Background

Current vector control strategies focus largely on indoor measures, such as long-lasting insecticide treated nets (LLINs) and indoor residual spraying (IRS); however mosquitoes frequently feed on sugar sources outdoors, inviting the possibility of novel control strategies. Attractive toxic sugar baits (ATSB), either sprayed on vegetation or provided in outdoor bait stations, have been shown to significantly reduce mosquito densities in these settings.

Methods

Simple models of mosquito sugar-feeding behaviour were fitted to data from an ATSB field trial in Mali and used to estimate sugar-feeding rates and the potential of ATSB to control mosquito populations. The model and fitted parameters were then incorporated into a larger integrated vector management (IVM) model to assess the potential contribution of ATSB to future IVM programmes.

Results

In the Mali experimental setting, the model suggests that about half of female mosquitoes fed on ATSB solution per day, dying within several hours of ingesting the toxin. Using a model incorporating the number of gonotrophic cycles completed by female mosquitoes, a higher sugar-feeding rate was estimated for younger mosquitoes than for older mosquitoes. Extending this model to incorporate other vector control interventions suggests that an IVM programme based on both ATSB and LLINs may substantially reduce mosquito density and survival rates in this setting, thereby substantially reducing parasite transmission. This is predicted to exceed the impact of LLINs in combination with IRS provided ATSB feeding rates are 50% or more of Mali experimental levels. In addition, ATSB is predicted to be particularly effective against Anopheles arabiensis, which is relatively exophilic and therefore less affected by IRS and LLINs.

Conclusions

These results suggest that high coverage with a combination of LLINs and ATSB could result in substantial reductions in malaria transmission in this setting. Further field studies of ATSB in other settings are needed to assess the potential of ATSB as a component in future IVM malaria control strategies.

Background

Residual malaria transmission has been reported in many areas even with adequate indoor vector control coverage, such as long-lasting insecticidal nets (LLINs). The increased insecticide resistance in Anopheles mosquitoes has resulted in reduced efficacy of the widely used indoor tools and has been linked with an increase in outdoor malaria transmission. There are considerations of incorporating outdoor interventions into integrated vector management (IVM) to achieve malaria elimination; however, more information on the combination of tools for effective control is needed to determine their utilization.

Methods

A spatial individual-based model was modified to simulate the environment and malaria transmission activities in a hypothetical, isolated African village setting. LLINs and outdoor attractive toxic sugar bait (ATSB) stations were used as examples of indoor and outdoor interventions, respectively. Different interventions and lengths of efficacy periods were tested. Simulations continued for 420 days, and each simulation scenario was repeated 50 times. Mosquito populations, entomologic inoculation rates (EIRs), probabilities of local mosquito extinction, and proportion of time when the annual EIR was reduced below one were compared between different intervention types and efficacy periods.

Results

In the village setting with clustered houses, the combinational intervention of 50% LLINs plus outdoor ATSBs significantly reduced mosquito population and EIR in short term, increased the probability of local mosquito extinction, and increased the time when annual EIR is less than one per person compared to 50% LLINs alone; outdoor ATSBs alone significantly reduced mosquito population in short term, increased the probability of mosquito extinction, and increased the time when annual EIR is less than one compared to 50% LLINs alone, but there was no significant difference in EIR in short term between 50% LLINs and outdoor ATSBs. In the village setting with dispersed houses, the combinational intervention of 50% LLINs plus outdoor ATSBs significantly reduced mosquito population in short term, increased the probability of mosquito extinction, and increased the time when annual EIR is less than one per person compared to 50% LLINs alone; outdoor ATSBs alone significantly reduced mosquito population in short term, but there were no significant difference in the probability of mosquito extinction and the time when annual EIR is less than one between 50% LLIN and outdoor ATSBs; and there was no significant difference in EIR between all three interventions. A minimum of 2 months of efficacy period is needed to bring out the best possible effect of the vector control tools, and to achieve long-term mosquito reduction, a minimum of 3 months of efficacy period is needed.

Conclusions

The results highlight the value of incorporating outdoor vector control into IVM as a supplement to traditional indoor practices for malaria elimination in Africa, especially in village settings of clustered houses where LLINs alone is far from sufficient.

Background

The development of insecticide resistance and the increased outdoor-biting behaviour of malaria vectors reduce the efficiency of indoor vector control methods. Attractive toxic sugar baits (ATSBs), a method targeting the sugar-feeding behaviours of vectors both indoors and outdoors, is a promising supplement to indoor tools. The number and configuration of these ATSB stations needed for malaria control in a community needs to be determined.

Methods

A hypothetical village, typical of those in sub-Saharan Africa, 600 × 600 m, consisting of houses, humans and essential resource requirements of Anopheles gambiae (sugar sources, outdoor resting sites, larval habitats) was simulated in a spatial individual-based model. Resource-rich and resource-poor environments were simulated separately. Eight types of configurations and different densities of ATSB stations were tested. Anopheles gambiae population size, human biting rate (HBR) and entomological inoculation rates (EIR) were compared between different ATSB configurations and densities. Each simulated scenario was run 50 times.

Results

Compared to the outcomes not altered by ATSB treatment in the control scenario, in resource-rich and resource-poor environments, respectively, the optimum ATSB treatment reduced female abundance by 98.22 and 91.80 %, reduced HBR by 99.52 and 98.15 %, and reduced EIR by 99.99 and 100 %. In resource-rich environments, n × n grid design, stations at sugar sources, resting sites, larval habitats, and random locations worked better in reducing vector population and HBRs than other configurations (P < 0.0001). However, there was no significant difference of EIR reductions between all ATSB configurations (P > 0.05). In resource-poor environments, there was no significant difference of female abundances, HBRs and EIRs between all ATSB configurations (P > 0.05). The optimum number of ATSB stations was about 25 for resource-rich environments and nine for resource-poor environments.

Conclusions

ATSB treatment reduced An. gambiae population substantially and reduced EIR to near zero regardless of environmental resource availability. In resource-rich environments, dispersive configurations worked better in reducing vector population, and stations at or around houses worked better in preventing biting and parasite transmission. In resource-poor environments, all configurations worked similarly. Optimum numbers of bait stations should be adjusted according to seasonality when resource availability changes.

Background

Agent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour.

Methods

A spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared.

Results

When the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P < 0.01). Survival was greater when sugar sources were randomly distributed in the whole village compared to clustering around outdoor resting sites or houses.

Conclusions

Increases in densities of sugar sources or outdoor resting sites significantly increase the survival and human biting rates of An. gambiae mosquitoes. Survival of An. gambiae is more supported by random distribution of sugar sources than clustering of sugar sources around resting sites or houses. Density and spatial distribution of natural sugar sources and outdoor resting sites modulate vector populations and human biting rates, and thus malaria parasite transmission.