Host and Microbial risk factors for drug-sensitive and resistant tuberculosis

但前提是。 结核分支杆菌是一种非常成功的病原体，每年感染800多万人，并导致 超过200万人死亡。据信，世界上三分之一的人口感染了这种微生物，但 只有一小部分感染者会继续发展为活动性疾病。尽管一些风险因素对 疾病进展已被描述，宿主和微生物机制导致增加 人们对易感性知之甚少。确定与传播有关的因素，并 药物敏感和耐药结核病的进展可能为临床和公众提供关注的靶点 健康干预。这种干预措施对于控制抗药性尤为重要。 结核病，因为目前的控制措施侧重于有效治疗感染病例。《长河》 学期目标是阐明与多药耐药(MDR)的出现和传播有关的因素和 广泛耐药(XDR)结核病，并制定和实施针对这些疾病的干预措施 减少结核病进展和传播的因素。这个项目的具体目标是 确定发展药物敏感性(DS)和多药耐药(MDR)的宿主、微生物和环境风险因素 并根据其流行病学和临床行为特征对菌株进行存档 它们可用于菌株多样性及其对MDR的贡献的基础研究。我们还将建立 一个全面的数据库，它将允许实时监测，并用于疫情建模和 个体预测模型将有助于有关耐药治疗的决策 肺结核。

PROVIDED. M. tuberculosis is a highly successful pathogen that infects over eight million people per year and leads to over 2 million deaths. One third of the world's population is believed to be infected with this organism, but only a small minority of those infected will go on to develop active disease. Although some risk factors for disease progression have been described, host and microbial mechanisms that lead to increased susceptibility are poorly understood. The identification of factors associated with the transmission and progression of drug sensitive and resistant tuberculosis may provide targets for focused clinical and public health interventions. Such interventions will be of particular importance for the control of drug resistant tuberculosis, since current control measures focus on the effective treatment of infectious cases. The long term goals are to elucidate factors involved in the emergence and transmission of multidrug (MDR) and extensively drug resistant (XDR) tuberculosis and to develop and implement interventions that target these factors in order to reduce tuberculosis progression and transmission. The specific aims of this project are to identify host, microbial and environmental risk factors for the development of drug sensitive (DS) and MDR tuberculosis and to archive strains characterized on the basis of their epidemiologic and clinical behavior so that they can be used in basic research on strain diversity and its contribution to MDR. We will also establish a comprehensive database which will allow real-time surveillance and be used for epidemic modeling and individual prediction models that will assist decision making regarding the treatment of drug resistant tuberculosis.