Preparing for a world with artemisinin resistance: using individual-based epidemiological modeling to minimize the long-term detrimental effects of antimalarial drug resistance

为青蒿素耐药性的世界做好准备：使用基于个体的流行病学模型最大限度地减少抗疟药物耐药性的长期有害影响

基本信息

批准号：
10457317
负责人：
Maciej F Boni
金额：
$ 34.39万
依托单位：
PENNSYLVANIA STATE UNIVERSITY, THE
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-10 至 2025-07-31
项目状态：
未结题

项目摘要

Project Summary/Abstract Plasmodium falciparum is the deadliest of the five species of malaria parasites that infect humans. Annually, there are over 200 million symptomatic cases of falciparum malaria and over 400,000 deaths – the majority of which occur in African children under the age of five. The two major interventions that have had an effect on reducing malaria prevalence over the past twenty years are mosquito control and use of antimalarial drugs. The most important class of drugs in this effort has been the artemisinin derivatives, which since 2005 have been deployed as artemisinin combination therapies (ACTs) only, in order to reduce the probability of emergence and spread of artemisinin-resistant genotypes. Despite these efforts, artemisinin resistance did emerge, and we are now facing the dangerous prospect that these drug-resistant genotypes may spread to Africa, where most of the world’s malaria cases occur. In this proposal, we will introduce and evaluate a number of drug-resistance management strategies that are intended to prevent, delay, and slow down the spread of drug-resistant genotypes of P. falciparum. First, we will make a number of technical advances in our existing individual-based (agent-based) simulation that we already use to model the evolution and epidemiology of P. falciparum in human populations. We will add explicit grid- based spatial structure to make the model more realistic. Additionally, we will add a genotype-phenotype map and clinically-parameterized pharmacodynamic/pharmacokinetic sub-models to make the model’s drug- resistance component as realistic as current data allow. Second, we will evaluate strategies for how best to manage the population-level introduction of novel antimalarial therapies that will become available in the 2020s. The strategies will be aimed at minimizing the long-term risk of drug resistance to both the novel therapies and to currently used ACTs, in order to minimize the number of treatment failures in the long run. Finally, we will parameterize country scenarios for Cambodia, Zambia, and Burkina Faso to provide specific country-level advice in low, medium, and high transmission malaria settings on how best to preëmpt drug resistance or minimize its current spread. As Cambodia is the epicenter of the current wave of artemisinin resistance, the Cambodia- specific model will be used to provide advice on how to contain and eliminate currently circulating artemisinin- resistant genotypes of P. falciparum.

项目摘要/摘要恶性疟原虫是感染人类的五种疟疾寄生虫中最致命的。每年有超过2亿症状的恶性疟疾病例和40万人死亡 - 大多数这发生在五岁以下的非洲儿童中。两种主要干预措施对在过去的二十年中，减少疟疾患病率是蚊子控制和使用抗疟药。在这项工作中，最重要的药物是青蒿素衍生物，自2005年以来一直是仅作为青蒿素组合疗法（使徒行为）部署，以减少出现的可能性和青蒿素耐药基因型的传播。尽管做出了这些努力，但青蒿素耐药确实出现了，我们是现在面对这些耐药基因型可能传播到非洲的危险前景，大多数发生了世界的疟疾病例。在此提案中，我们将介绍和评估许多抗药性管理策略旨在预防，延迟和减慢恶性疟原虫抗药性基因型的扩散。首先，我们会的在我们现有的基于个体的（基于代理的）模拟中，取得了许多技术进步用于模拟人群中恶性疟原虫的进化和流行病学。我们将添加明确的网格 - 基于空间结构，使模型更现实。此外，我们将添加一个基因型 - 表型图以及临床参数化的药效/药代动力学子模型，使该模型的药物 - 电阻组件与当前数据允许一样现实。其次，我们将评估策略的方式管理将在2020年代可用的新型抗疟疾疗法的种群水平引入。这些策略将旨在最大程度地降低对新疗法的耐药性和耐药性的长期风险从长远来看，目前使用的行为是为了最大程度地减少治疗失败的数量。最后，我们会的柬埔寨，赞比亚和布基纳法索的参数化国家方案，以提供特定的国家 /地区级建议在低，中，高传输疟疾的设置中，如何最好地预防耐药性或最小化其耐药性电流蔓延。由于柬埔寨是当前青蒿素耐药性浪潮的中心，柬埔寨 - 特定模型将用于提供有关如何遏制和消除当前循环阿甲蛋白酶的建议恶性疟原虫的抗性基因型。