Predicting the impact of insecticide-treated bed nets on malaria transmission: the devil is in the detail

BACKGROUND: Insecticide-treated bed nets (ITNs), including long-lasting insecticidal nets (LLINs), play a primary role in global campaigns to roll back malaria in tropical Africa. Effectiveness of treated nets depends on direct impacts on individual mosquitoes including killing and excite-repellency, which vary considerably among vector species due to variations in host-seeking behaviours. While monitoring and evaluation programmes of ITNs have focuses on morbidity and all-cause mortality in humans, local entomological context receives little attention. Without knowing the dynamics of local vector species and their responses to treated nets, it is difficult to predict clinical outcomes when ITN applications are scaled up across African continent. Sound model frameworks incorporating intricate interactions between mosquitoes and treated nets are needed to develop the predictive capacity for scale-up applications of ITNs. METHODS: An established agent-based model was extended to incorporate the direct outcomes, e.g. killing and avoidance, of individual mosquitoes exposing to ITNs in a hypothetical village setting with 50 houses and 90 aquatic habitats. Individual mosquitoes were tracked throughout the life cycle across the landscape. Four levels of coverage, i.e. 40, 60, 80 and 100%, were applied at the household level with treated houses having only one bed net. By using Latin hypercube sampling scheme, parameters governing killing, diverting and personal protection of net users were evaluated for their relative roles in containing mosquito populations, entomological inoculation rates (EIRs) and malaria incidence. RESULTS: There were substantial gaps in coverage between households and individual persons, and 100% household coverage resulted in circa 50% coverage of the population. The results show that applications of ITNs could give rise to varying impacts on population-level metrics depending on values of parameters governing interactions of mosquitoes and treated nets at the individual level. The most significant factor in determining effectiveness was killing capability of treated nets. Strong excito-repellent effect of impregnated nets might lead to higher risk exposure to non-bed net users. CONCLUSION: With variabilities of vector mosquitoes in host-seeking behaviours and the responses to treated nets, it is anticipated that scale-up applications of INTs might produce varying degrees of success dependent on local entomological and epidemiological contexts. This study highlights that increased ITN coverage led to significant reduction in risk exposure and malaria incidence only when treated nets yielded high killing effects. It is necessary to test efficacy of treated nets on local dominant vector mosquitoes, at least in laboratory, for monitoring and evaluation of ITN programmes.