Air Pollution Effects on Transmission of Mycobacterium tuberculosis in Urban Slum Community in Uganda

空气污染和结核病是两种最具破坏性和威胁生命的全球公共卫生问题 有问题。全世界有数亿人生活在城市贫民窟，他们是弱势的、边缘化的和艰苦的- 受室内和室外空气污染和结核分枝杆菌影响最大的是可到达人群 变速箱。该项目探索空气污染细颗粒物(PM2.5)暴露是否以及如何增加 在结核病高发城市贫民窟，结核分枝杆菌从结核病指标病例向其家庭接触者(HC)的传播 坎帕拉/乌干达的纳穆旺戈地区。我们之前已经表明，空气污染PM2.5的暴露抑制了 基本的、保护性的、结核分枝杆菌特异性的、人类先天的和适应性的宿主免疫反应。无人应答的钥匙 对全球结核病控制工作具有重要意义的问题是，暴露在空气污染中是否会增加 结核分枝杆菌在脆弱社区的传播，通过(结核病指数病例的)传染性增加 以及(他们的接触者)对结核杆菌感染的易感性。我们假设吸入性接触PM2.5 通过增加结核病源强度，即结核分枝杆菌含量，增加结核病指标病例的传染性 通过呼吸气雾剂，并通过引发咳嗽。我们进一步假设PM2.5暴露抑制了保护性 免疫反应导致结核病指示病例中的HC对结核杆菌感染的易感性增加。两者都有 预计将增加结核分枝杆菌在社区中的传播。为了解决我们的假设，我们将 评估(1)结核病指示病例及其HC(结核分枝杆菌传播)(SA1)中新的结核分枝杆菌感染的来源强度； (2)个人空气污染(PM2.5)暴露量(SA2)和(3)个人空气污染(PM2.5)暴露量 与呼吸道巨噬细胞中的PM负荷、来源强度和结核分枝杆菌向HC的传播有关(SA3)。评估 结核病指数病例的来源强度，我们将使用 新的口罩采样方法。我们还将与莱斯特医院一起确定结核病指标病例咳嗽频率 咳嗽监测，评估胸片和培养阳性的时间(MGIT培养)。结核分枝杆菌从 结核病对丙型肝炎的指示病例将通过结核菌素皮肤试验和QFN-Plus血液试验在0至5周内确定 8.所有措施综合反映了结核病指标病例的传染性。暴露于PM2.5的结核病指示病例和 将采用多种方法对HC的随机样本进行研究：黄金标准重量法(UPAS)和实测法。 第0周至第8周的空气监测时间，评估痰中呼吸道巨噬细胞的PM负荷 在随机选择的和新感染结核分枝杆菌的固定家庭中诱发结核病指数病例 PM2.5和室外PM2.5监测，家庭调查问卷调查。结核病指标之间的关联 将使用线性建模来寻找病例来源强度、结核分枝杆菌传播和PM2.5暴露，以确定两者 主要影响因素和影响因素。破译导致结核分枝杆菌传播的环境因素 脆弱的城市人口将为强制公共卫生行动提供急需的数据，并改善 世界范围内的结核病控制方法。

Air pollution and tuberculosis (TB) represent two of the most devastating and life-threatening global public health problems. With hundreds of million persons living in urban slums worldwide, vulnerable, marginalized and hard- to-reach populations are most affected by indoor and outdoor air pollution and Mycobacterium tuberculosis (Mtb) transmission. This project explores if and how air pollution fine particulate matter (PM2.5) exposure increases the transmission of Mtb from TB index cases to their household contacts (HC) in a high TB incidence urban slum area (Namuwongo) in Kampala/Uganda. We have previously shown that air pollution PM2.5 exposures suppress essential, protective, Mtb-specific, human innate and adaptive host immune responses. A key unanswered question of great significance to global TB control efforts is whether air pollution exposure increases the risk for transmission of Mtb in vulnerable communities, both through increased infectiousness (of the TB index cases) and susceptibility to Mtb infection (of their contacts). We hypothesize that inhalational exposure to PM2.5 increases the infectiousness of TB index cases by increasing their source strength i.e. the Mtb content in their respiratory aerosols, and by triggering cough. We further hypothesize that PM2.5 exposure suppresses protective immune responses leading to increased susceptibility to Mtb infection in the HC of the TB index cases. Both would be expected to increase transmission of Mtb in the community. To address our hypotheses, we will evaluate (1) the source strength of TB index cases and new Mtb infection in their HC (Mtb transmission) (SA1), (2) personal air pollution (PM2.5) exposures (SA2) and (3) how personal air pollution (PM2.5) exposure is associated with PM load in airway macrophages, source strength, and Mtb transmission to HC (SA3). To assess the source strength of the TB index cases, we will quantify the Mtb load in their respiratory aerosols using a novel face mask sampling approach. We will also determine TB index case cough frequencies with the Leicester Cough Monitor, assess chest radiographs and time to culture positivity (MGIT culture). Transmission of Mtb from TB index cases to HC will be ascertained by tuberculin skin test and QFN-Plus blood test between weeks 0 and 8. All measures combined reflect infectiousness of TB index cases. Exposure to PM2.5 of TB index cases and a random sample of HC will be studied using multiple approaches: `gold standard' gravimetric (UPAS) and real- time air monitoring between weeks 0 and 8, assessment of PM load in airway macrophages obtained by sputum induction of TB index cases and in randomly selected as well as newly Mtb-infected HC, stationary household PM2.5 and outdoor PM2.5 monitoring, and household study with questionnaires. Associations between TB index case source strength, Mtb transmission and PM2.5 exposure will be sought using linear modeling, to identify both main effects and modifying factors. Deciphering environmental factors that contribute to transmission of Mtb in vulnerable urban populations will provide much needed data for mandated public health actions and improved TB control approaches worldwide.