Disentangling the human vector relationship to disrupt dengue and chikungunya virus outbreaks in Kenya

在撒哈拉以南非洲，对登革热和基孔肯雅病毒的常规被动监测只能检测到其影响的一小部分，因为误诊的可能性很高，而且在不同地区和不同易感人群中传播的程度未经研究。已知和未知的昆虫学、环境和行为因素在不同生境中导致传播的差异。缺乏系统的监测和准确的诊断，加上临床怀疑程度低，都导致非洲环境中的诊断不足和无法预防疫情。在这一更新建议中，我们的假设是，持续的地方性传播导致爆发的可能性，这是由可测量的因素（人类运动和行为模式、天气/气候和病毒输入/引入）改变的，并且这种转变是可预测和可预防的。这些研究的目的是详细说明在人-病媒界面促进流行病传播的主要因素，并确定阻断这些因素的机会。为了确定暴发的关键驱动因素，我们计划：1)测量蚊子在空间和时间上的丰度；2)使用新技术更好地定义人类媒介暴露；3)识别导致暴露增加的人类属性，如运动和行为；4)了解疫情是由新病毒引入还是地方性病毒株引起的；5)确定正在进行的人际传播和爆发引发的最具影响力的驱动因素，然后使用建模来比较干预策略的潜在影响。采用新方法，我们实现了以下目标：1)确定媒介丰度增加和人类传播风险增加的时间段，以划定登革热和基孔肯雅热流行病过渡的阈值；2)详细说明病媒数量增加和人间传播风险增加的地点；3)确定记录在案的聚集性感染是否因输入/引进与地方性传播而发生；4)为预测影响建立疫情模型，为政策提供信息。这项研究基于15年的纵向合作研究，涉及肯尼亚蒙巴萨（沿海）和基苏木（西部）的队列，这两个地区全年都有登革热病毒和CHIKV的传播，并记录了最近的疫情。这些研究将填补关于CHIKV和DENV在当地栖息地持续存在以及在不同环境中导致疫情传播的因素方面的知识空白。这些数据还将回答有关发热综合征虫媒病毒病因的基本问题，同时提供相关疾病负担和长期后遗症的最佳估计。

In sub-Saharan Africa, routine passive surveillance for dengue (DENV) and chikungunya (CHIKV) viruses detects only a fraction of their impact, given the high probability of misdiagnosis and unstudied levels of transmission across different landscapes and within different susceptible populations. Known and unknown entomologic, environmental, and behavioral factors differentially drive transmission in different habitats. The lack of systematic surveillance and accurate diagnostics coupled with low levels of clinical suspicion all lead to under-diagnosis in the African setting and the inability to prevent outbreaks. In this renewal proposal, our hypothesis is that ongoing endemic transmission leads to potential for outbreaks that is modified by measurable factors (human movement and behavior patterns, weather/climate, and viral importations/introductions), and that this transition is predictable and preventable. The objective of these studies is to detail the dominant factors that facilitate epidemic transmission at the human-vector interface and to identify opportunities to blockade them. In order to define key drivers of outbreaks, we plan to: 1) Measure mosquito abundance in space and time; 2) Better define human-vector exposure using novel technology; 3) Identify human attributes such as movement and behavior that contribute to increased exposure; 4) Understand if outbreaks are due to new viral introductions or endemic viral strains and; 5) Identify the most influential drivers of ongoing human transmission and outbreak initiation and then use modeling to compare the potential impact of intervention strategies. Using novel approaches, we address the following aims: 1) Define time periods of increased vector abundance and increased risk for human transmission to delineate thresholds for dengue and chikungunya epidemic transition; 2) Detail locations with increased vector abundance and increased risk for human transmission; 3) Identify whether documented infection clusters occur due to importation/introduction vs. endemic transmission; and 4) Model outbreaks for predictive impact to inform policy. This research is based on 15 years of collaborative longitudinal studies and involves cohorts in Mombasa (coastal) and Kisumu (western), Kenya, where there is year-round transmission and documented recent outbreaks of DENV and CHIKV. These studies will fill knowledge gaps about the persistence of CHIKV and DENV in local habitats and the factors that contribute to outbreak transmission in varied settings. The data will also answer fundamental questions about arboviral etiologies in fever syndromes, while providing best estimates of related disease burden and long-term sequelae.