Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study

• DOI: 10.1016/j.lanwpc.2023.100833
• Publication Date: 2023-06-29T10:46:46Z
• Authors: Meng Li; Liping Lu; Qi Jiang; Yuan Jiang; Chongguang Yang; Jing Li; Yangyi Zhang; Jinyan Zou; Yong Li; Wenqi Dai; Jianjun Hong; Howard Takiff; Xin Shen; Xiaoqin Guo; Zhengan Yuan; Qian Gao
• Keywords: 1. No poverty; Articles; 3. Good health

With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over past few decades, but recently rate decrease has slowed, especially large cities such as Shanghai. To help formulate strategies to further reduce incidence, we performed a 10-year study Songjiang, district Shanghai, delineate characteristics, transmission patterns, and dynamic changes local burden.We conducted population-based culture-positive pulmonary patients diagnosed Songjiang during 2011-2020. Genomic clusters were defined with threshold distance 12-single-nucleotide-polymorphisms based on whole-genome sequencing, risk factors for clustering identified by logistic regression. Transmission inference was using phybreak. The distances between residences compared genomic their isolates. Spatial patient hotspots kernel density estimation.Of 2212 enrolled patients, 74.7% (1652/2212) internal migrants. (25.2%, 558/2212) spatial concentrations clustered unclustered unchanged period. Migrants had significantly higher rates less than residents. Clustering highest male migrants, younger both residents migrants employed physical labor. Only 22.1% events occurred more likely transmit decreased rapidly increasing residences, half pairs lived ≥5 km apart. Epidemiologic links only 15.6% mostly close contacts.Although some Songjiang's migrant population is caused strains brought infected local, recent an important driver burden. These results suggest that reductions require novel detect early interrupt urban transmission.Shanghai Municipal Science Technology Major Project (ZD2021CY001), National Natural Foundation (82272376), Research Council (2017ZX10201302-006).