Community Transmission of Tuberculosis Urban Africa

非洲城市结核病的社区传播

• 批准号: 9761955
• 负责人: Christopher C. Whalen
• 金额: $ 66.58万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9761955
• 关键词: Address; Africa; African; Archives; Area; BCG Vaccine; Bayesian Modeling; Cellular Phone; Communities; Community Networks; Complex; Data; Detection; Development; Diagnosis; Disease; Effectiveness; Epidemic; Epidemiology; Event; Genetic Variation; Genomics; Geography; Goals; Household; Incidence; Individual; Infection; Intervention; Interview; Investigation; Lead; Locales; Location; Maps; Measures; Metadata; Methods; Modeling; Molecular Epidemiology; Movement; Mycobacterium tuberculosis; Patients; Pattern; Phylogenetic Analysis; Population; Prevalence; Pulmonary Tuberculosis; Recording of previous events; Records; Research; Resolution; Role; Social Mobility; Social Network; Symptoms; Time; Trees; Tuberculosis; Uganda; Variant; World Health Organization; advanced disease; burden of illness; case finding; community setting; design; disorder control; falls; genome sequencing; indexing; meetings; mycobacterial; next generation; novel; novel strategies; prevent; programs; public health intervention; support network; theories; transmission process; tuberculosis treatment; urban setting; whole genome

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.

根据世界卫生组织的数据，全球结核病的负担在2000年达到顶峰，此后一直 以每年1.5%的速度下降。这一进展不大，未能实现千年发展目标 消灭结核病。此外，这一平均下降掩盖了发病率和死亡率的重要变化 结核病在当今世界的流行。这种变异突出了疾病的决定因素 不同地区的发病率可能不同，因此干预措施必须针对当地的疾病流行病学而量身定做。这个 当今结核病控制的标准方法依赖于对流行结核病的检测和治疗 案子。这种方法在结核病负担高的地区可能效果有限，在那里M。 相应地，结核病传播率也很高。事实上，当一个病例被诊断和治疗时， 下一代病例已经被新感染。在遏制艾滋病疫情方面取得进展 对于结核病，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活跃病例发现的支柱。 虽然家庭是结核病密集传播的环境，但家庭传播账户 不到25%的结核病发生在特定的社区。虽然家庭是一个方便的， 对于易于识别和评估的本地化社交网络传播，我们必须更好地理解 支持结核分枝杆菌传播并导致疾病“热点”的复杂社区网络。 这项提案的目标是开发衡量支持结核病的社区网络的方法。 变速箱。在这项建议中，我们计划重建传染性结核病的社会和流动网络 使用移动电话元数据并将这些信息与全基因组集成在一起 从首发病例中提取结核分枝杆菌毒株的序列以推断传播网络。具体目标 主要有：1)在确诊前评估肺结核病例的动向，作为M。 非洲城市社区中的结核病传播；2)推断非洲城市社区中结核分支杆菌的传播树 非洲城市社区使用结核病指征病例和相关病例分离株的全基因组测序 传播推论到社交网络和移动模式。 为了达到这些目标，我们将通过收集存档的细胞来扩展我们当前项目的设计 在结核病诊断前一年的索引病例的电话元数据。然后我们将构建 在诊断结核病之前绘制社区内流动地图的社会流动网络。我们会 使用从病例网络收集的分离株的全基因组测序重建传播树 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 绘制传播地图的新方法可能会给结核病控制项目提供一种有用的方式来适应公众 对当地结核病流行病学作出反应的卫生干预措施。