Identifying gaps between LLIN use and vector exposure to improve malaria control

确定 LLIN 使用和媒介暴露之间的差距，以改善疟疾控制

• 批准号: 10647800
• 负责人: Paul Joseph Krezanoski
• 金额: $ 19.72万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10647800
• 关键词: Address; Adherence; Affect; Africa; African; Anopheles Genus; Area; Award; Beds; Bite; Blood; Cessation of life; Characteristics; Child; Classification; Cohort Studies; Culicidae; Data; Dedications; Electronics; Entomology; Epidemiology; Exposure to; Female; Future; Genotype; Goals; Health; Hour; Household; Human; Incidence; Individual; Insecticides; International; Intervention; Life; Link; Location; Longitudinal cohort; Malaria; Malaria prevention; Measurement; Measures; Mentored Patient-Oriented Research Career Development Award; Mentorship; Modeling; Monitor; Multivariate Analysis; National Institute of Allergy and Infectious Disease; Participant; Patient Self-Report; Pattern; Persons; Predisposition; Prevention; Public Health; Recommendation; Reporting; Research; Research Activity; Resolution; Risk; Sleep; Testing; Training; Uganda; United States National Institutes of Health; Universal Coverage; Update; Variant; Vertebral column; Work; World Health Organization; career; cohort; density; design; disease transmission; experience; high risk; improved; infectious disease model; innovation; invention; malaria transmission; new technology; novel strategies; programs; scale up; sensor; skills; tool; transmission process; vector

PROJECT SUMMARY/ABSTRACT Malaria affects three billion people worldwide. Despite remarkable reductions in malaria incidence over the last 15 years, recent evidence shows that our traditional control tools are weakening. Long-lasting insecticide-treated bednets (LLINs) are the most widely used tool for malaria prevention and have contributed significantly to decreases in malaria incidence, but recent studies suggest that LLINs are either less effective than before or people are not using them as reported. A rigorous assessment of how the timing and location of vector exposure intersects with real-life use of LLINs could be vitally important to regain the initiative in malaria control. However, the lack of a reliable measure of LLIN use presents a major challenge. Current measurement tools, like self-reported use, are subjective and unable to account for temporal variations in use. To address these limitations, I invented an electronic monitor of LLIN use. SmartNet uses sensors embedded in a standard LLIN to continuously assess whether it is unfurled with 98% accuracy. We have completed successful feasibility, acceptability and field trials of SmartNet. The central rationale for this project is that continuous monitoring of individual LLIN use combined with quantified exposure to malaria vectors will allow a more robust analysis than has previously been possible of how LLINs reduce vector exposure in practice. The research goal of this K23 proposal is to develop high-yield interventions for improving malaria control by identifying gaps between individual risk of vector exposure and individual LLIN use. To facilitate this work, I have access to a longitudinal cohort of 480 individuals in Uganda. Our approach leverages intensive entomology surveillance already being gathered every two weeks in this cohort. Additionally, we will deploy SmartNets over every sleeping space to cover every individual over multiple years. High-yield interventions will be identified by pursuing three specific aims: 1) quantify exposure to malaria vectors and identify factors associated with higher risk, 2) quantify LLIN use and identify factors associated with poor adherence and 3) identify mismatches between LLIN use and vector exposure, develop interventions addressing these gaps and then systematically determine the highest-yield interventions for reducing vector-human contact using a model of vector exposure. My long-term career goal is to establish an independent research career developing innovative approaches for improving malaria control. This K23 proposal supplements my prior experience with mentorship and training in malaria entomology and epidemiology and infectious disease modelling. Together, the proposed research activities and complementary training are designed to lead to a robust program of future work. I will emerge from this award prepared for a strong NIH R01 application to apply this approach in different transmission settings, to develop operational studies of the high-yield interventions we identify and to expand the scope from reducing vector-human contact to reducing actual malaria incidence. This K23 award provides the crucial link between my current experience and achieving my career goal of becoming an international leader inventing, deploying and testing innovative approaches for improving malaria prevention.

项目总结/摘要 疟疾影响着全世界30亿人。尽管过去一年疟疾发病率显著下降， 15年来，最近的证据表明，我们传统的控制工具正在减弱。长效驱虫 蚊帐是最广泛使用的疟疾预防工具，对降低疟疾发病率作出了重大贡献，但最近的研究表明，蚊帐的效果不如以前， 并没有像报道的那样使用它们。严格评估病媒接触的时间和地点如何与长效驱虫蚊帐的实际使用交叉，对于重新获得疟疾控制的主动权至关重要。但 缺乏对长效杀虫剂使用情况的可靠衡量标准是一项重大挑战。目前的测量工具，如自我报告 使用，是主观的，不能解释使用中的时间变化。为了解决这些局限性，我发明了 LLIN使用的电子监视器。SmartNet使用嵌入在标准LLIN中的传感器， 它是否展开的准确率高达98%我们已经完成了成功的可行性，可接受性和现场试验 智能网这一项目的主要理由是，持续监测单个长效杀虫剂吸入器的使用情况， 与疟疾病媒接触的量化将允许比以前更可靠的分析 长效驱虫蚊帐如何在实践中减少病媒接触。本K23方案的研究目标是开发高产 通过查明接触病媒的个人风险与 个人LLIN使用。为了促进这项工作，我有机会在乌干达纵向队列的480人。 我们的方法利用了在这个群体中每两周收集一次的密集昆虫学监测。此外，我们将在每个睡眠空间部署智能网络，以覆盖多个睡眠空间中的每个人。 年将通过追求三个具体目标来确定高收益的干预措施： 向量，并确定与高风险相关的因素，2）量化LLIN的使用，并确定与 3）查明长效驱虫蚊帐的使用与病媒接触之间的不匹配，制定解决这些差距的干预措施，然后有系统地确定减少病媒-人传播的最有效干预措施 接触使用一个模型的向量曝光。我的长期职业目标是建立一个独立的研究 职业发展创新方法，以改善疟疾控制。这个K23提案补充了我之前的提案 在疟疾昆虫学和流行病学以及传染病建模方面的指导和培训经验。拟议的研究活动和补充培训旨在共同促成一项强有力的 未来的工作计划。我将从这个奖项出来准备一个强大的NIH R 01应用程序， 方法在不同的传输设置，开发业务研究的高产干预措施，我们 确定并扩大范围，从减少病媒与人的接触到减少疟疾的实际发病率。这 K23奖为我目前的经验和实现我的职业目标提供了至关重要的联系， 一位国际领导者，发明、部署和测试改进疟疾预防的创新方法。

项目成果

Evaluation of an accelerometer-based monitor for detecting bed net use and human entry/exit using a machine learning algorithm.

• DOI: 10.1186/s12936-022-04102-z
• 发表时间: 2022-03-12
• 期刊: Malaria journal
• 影响因子: 3
• 作者: Koudou GB;Monroe A;Irish SR;Humes M;Krezanoski JD;Koenker H;Malone D;Hemingway J;Krezanoski PJ
• 通讯作者: Krezanoski PJ