病毒性肝炎、痢疾、肺结核、梅毒、手足口病等传染病已成为危害我国居民健康的重大公共卫生问题。气象因素可能从病原活性、传播途径和人群易感性等多个方面影响传染病的流行。本研究基于“二阶段建模”的思想，拟采用分布滞后非线性模型与Meta回归，分析气象因素与发病风险之间的潜在关系，并估计人群归因病例数及百分比，探讨气象因素影响的“净效应”，并识别潜在的影响气象因素-发病风险关系空间分布的社会经济因素；继而利用基线的归因病例数与本研究拟估计的气象因素变化数据，来预测本世纪中及本世纪末，我国各种重大传染病的归因疾病负担。本研究将进一步提出一种新方法，从社会经济的角度，评估人群对气象因素影响传染病的敏感性，计算社会敏感性指数，并研究其空间分布特征，识别敏感区域。

Infectious diseases including viral hepatitis, dysentery, tuberculosis, syphilis, and hand, foot, and mouth disease (HFMD) have become major public health issues in China. Meteorological factors may play a critical role in the development of these major infectious diseases via potential impacts on the activity of the virus, the route of transmission, and the vulnerability of the population, etc. In the present study, the relationship between the risk of infectious diseases and meteorological predictors, as well as the attributable number and fraction of reported cases which indicate the “net effect” of a meteorological predictor will be assessed with distributed lag non-linear model and meta regression under the two-stage modeling framework. Socio-economic factors potentially modifying the predictor-RR association will also be identified. We will then incorporate the attributable number of cases and estimated change in meteorological predictors between the baseline and the future into the distributed lag non-linear model to project the attributable burden of major infectious diseases in China in 2050s and 2100s. We will also propose a novel methodology to evaluate the vulnerability of the population to the risk of infectious diseases that can be attributed to a certain meteorological predictor from the socio-economic perspective. A social vulnerability index (SVI) will be calculated so that vulnerable areas can be identified based on the spatial pattern of SVI.