Metanetwork Transmission Model for Predicting a Malaria-Control Strategy - Li, Bo; Liu, Xiao; Wang, Wen-Juan; Zhao, Feng; An, Zhi-Yong; Zhao, Hai (Frontiers in Genetics, 2018)
Background: Mosquitoes are the primary vector for malaria transmission to humans, with numerous experiments having been conducted to aid in the control of malaria transmission. One of the main approaches aims to develop malaria parasite resistance within the mosquito population by introducing a resistance (R) allele. However, when considering this approach, some critical factors, such as the life of the mosquito, female mosquito fertility capacity, and human and mosquito mobility have not been considered. Thus, an understanding of how mosquitoes and humans affect disease dynamics is needed to better inform malaria control policy making. Methods: In this study, a method was proposed to create a metanetwork based on geographic maps of Gambia, and a model was constructed to simulate evolution within a mixed population, with factors such as birth, death, reproduction, biting, infection, incubation, recovery, and transmission between populations considered in the network metrics. First, the same number of refractory mosquitoes (RR genotype) were introduced into each population, and the prevalence of the R allele (the ratio of resistant alleles to all alleles) and malaria were examined. Additionally, a series of simulations were performed to evaluate two different deployment strategies for reducing the prevalence of malaria. The R allele and malaria prevalence were calculated for both strategies, with 10,000 refractory mosquitoes deployed into randomly selected populations or selection based on nodes with top betweenness values. The 10,000 mosquitoes were deployed among 1, 5, 10, 20, or 40 populations. Results: The simulations in this paper showed that a higher RR genotype (resistant-resistant genes) ratio leads to a higher R allele prevalence and lowers malaria prevalence. Considering the cost of deployment, the simulation was performed with 10,000 refractory mosquitoes deployed among 1 or 5 populations, but this approach did not reduce the original malaria prevalence. So, instead, the 10,000 refractory mosquitoes were distributed among 10, 20, or 40 populations and were shown to effectively reduce the original malaria prevalence. Thus, deployment among a relatively small fraction of central nodes can offer an effective strategy to reduce malaria. Conclusion: The standard network centrality measure is suitable for planning refractory mosquitoes deployment.