AbstractDengue, chikungunya and zika are all transmitted by the Aedes aegypti mosquito. Despite the strong influence of host spatial distribution and movement patterns on the ability of mosquito vectors to transmit pathogens, there is little understanding how these complex interactions modify the spread of disease in spatially heterogeneous populations. In light of present fears of a worldwide zika epidemic, and failures to eradicate dengue and chikungunya; there is a pressing need to get a better picture of how high-resolution details such as human movement in a small landscape, modify the patterns of transmission of these diseases and how different mosquito-control interventions could be affected by these movements.In this work we use a computational agent-based model (ABM) to simulate mosquito-human interactions in two different levels of spatial heterogeneity, with human movement, and in the presence of three mosquito-control interventions (spatial spraying, the release of Wolbachia-infected mosquitoes and release of insects with dominant lethal gene). To analyse the results from each of these experiments we examined mosquito population dynamics and host to host contact networks that emerged from the distribution of consecutive bites across humans. We then compared results across experiments to understand the differential effectiveness of different interventions in both the presence and absence of spatial heterogeneities, and analysed network measures of epidemiological relevance (degree probability distributions, mean path length, network density and small-worldness).From our experiments we conclude that spatial heterogeneity greatly influences how a pathogen may spread in a host population when mediated by a mosquito vector, and that these important heterogeneities also strongly affect effectiveness of interventions. Finally, we demonstrate that these host to host vectorial-contact networks can provide operationally important information to inform selection of optimal vector-control strategies.Author SummaryMosquito-borne diseases’ transmission patterns arise from the complex interactions between hosts and vector. Because these interactions are influenced by host and vector behaviour, spatial constraints, and other factors they are amongst the most difficult to understand. In this work, we use our computational agent-based model: SoNA3BS; to simulate two spatially different settings in the presence and absence of three different mosquito-control interventions: fogging, the release of Wolbachia-infected mosquitoes and the release of insects with dominant lethal gene. Throughout these simulations, we record mosquito population dynamics and mosquito bites on persons. We then compare mosquito population dynamics to the vectorial-contact networks (that emerge from subsequent mosquito bites between humans) and, after performing these comparisons, we proceeded to show that even when mosquito population sizes are almost equal in both spatial settings, the resulting vectorial-contact networks are radically different. This has profound implications in our understanding of how mosquito-borne diseases spread in human populations and is relevant to the effective use of resources allocated to stop these pathogens from causing more harm in human populations.
The Use of Automated Traps to Assess the Efficacy of Insecticide Barrier Treatments Against Abundant Mosquitoes in Remote Environments
