Disrupting Vector-borne Disease Transmission in Complex Urban Environments

描述(申请人提供)：在复杂的城市环境中中断媒介传播疾病传播这项提议将通过开发新的方法来改进媒介传播疾病传播的建模，以对未观察到的空间过程进行推断，这些方法对空间数据收集中固有的不准确和不确定性具有很强的抵抗力。为了开发和评估我们的方法，我们将在秘鲁阿雷基帕市进行实地调查，在那里，恰加斯病的寄生虫克氏锥虫通过昆虫媒介Triatoma inestans传播是一个严重的城市问题。恰加斯病是美洲最致命的媒介传播疾病之一；超过800万人感染了克氏锥虫。在这800万人中，预计有20%至30%的人会进展为心脏病或消化性慢性恰加斯病，这种疾病很难治疗，而且往往是致命的。城市的密集环境促进了病媒和寄生虫的传播，阻碍了控制努力，并使 面临感染风险的个人数量。更复杂的控制是城市街道的网格，这导致了复杂的媒介传播模式。我们的建议包括三个具体目标；每个目标都解决了阐明媒介传播疾病传播过程中未知过程的广泛挑战：1)测绘：创建媒介感染地图，解释不完善的昆虫学调查和景观中的空间障碍；2)建模传播：预测感染毛滴虫在城市中的传播，尽管其最初发生的地图不完美；以及，3)空间控制：通过自适应空间采样检测感染毛滴虫的疫点重新出现和毛滴虫感染的微观流行。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的许多媒介传播疾病的控制。

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.