Disrupting Vector-borne Disease Transmission in Complex Urban Environments

描述（由申请人提供）：在复杂的城市环境中中断病媒传播疾病的传播该提案将通过开发新方法来改进病媒传播疾病传播的建模，以推断未观察到的空间过程，这些空间过程对空间数据收集中固有的不准确性和不确定性具有鲁棒性。为了发展和评估我们的方法，我们将在秘鲁的阿雷基帕市进行实地考察，在那里，南美锥虫病的寄生虫媒介克氏锥虫通过昆虫媒介致病锥虫的传播是一个严重的城市问题。查加斯病是美洲最致命的病媒传播疾病之一，有800多万人感染了查加斯病。克鲁兹在这800万人中，预计有20%至30%的人会发展为心脏或消化道慢性恰加斯病，这种疾病难以治疗，往往是致命的。城市密集的环境促进了病媒和寄生虫的传播，阻碍了控制工作， 有感染风险的人数。使控制更加复杂的是城市街道的网格，这导致了病媒传播的复杂模式。我们的建议包括三个具体目标;每个目标都解决了一个广泛的挑战，以阐明媒介传播疾病传播的不可见过程：1）绘图：创建媒介侵扰的地图，说明不完善的昆虫调查和景观中的空间障碍; 2）建模传播：预测T。infestans扩散通过一个城市，尽管其最初发生的地图不完善;和，3）空间控制：检测T。infestans的重新出现和T.通过自适应空间采样的Cruzi感染。实现这三个相互关联的目标将改善对城市和其他复杂环境中许多病媒传播疾病的控制。

DESCRIPTION (provided by applicant): Disrupting Vector-borne Disease Transmission in Complex Urban Environments This proposal will improve modeling of vector-borne disease transmission by developing new methods to make inference on unobserved spatial processes that are robust to the inaccuracies and uncertainties inherent in spatial data collection. To develop and evaluate our methods, we will conduct fieldwork in the city of Arequipa, Peru, where transmission of the parasitic agent of Chagas disease, Trypanosoma cruzi, by the insect vector Triatoma infestans is a serious urban problem. Chagas disease is one of the most deadly vector-borne diseases in the Americas; over 8 million people are infected with T. cruzi. Of these 8 million individuals 20% to 30% are expected to progress to cardiac or digestive forms of chronic Chagas disease which are difficult to treat and often fatal. The dense environment of cities facilitates the spread of vectors and parasites, hindering control efforts and putting large numbers of individuals at risk for infection. Further complicating control is the grid of city strets that leads to complex patterns of vector dispersal. Our proposal consists of three specific aims; each addresses a broad challenge to elucidating unseen processes of the spread of vector-borne diseases: 1) Mapping: To create maps of vector infestation that account for imperfect entomological surveys and spatial barriers in a landscape; 2) Modeling Spread: To predict T. infestans dispersal through a city despite imperfect maps of its initial occurrence; and, 3) Spatia Control: To detect foci of T. infestans re-emergence and micro-epidemics of T. cruzi infection through adaptive spatial sampling. Achieving these three interlocking aims will improve control of many vector-borne diseases in urban and other complex environments.