show three distinct spatial hotspots, ranging from the high-probability regions to the medium- and low-probability regions. Regions along Lake Kariba, the Kafue River, and the Luangwa Rivers, as well as along the Mumbwa, Chibombo, Kapiri Mposhi, and Mpika districts were predicted to be suitable habitats for both species. The rainfall and temperature extremes were the most contributing variables in the predictive models.

Keywords: Aedes; Chikungunya virus; Culex; West Nile virus; Zambia; arbovirus; ecological niche modeling.

Figure 1

Map of Zambia showing locations of Culex and Aedes occurrence records included in MaxEnt modeling. The red and green dots represent the Culex and Aedes species, respectively. The overlap of red and green points indicates that both species were captured in the location. The yellow, dark blue, and light blue colors represent the sampling areas.

Figure 2

ROC curves for MaxEnt Aedes (A) and Culex (B) models’ performance (red line: training and testing data; blue line: standard deviation; and black line: random prediction). The AUC had values of 0.761 and 0.821 for Aedes and Culex, respectively.

Figure 3

Jackknife of test gain for Aedes (A) and Culex (B). The blue bars show the effect of each variable on the model by itself, while the light blue bars show the effect in the model when this variable is not considered. The red bar represents the performance of the model when all variables are included in the model.

Figure 4

Potential probability distribution of Aedes (A) and Culex (B) species in Zambia. Areas of high suitability are represented by the orange color through the light yellow color and less suitable areas are represented by the green color.

Figure 5

The effect of each environmental variable that most contributes to the suitability habitat of Aedes species when the remaining variables are configured to their average value. (A): BIO 18, precipitation of the warmest quarter, for which the units are millimeters of precipitation; (B): BIO 17, precipitation of the driest quarter, for which the units are millimeters of precipitation; and (C): BIO 4, temperature seasonality, for which the units are degrees Celsius by 10.

Figure 6

Shows the effect of each environmental variable that most contributes to the suitability habitat of Culex species when the remaining variables are configured to their average value. (A): BIO 18, precipitation of the warmest quarter, for which the units are millimeters of precipitation; (B): BIO 4, temperature seasonality, for which the units are degrees Celsius by 10; (C): elevation, for which X-axis units are millimeters above sea level; and (D): BIO 16, precipitation of wettest quarter (BIO 16), for which the units are millimeters of precipitation.