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

• 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
• 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
• 来源: https://reporter.nih.gov/project-details/10457317
• 关键词: Africa; Africa South of the Sahara; African; Age; Anti-malarial drug resistance; Antimalarials; Artemisinins; Automobile Driving; Burkina Faso; Cambodia; Case Study; Cessation of life; Child; Chloroquine; Clinical; Clinical Trials; Combined Modality Therapy; Country; Culicidae; Dangerousness; Data; Disease; Drops; Drug Kinetics; Drug Modelings; Drug Prospecting; Drug resistance; Drug usage; Elements; Epidemiology; Evaluation; Evolution; Falciparum Malaria; Frequencies; Genotype; Guidelines; Human; Individual; Intervention; Invaded; Link; Malaria; Maps; Mathematics; Medicine; Mefloquine; Methods; Modeling; Mosquito Control; Outcome; Parasites; Pharmaceutical Preparations; Pharmacodynamics; Phenotype; Plasmodium falciparum; Policies; Population; Preparation; Prevalence; Privatization; Probability; Pyrimethamine-Sulfadoxine; Recommendation; Recording of previous events; Research; Resistance; Risk; Rotation; Running; Southeastern Asia; Structure; Therapeutic; Treatment Efficacy; Treatment Failure; Variant; World Health Organization; Writing; Zambia; base; data modeling; drug market; epidemiological model; global health; malaria transmission; novel; novel strategies; novel therapeutics; pharmacodynamic model; pharmacokinetic model; pharmacokinetics and pharmacodynamics; preempt; prevent; resistance mechanism; risk minimization; simulation; transmission process; vector control

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.

项目总结/摘要 恶性疟原虫是感染人类的五种疟原虫中最致命的一种。每年， 有2亿多例有症状的恶性疟疾病例，40多万人死亡-大多数 发生在五岁以下的非洲儿童身上。两个主要的干预措施， 在过去二十年中，减少疟疾流行的主要措施是控制蚊子和使用抗疟药物。的 在这一努力中，最重要的一类药物是青蒿素衍生物，自2005年以来， 仅作为青蒿素联合疗法（ACT）部署，以降低出现的可能性， 青蒿素耐药基因型的传播。尽管做出了这些努力，但青蒿素耐药性确实出现了，我们正在 现在面临着危险的前景，这些耐药基因型可能会蔓延到非洲，那里的大多数 世界上的疟疾病例发生。 在本提案中，我们将介绍和评估一些耐药性管理策略， 旨在预防、延迟和减缓恶性疟原虫耐药基因型的传播。一是 在我们现有的基于个体（基于代理）的模拟中取得了一些技术进步，我们已经 用于模拟恶性疟原虫在人群中的进化和流行病学。我们将添加明确的网格- 基于空间结构，使模型更加真实。此外，我们将添加基因型-表型图 和临床参数化药效学/药代动力学子模型，以使模型的药物- 电阻分量尽可能真实，因为目前的数据允许。其次，我们将评估如何最好地 管理在人口一级引进将在2020年代提供的新型抗疟疗法。 这些策略旨在最大限度地减少对新疗法和新疗法的耐药性的长期风险。 目前使用的以青蒿素为基础的综合疗法，以便从长远来看尽量减少治疗失败的次数。最后我们将 柬埔寨、赞比亚和布基纳法索的参数化国家情景，以提供具体的国家一级咨询意见 在低、中、高传播疟疾环境中，如何最好地预防耐药性或最大限度地减少 电流传播。由于柬埔寨是当前青蒿素耐药性浪潮的中心，柬埔寨- 将使用特定模型来提供有关如何遏制和消除当前流行的青蒿素的建议- 恶性疟原虫的抗性基因型。