The effective population size of malaria mosquitoes: large impact of vector control

Abstract

Malaria vectors in sub-Saharan Africa have proven themselves very difficult adversaries in the global struggle against malaria. Decades of anti-vector interventions have yielded mixed results--with successful reductions in transmission in some areas and limited impacts in others. These varying successes can be ascribed to a lack of universally effective vector control tools, as well as the development of insecticide resistance in mosquito populations. Understanding the impact of vector control on mosquito populations is crucial for planning new interventions and evaluating existing ones. However, estimates of population size changes in response to control efforts are often inaccurate because of limitations and biases in collection methods. Attempts to evaluate the impact of vector control on mosquito effective population size (N(e)) have produced inconclusive results thus far. Therefore, we obtained data for 13-15 microsatellite markers for more than 1,500 mosquitoes representing multiple time points for seven populations of three important vector species--Anopheles gambiae, An. melas, and An. moucheti--in Equatorial Guinea. These populations were exposed to indoor residual spraying or long-lasting insecticidal nets in recent years. For comparison, we also analyzed data from two populations that have no history of organized vector control. We used Approximate Bayesian Computation to reconstruct their demographic history, allowing us to evaluate the impact of these interventions on the effective population size. In six of the seven study populations, vector control had a dramatic impact on the effective population size, reducing N(e) between 55%-87%, the exception being a single An. melas population. In contrast, the two negative control populations did not experience a reduction in effective population size. This study is the first to conclusively link anti-vector intervention programs in Africa to sharply reduced effective population sizes of malaria vectors.

Figure 1. A map indicating the seven study sites in Equatorial Guinea.

Two locations were sampled on Bioko Island and five locations on mainland Equatorial Guinea. Additionally, two negative control populations; Tiko in Cameroon and Fanzana in Mali were included in our study.

Figure 2. Density plots of effective population size estimates.

Posterior density plots of estimated N_e from ABC analysis for the seven study populations A) Punta Europa, B) Ukomba, C) Mongomo, D)Yengue, E) Niefang, F) Arena Blanca and G) Cogo. Solid line depicts the post-intervention N_e, whereas the dashed line corresponds to the pre-intervention N_e.

Figure 3. Density plots of effective population size estimates and time of population size change.

Posterior density plots of estimated N_e from the ABC analysis of the two negative control populations, Tiko, Cameroon (3A) and Fanzana, Mali (3B).