Community Transmission of Tuberculosis Urban Africa

根据世界卫生组织的数据，全球结核病负担在2000年达到顶峰， 每年下降1.5%。这一微小的进展福尔斯没有达到千年发展目标， 消灭结核病。此外，这种平均下降隐藏了发病率的重要变化， 结核病在当今世界的流行情况。这种差异突出表明，疾病的决定因素 各区域的发病率可能不同，因此干预措施必须适合当地的疾病流行病学。的 当今控制结核病的标准方法依赖于对流行结核病的检测和治疗 例这种方法可能在结核病高负担地区效果有限，其中M。 结核病的传播率相应较高。事实上，当一个病例得到诊断和治疗时， 下一代病例已经是新感染的。为了在遏制艾滋病流行方面取得进展， 因此，必须通过减少传播或预防疾病来预防新病例。 几十年来，家庭接触调查一直是结核病主动发现的主要手段。 虽然家庭是结核病传播的一个密集场所， 在一个特定的社区中，结核病的发病率不到25%。虽然家庭是一个方便， 本地化的社会网络的传播，很容易识别和评估，我们必须更好地了解 支持M的复杂社区网络。结核病的传播和导致疾病的“热点”。 该提案的目标是制定衡量支持结核病的社区网络的方法 传输在这个建议中，我们计划重建传染性结核病的社会和流动网络 利用手机元数据，将这些信息与全基因组整合， 序列的M.从指示病例中提取结核菌株，以推断传播网络。具体目标 主要有：1）评估确诊前肺结核病例的移动情况作为结核分枝杆菌的指标。 结核病在非洲城市社区的传播; 2）推断M.结核病在 非洲城市社区使用结核指示病例和相关病例分离株的全基因组测序 对社交网络和移动模式的传输推断。 为了实现这些目标，我们将通过收集存档的蜂窝网络来扩展我们当前项目的设计。 诊断结核病前一年索引病例的电话元数据。然后我们将构建 社会流动网络，在结核病诊断之前绘制社区内的流动图。我们将 利用从病例网络收集的分离株的全基因组测序来重建传播树 使用贝叶斯框架，该框架将社会和移动网络与系统发育信息相结合。这 绘制传播图的新方法可能为结核病控制项目提供一种有用的方法， 针对当地结核病流行情况采取的卫生干预措施。

According to the World Health Organization, the global burden of tuberculosis peaked in 2000 and has since declined by 1.5% per year. This modest progress falls short of the Millennial Development Goals for tuberculosis elimination. Moreover, this average decline hides important variation in the incidence and prevalence of tuberculosis around the world today. This variation highlights that determinants of disease incidence may differ across regions, so interventions must be tailored to local the epidemiology of disease. The standard approach to tuberculosis control today relies on detection and treatment of prevalent tuberculosis cases. This approach may have limited effectiveness in areas of high tuberculosis burden where M. tuberculosis transmission is correspondingly high. Indeed, by the time a case is diagnosed and treated, the next generation of cases has already been newly infected. To make progress in curbing the epidemic of tuberculosis, new cases must be prevented, either by reducing transmission or by preventing disease. Household contact investigation has been a mainstay of active case finding of tuberculosis for decades. Although the household is a setting of intense transmission of tuberculosis, household transmission accounts for less than 25% of tuberculosis that occurs in a given community. While the household is a convenient, localized social network for transmission that is easily identified and evaluated, we must better understand the complex community networks that support M. tuberculosis transmission and lead to disease ‘hotspots’. The goal of this proposal is to develop methods for measuring community networks that support tuberculosis transmission. In this proposal, we plan to reconstruct the social and mobility networks of infectious tuberculosis cases before diagnosis by using cellular telephone metadata and integrate this information with whole genome sequences of the M. tuberculosis strains from index cases to infer transmission networks. The Specific Aims are: 1) To assess the movement of pulmonary tuberculosis cases before diagnosis as an indicator of M. tuberculosis transmission in an urban African community; 2) To infer transmission trees of M. tuberculosis in an urban African community using whole genome sequencing of isolates from tuberculosis index cases and relate transmission inferences to social networks and mobility patterns. To address these aims, we will expand the design of our current project by collecting archived cellular telephone metadata from index cases for one year prior to the diagnosis of tuberculosis. We will then construct socio-mobility networks that map movement within the community prior to diagnosis of tuberculosis. We will use whole genome sequencing of isolates collected from case networks to reconstruct transmission trees using a Bayesian framework which combines social and mobility networks with phylogenetic information. This novel approach to mapping transmission may give tuberculosis control programs a useful way to tailor public health interventions that are responsive to the local epidemiology of tuberculosis.