Department of Parasitology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil.
Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
PLoS Comput Biol. 2020 Mar 13;16(3):e1007377. doi: 10.1371/journal.pcbi.1007377. eCollection 2020 Mar.
The overall malaria burden in the Americas has decreased dramatically over the past two decades, but residual transmission pockets persist across the Amazon Basin, where Plasmodium vivax is the predominant infecting species. Current elimination efforts require a better quantitative understanding of malaria transmission dynamics for planning, monitoring, and evaluating interventions at the community level. This can be achieved with mathematical models that properly account for risk heterogeneity in communities approaching elimination, where few individuals disproportionately contribute to overall malaria prevalence, morbidity, and onwards transmission. Here we analyse demographic information combined with routinely collected malaria morbidity data from the town of Mâncio Lima, the main urban transmission hotspot of Brazil. We estimate the proportion of high-risk subjects in the host population by fitting compartmental susceptible-infected-susceptible (SIS) transmission models simultaneously to age-stratified vivax malaria incidence densities and the frequency distribution of P. vivax malaria attacks experienced by each individual over 12 months. Simulations with the best-fitting SIS model indicate that 20% of the hosts contribute 86% of the overall vivax malaria burden. Despite the low overall force of infection typically found in the Amazon, about one order of magnitude lower than that in rural Africa, high-risk individuals gradually develop clinical immunity following repeated infections and eventually constitute a substantial infectious reservoir comprised of asymptomatic parasite carriers that is overlooked by routine surveillance but likely fuels onwards malaria transmission. High-risk individuals therefore represent a priority target for more intensive and effective interventions that may not be readily delivered to the entire community.
在过去的二十年中，美洲的整体疟疾负担显著下降，但在亚马逊盆地仍存在残留的传播点，其中间日疟原虫是主要的感染物种。目前的消除努力需要更好地定量了解疟疾传播动态，以便在社区层面进行规划、监测和评估干预措施。这可以通过数学模型来实现，这些模型可以正确考虑接近消除的社区中的风险异质性，在这些社区中，少数人不成比例地导致了总体疟疾流行率、发病率和传播。在这里，我们分析了人口统计信息，并结合巴西曼西尼奥利马镇的常规收集的疟疾发病率数据进行分析。我们通过同时拟合年龄分层间日疟发病率密度和每个人在 12 个月内经历的间日疟感染次数的频率分布，来估计宿主人群中高风险个体的比例。使用最佳拟合 SIS 模型进行的模拟表明，20%的宿主贡献了 86%的间日疟总体负担。尽管在亚马逊地区通常发现的整体感染率较低，比非洲农村地区低一个数量级，但高风险个体在反复感染后逐渐产生临床免疫力，最终形成一个由无症状寄生虫携带者组成的大量感染性储库，这被常规监测所忽视，但可能助长了疟疾的传播。因此，高风险个体是更密集和有效的干预措施的优先目标，这些干预措施可能不容易提供给整个社区。
