Transmission dynamics of lymphatic filariasis: vector‐specific density dependence in the development of Wuchereria bancrofti infective larvae in mosquitoes

Abstract The principles of meta‐analysis developed in a previous study were extended to investigate the process of Wuchereria bancrofti (Cobbold) (Filarioidea: Onchocercidae) infection in mosquito (Diptera: Culicidae) hosts, focusing specifically on the functional forms and strength of density dependence in the development of ingested microfilariae (mf) to infective (third instar) larvae (L3). Mathematical models describing observed mf−L3 functional responses for each of the major three parasite‐transmitting vector genera, Aedes, Culex and Anopheles mosquitoes, were fitted to paired mf−L3 data collated from all available studies in the published literature. Model parameters were estimated and compared by deriving and applying a data synthetic framework, based on applying a non‐linear weighted regression model for fitting mathematical models to multistudy data. The results confirm previous findings of the existence of significant between‐genera differences in the mf−L3 development relationship, particularly with regard to the occurrence of limitation in Culex mosquitoes and facilitation in Aedes and Anopheles mosquitoes. New and unexpected findings regarding L3 development from ingested mf were discovered as follows: (1) for Culex, overcompensation in L3 development at higher intensities of mf (or a peaked mf−L3 functional response) was detected; (2) for Aedes mosquitoes, facilitation (with an apparent asymptotic constraint on L3 development at high mf densities) was shown to be the major process governing L3 development, and (3) for Anopheles, a stronger facilitation type of response with no apparent saturation in L3 development appears to govern L3 output from ingested mf. These results yield major new insights regarding filarial vector infection dynamics and their potential impacts on parasite control, and demonstrate the efficacy of employing a data synthetic approach to reveal and estimate parasitic infection processes in host populations.