Chongguang Yang1, Jian Kang2, Xin Shen3, Nicolas A Menzies4, Liping Lu5, Xiaoqin Guo5, Ted Cohen1. 1. Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT, USA. 2. Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 3. Department of Tuberculosis Control, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China. shenxin@scdc.sh.cn. 4. Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA. nmenzies@hsph.harvard.edu. 5. Department of Tuberculosis Control, Songjiang Center for Disease Control and Prevention, Shanghai, China.
Abstract
BACKGROUND: Large-scale rural-to-urban migration has changed the epidemiology of tuberculosis (TB) in large Chinese cities. We estimated the contribution of TB importation, reactivation of latent infection, and local transmission to new TB cases in Shanghai, and compared the potential impact of intervention options. METHODS: We developed a transmission dynamic model of TB for Songjiang District, Shanghai, which has experienced high migration over the past 25 years. We calibrated the model to local demographic data, TB notifications, and molecular epidemiologic studies. We estimated epidemiological drivers as well as future outcomes of current TB policies and compared this base-case scenario with scenarios describing additional targeted interventions focusing on migrants or vulnerable residents. RESULTS: The model captured key demographic and epidemiological features of TB among migrant and resident populations in Songjiang District, Shanghai. Between 2020 and 2035, we estimate that over 60% of TB cases will occur among migrants and that approximately 43% of these cases will result from recent infection. While TB incidence will decline under current policies, we estimate that additional interventions-including active screening and preventive treatment for migrants-could reduce TB incidence by an additional 20% by 2035. CONCLUSIONS: Migrant-focused TB interventions could produce meaningful health benefits for migrants, as well as for young residents who receive indirect protection as a result of reduced TB transmission in Shanghai. Further studies to measure cost-effectiveness are needed to evaluate the feasibility of these interventions in Shanghai and similar urban centers experiencing high migration volumes.
BACKGROUND: Large-scale rural-to-urban migration has changed the epidemiology of tuberculosis (TB) in large Chinese cities. We estimated the contribution of TB importation, reactivation of latent infection, and local transmission to new TB cases in Shanghai, and compared the potential impact of intervention options. METHODS: We developed a transmission dynamic model of TB for Songjiang District, Shanghai, which has experienced high migration over the past 25 years. We calibrated the model to local demographic data, TB notifications, and molecular epidemiologic studies. We estimated epidemiological drivers as well as future outcomes of current TB policies and compared this base-case scenario with scenarios describing additional targeted interventions focusing on migrants or vulnerable residents. RESULTS: The model captured key demographic and epidemiological features of TB among migrant and resident populations in Songjiang District, Shanghai. Between 2020 and 2035, we estimate that over 60% of TB cases will occur among migrants and that approximately 43% of these cases will result from recent infection. While TB incidence will decline under current policies, we estimate that additional interventions-including active screening and preventive treatment for migrants-could reduce TB incidence by an additional 20% by 2035. CONCLUSIONS: Migrant-focused TB interventions could produce meaningful health benefits for migrants, as well as for young residents who receive indirect protection as a result of reduced TB transmission in Shanghai. Further studies to measure cost-effectiveness are needed to evaluate the feasibility of these interventions in Shanghai and similar urban centers experiencing high migration volumes.
Entities:
Keywords:
China; Internal migration; Public health policy; Transmission-dynamic modeling; Tuberculosis