Interdisciplinary and multi-level approach to estimate the disease burden and outcomes of childhood tuberculous meningitis.

项目总结 候选人：Karen Du Preez博士致力于研究事业，专注于改善 低收入和中等收入国家的儿童。她的总体职业发展目标是成为一名 独立的临床医生科学家，拥有全面、跨学科的技能和研究网络，可有效地 回答高度优先的公共卫生问题，并有能力将研究成果转化为有意义的 政策和执行方面的变化，以改善南非和全球儿童的卫生保健。这个整体 目标由三个具体的培训目标支持：1)理解并将专门的分析技能应用于公众 卫生研究，特别是疾病估计建模技术和空间分析方法；2) 加强临床、管理和领导方面的专业知识；以及3)培养转化研究的能力 转变为有意义的政策变化和实施。杜普雷兹博士得到了德斯蒙德·图图结核病的全力支持 中心是南非开普敦斯泰伦博什大学的国际公认的研究中心， 组建了一支在儿科结核病研究的各个方面都非常有经验的指导团队，并积极参与 在国家和国际两级为科学指导委员会作出贡献并支持儿科结核病 计划实施。 研究：儿童结核病的疾病负担和疾病谱缺乏可靠的监测数据 结核病是一项挑战，它限制了我们在全球适当管理该疾病的能力。结核脑膜炎(TB)是一种 严重形式的儿童结核病，预后非常差，通常导致终生神经功能障碍 如果不及早诊断和治疗，就会导致残疾。儿童TBM监测数据很少，总体上 因此，这项研究的目标是确定儿童三岁时的TBM的负担、发生率和结局 级别：全球、国家(南非)和国家以下各级(开普敦地区)，同时确定 预防，早诊断，早治疗。数学建模技术将被用来估计 按国家和世卫组织区域分列的全球儿童结核病负担和可归因性死亡率(具体目标1)。 南非14年(2004-2017)的常规结核病监测数据将被用来确定 国家疾病负担和儿童TBM治疗结果的时空异质性 确定高负担地点和不利结果的人口层面的驱动因素(具体目标2)。 前瞻性、互补性的监测策略将确定所有诊断和未诊断的儿童结核 开普敦卫生区两年内的病例(15年)。所有已确认身份的儿童都有资格 申请参加一项观察性队列研究，该研究将收集关于诊断确定性、疾病严重性、 结核病预防治疗和早期诊断的合并症、结果和错失机会 目的是告知早期诊断(诊断算法)和针对改进的TBM的有针对性的干预 预防和护理(具体目标3)。

PROJECT SUMMARY Candidate: Dr. Karen du Preez has dedicated herself to a research career focused on improving health care for children in low and middle income countries (LMIC). Her overall career development goal is to become an independent clinician scientist with a comprehensive, interdisciplinary skill set and research network to efficiently answer high priority public health questions, and have the ability to translate research findings into meaningful policy and implementation changes to improve health care for children in South Africa, and globally. This overall goal is supported by three specific training aims: 1) To understand and apply specialized analytical skills to public health research, specifically disease estimation modelling techniques and spatial analytic methods; 2) To strengthen clinical, management and leadership expertise; and 3) To develop the ability to translate research into meaningful policy changes and implementation. Dr. du Preez has the full support of the Desmond Tutu TB Centre, an internationally recognized research center at Stellenbosch University, Cape Town, South Africa and has assembled a mentoring team highly experienced in all facets of pediatric TB research, and actively involved at both national and international level contributing to scientific steering committees and supporting pediatric TB program implementation. Research: The lack of reliable surveillance data for the disease burden and spectrum of pediatric tuberculosis (TB) is a challenge that limits our ability to appropriately manage the disease globally. TB meningitis (TBM) is a severe form of pediatric tuberculosis with very poor outcomes and often consequent lifelong neurological disability if not diagnosed and treated early. Very little childhood TBM surveillance data exist and the overall goal of this research is therefore to determine the burden, incidence and outcomes of childhood TBM at three levels: global, national (South Africa) and sub-national (Cape Town district), whilst identifying opportunities for prevention, earlier diagnosis and treatment. Mathematical modelling techniques will be used to estimate the global burden of childhood TBM disease and attributable mortality, by country and WHO region (Specific Aim 1). Routine TB surveillance data from South Africa, spanning 14 years (2004-2017), will be used to determine the spatiotemporal heterogeneity of the national disease burden and treatment outcomes of childhood TBM and identify population-level drivers of high burden locations and unfavorable outcomes (Specific Aim 2). Prospective, complementary surveillance strategies will identify all diagnosed and undiagnosed childhood TBM cases (<15 years) within the Cape Town health district over a 2-year period. All identified children will be eligible for enrolment in an observational cohort study that will collect data on diagnostic certainty, disease severity, comorbidities, outcomes and missed opportunities for both TB preventive therapy and earlier diagnosis, with the aim of informing earlier diagnosis (diagnostic algorithms) and targeted interventions for improved TBM prevention and care (Specific Aim 3).