传染病传播的多维性提示运用时空传播模型模拟与预测传染病的时空扩散过程的重要性，除宿主和环境因素，病原体自身特征对传染病传播也起重要作用。本研究拟在人口流动频繁的城市和农村人群建立结核病患者和接触者队列，通过随访获得治疗转归及耐药等相关参数。通过24位点MIRU-VNTR及45位点SNP组合，配合测序，建立高分辨率的分型方法以鉴别社区外源性再感染，识别在目标人群近期传播的优势流行亚种Mtb及种群差异，探索Mtb的时空传播、系统发育和适应机制。并运用NetLogo建立基于多Agent和病原体特征的结核病流行病学仿真传播模型，通过耦合耐药、人群流动等子模型，探索结核病疫情稳定的阈值条件及基本再生数的变化，研究个体流动、耐药等因素对结核病传播和发生的作用机制，评估和预测不同潜在干预模式的效果。获得的模拟结果有助于更准确理解复杂情况下中国的结核病扩散机制，为国家制定结核病控制策略提供依据。

The multidimensional nature of the spread of infectious diseases implies the importance of using the spatiotemporal transmission model that visually simulate and forecast infectious disease diffusion. In addition to host and environmental factors, characteristics of pathogens on tuberculosis transmission also play an important role. In this application, through a cohort study for TB patients and contacts in urban and rural population respectively with a large proportion of population movements, we will obtain treatment outcome and drug resistance and other related parameters. By using 24 locus MIRU-VNTR and 45 single nucleotide polymorphisms (SNP) in combination with sequencing, we will establish the high resolution typing method to identify community exogenous reinfection and recognition in the target population of dominant endemic subspecies of Mycobacterium tuberculosis (Mtb), and to explore different subtypes and drug resistance of Mtb in the ability of space-time transmission. On the basis of above, NetLogo will be used to develop agent-based simulation models combined with pathogen transmission characteristics to understand the threshold of TB epidemic stability and basic reproduction value with time and space. The models will also help explore the impacts of rural-urban migration in Mtb transmission by coupling a population movement sub-model and anti-tuberculosis drug resistance by coupling a drug resistance model. The potential effect of different interventions or strategies will be evaluated and predicted in the modelling which will help understand the transmission mechanism of tuberculosis in the complex population network of China and provide evidence for the policy making of controlling TB in the country.