Mosquito Biting and Movement Rates as an Emergent Community Property and The Implications for Malarial Interventions

Abstract

Malaria, a mosquito-vectored disease, continues to be one of the most important scourges afflicting humankind. In this paper, we take a mosquito-centric approach by studying mosquito states (i.e., energy, neurological health, and toxin information state) to demonstrate how key parameters of malaria, biting and movement rates and mosquito survival, are all emergent properties of those states when considered in the context of the background community interactions. We do so as follows: First, we develop a dynamic state variable model of mosquito biting and movement decisions that maximize mosquito expected reproductive success (fitness), and then we embed those optimal policies in a Monte Carlo simulation wherein mosquitoes attempt to feed on human hosts at domiciles where insecticide-treated bednets (ITNs) and insecticidal residual wall sprays (IRSs) are used. We find that biting rates, at the domicile level, are not impacted by mosquito state but that emigration rates from domiciles are determined by an interaction between mosquito energy state, information state, and risk of predation. This means that malaria incidence, at the village level at least, may be best understood as a response of mosquitoes to their ecological community that includes nectar-bearing plants, predators, the spatial arrangement of homes, and the protection of humans in those homes.

Keywords:

• Mosquito
• malaria
• Anopheles
• bednet
• dynamic state variable
• biting rate
• Monte Carlo