A combined experimental-computational approach for spatial protection efficacy assessment of controlled release devices against mosquitoes (Anopheles)

This work describes the use of entomological studies combined with in silico models (computer simulations derived from numerical models) to assess the efficacy of a novel device for controlled release of spatial repellents. Controlled Release Devices (CRDs) were tested with different concentrations of metofluthrin and tested against An. quadrimaculatus mosquitoes using arm-in cage, semi-field, and outdoor studies. Arm-in-cage trials showed an approximate mean values for mosquito knockdown of 40% and mosquito bite reduction of 80% for the optimal metofluthrin formulation for a 15-minute trial. Semi-field outdoor studies showed a mean mortality of a 50% for 24 hour trial and 75% for a 48 hour trial for optimal concentrations. Outdoors studies showed an approximate mean mortality rate of 50% for a 24 hour trial for optimal concentrations. Numerical simulations based on Computational Fluid Dynamics (CFD) were performed in order to obtain spatial concentration profiles for 24 hour and 48 hour periods. Experimental results were correlated with simulation results in order to obtain a functional model that linked mosquito mortality with the estimated spatial concentration for a given period of time. Such correlation provides a powerful insight in predicting the effectiveness of the CRDs as a vector-control tool. While CRDs represent an alternative to current spatial repellent delivery methods, such as coils, candles, electric repellents, and passive emanators based on impregnated strips, the presented method can be applied to any spatial vector control treatment by correlating entomological endpoints, i.e. mortality, with in-silico simulations to predict overall efficacy. The presented work therefore presents a new methodology for improving design, development and deployment of vector-control tools to reduce transmission of vector-borne diseases, including malaria and dengue.