Universidad San Francisco de Quito, Instituto de Geografía, Quito, Ecuador.
Duke University, Duke global Health Institute, Durham, NC, United States of America.
PLoS One. 2018 Mar 6;13(3):e0193493. doi: 10.1371/journal.pone.0193493. eCollection 2018.
Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.
尽管疟疾控制措施在近几十年来显著降低了疟疾的流行率，但全球根除疟疾仍远未实现。最近的研究表明，低传播地区的环境和社会异质性对塑造疟疾微观流行病学具有更大的影响。应该开发和测试新的综合和更本地化的控制策略。在这里，我们提出了一组基于代理的模型，旨在研究局部尺度人类活动对典型亚马逊环境中局部尺度疟疾传播的影响，在这种环境中，疟疾传播率较低，与季节性河流洪水密切相关。基于代理的模拟结果表明，整体疟疾发病率基本上不受局部尺度人类活动的影响。相比之下，疟疾高危空间热点的位置严重依赖于人类的活动，因为模拟的疟疾热点主要集中在农场，那里的工人白天工作。然后，我们使用基于代理的模型来测试两种不同的疟疾控制策略的有效性，这两种策略都旨在通过针对热点来降低局部尺度的疟疾发病率。第一种控制方案是对蚊子叮咬的人进行治疗，在模拟过程中，这些人至少有一次进入了考虑到实际感染人类个体所在地点的热点区域。第二种方案涉及对进入热点区域的人进行治疗，假设每个感染个体的感染地点都位于个体居住的家庭中。模拟结果表明，与随机治疗相比，这两种方案在控制疟疾方面都表现得更好，尽管针对家庭热点的方案略好一些。
