The potential of attractive insecticide-treated nets (ITNs) in reducing malaria transmission: a modeling study

Recent studies suggest that insecticide-treated nets (ITNs) may actively attract malaria vectors, increasing their likelihood of coming into contact with the insecticide while potentially reducing personal protection. The impact of such attractive ITN on malaria transmission at the community level remains unclear. In this study, we developed a model to compare the effectiveness of attractive, inert and deterrent ITNs under varying levels of human usage and different degrees of physiological or behavioral resistance to insecticides in malaria vectors. We developed a model to simulate the host-seeking, feeding and mortality (HSFM) of mosquito vectors facing ITNs. This model allows mosquitoes to choose between two rooms based on the presence and remote influence (attractive, inert or deterrent) of ITNs. The HSFM model was then integrated into a malaria transmission model to compare the Plasmodium transmission potential of mosquitoes exposed to these different type of ITNs under various scenarios of ITN coverage, physiological resistance, quantitative behavioral resistance, and qualitative behavioral resistance. The model predicts that attractive ITNs consistently reduce malaria transmission potential of vectors more effectively than inert or deterrent ITNs, even in the presence of resistant vector phenotypes. For instance, at intermediate use rate (50%), strongly attractive ITNs are expected to reduce transmission by up to 67% compared to deterrent ITNs. In resistant vector populations, attractive ITNs remained more effective overall, though the reduction in transmission were less pronounced. Our findings suggest that both inert and attractive ITNs could enhance malaria control efforts, outperforming current deterrent ITNs, even in resistant vector populations. Shifting from deterrent to inert or attractive ITNs could significantly improve vector control strategies, warranting further research and product development to fully explore and optimize this approach.