Transmission dynamics of lymphatic filariasis: density‐dependence in the uptake ofWuchereria bancroftimicrofilariae by vector mosquitoes

Abstract

Abstract. Gaining a better understanding of parasite infection dynamics in the vector mosquito (Diptera: Culicidae) population is central to improving knowledge regarding the transmission, persistence and hence control of lymphatic filariasis. Here, we use data on mosquito feeding experiments collated from the published literature to examine the available evidence regarding the functional form of the first component of this parasite±vector relationship for Wuchereria bancrofti (Filarioidea: Onchocercidae) causing Bancroftian filariasis, i.e. the rate of microfilariae (mf) uptake from the blood of infected humans by the feeding mosquito vector. Using a simple logarithmic regression model for describing the observed relationships between the mean numbers of mf ingested per mosquito and parasite load in humans in each study, and a linear mixed-effects metaanalytical framework for synthesizing the observed regressions across studies, we show here for the first time clear evidence for the existence of densitydependence in this process for all the three major filariasis transmitting mosquito vectors. An important finding of this study is that this regulation of mf uptake also varies significantly between the vector genera, being weakest in Culex, comparatively stronger in Aedes and most severe and occurring at significantly lower human mf loads in Anopheles mosquitoes. The analysis of the corresponding mf uptake prevalence data has further highlighted how density-dependence in mf uptake may influence the observed distributions of mf in vector populations. These results show that whereas strong regulation of mf uptake, especially when it leads to saturation in uptake at low human parasite intensities, can lead to static distributions of mf per mosquito with host parasite intensity, a weaker regulation of mf ingestion can give rise to changes in both mean mf loads and in the frequency distribution of parasites/mosquito with increasing human parasite intensity. These findings highlight the importance of considering local vector infection dynamics when attempting to predict the impacts of community-based filariasis control. They also emphasize the value of developing and applying robust meta-analytic methods for estimating functional relationships regarding parasitic infection from population ecological data.

An Analysis of Genetic Diversity and Inbreeding in Wuchereria bancrofti: Implications for the Spread and Detection of Drug Resistance

“…Although density-dependent processes are known to operate on the uptake and development of W. bancrofti in An. gambiae , infective vectors will regularly transmit multiple related L3 larvae simultaneously [46]. Other mosquito vectors of W. bancrofti have even greater vector competence.…”

Complex Ecological Dynamics and Eradicability of the Vector Borne Macroparasitic Disease, Lymphatic Filariasis

“…Two distinctive density dependences are included in the model in accordance with available data and knowledge regarding infection processes governing parasite transmission dynamics: one which governs the uptake of microfilariae (Mf) and the development of L3-stage (infective) larvae by mosquito vectors when a bloodmeal is taken from a human host [13]–[15]; and a second concerning the mating probability of worms inside the human hosts [16]. We regard that both these density dependences are likely to independently and simultaneously act to affect the transmission of filariasis, via the introduction of vector biting transmission thresholds and breakpoint worm levels in the human population [10].…”

LYMFASIM, a simulation model for predicting the impact of lymphatic filariasis control: quantification for African villages

“…If adjustments are made for differences in exposure to mosquito bites, then the model should be valid for other Indian areas, assuming that the basic biological assumptions are correct. However, the model cannot be used in regions with other vector or parasite species, because of known differences in the transmission dynamics (Southgate, 1992 ;Snow and Michael, 2002 ;Snow et al 2006). To support decision making in the elimination programmes worldwide, we need vector-parasite specific, validated model variants (Dadzie et al 2004 ;Stolk, de Vlas and Habbema, 2006).…”