Zhengwei Liu , Xiangchen Li , Haiyan Xiong , Qingrong Zhou , Huaiming Yi , Kunyang Wu , Zonglei Zhou , Yewei Lu , Yelei Zhu , Lin Zhou , Mingwu Zhang , Junshun Gao , Junli Gao , Songhua Chen , Xiaomeng Wang , Weibing Wang
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Gene mutations associated with drug resistance were identified in 19.4% (103/532) of strains, including 47 rifampicin or isoniazid-resistant strains, eight multi-drug-resistant (MDR) strains, and five pre-extensively drug-resistant (pre-XDR) strains. Genomic clustering revealed 53 distinct clusters with an overall transmission clustering rate of 23.9% (127/532). Patients with a history of retreatment and those infected with L2 strains had a higher risk of recent transmission. Spatial and epidemiological analysis unveiled significant transmission hotspots, especially in densely populated urban areas, involving various public places such as medical institutions, farmlands, markets, and cardrooms. The study emphasizes the pivotal role of Beijing strains and urban-based TB transmission in the western mountainous regions in Zhejiang, highlighting the urgent requirement for specific interventions to mitigate the impact of TB in these unique communities.</p></div>","PeriodicalId":54986,"journal":{"name":"Infection Genetics and Evolution","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1567134824000546/pdfft?md5=ddf2a00db7bab082cc1fd046d60e9e02&pid=1-s2.0-S1567134824000546-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Genomic and spatial analysis reveal the transmission dynamics of tuberculosis in areas with high incidence of Zhejiang, China: A prospective cohort study\",\"authors\":\"Zhengwei Liu , Xiangchen Li , Haiyan Xiong , Qingrong Zhou , Huaiming Yi , Kunyang Wu , Zonglei Zhou , Yewei Lu , Yelei Zhu , Lin Zhou , Mingwu Zhang , Junshun Gao , Junli Gao , Songhua Chen , Xiaomeng Wang , Weibing Wang\",\"doi\":\"10.1016/j.meegid.2024.105603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In the mountainous, rural regions of eastern China, tuberculosis (TB) remains a formidable challenge; however, the long-term molecular epidemiological surveillance in these regions is limited. 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Genomic and spatial analysis reveal the transmission dynamics of tuberculosis in areas with high incidence of Zhejiang, China: A prospective cohort study
In the mountainous, rural regions of eastern China, tuberculosis (TB) remains a formidable challenge; however, the long-term molecular epidemiological surveillance in these regions is limited. This study aimed to investigate molecular and spatial epidemiology of TB in two mountainous, rural counties of Zhejiang Province, China, from 2015 to 2021, to elucidate the recent transmission and drug-resistance profiles. The predominant Lineage 2 (L2) Beijing family accounted for 80.1% of total 532 sequenced Mycobacterium tuberculosis (Mtb) strains, showing consistent prevalence over seven years. Gene mutations associated with drug resistance were identified in 19.4% (103/532) of strains, including 47 rifampicin or isoniazid-resistant strains, eight multi-drug-resistant (MDR) strains, and five pre-extensively drug-resistant (pre-XDR) strains. Genomic clustering revealed 53 distinct clusters with an overall transmission clustering rate of 23.9% (127/532). Patients with a history of retreatment and those infected with L2 strains had a higher risk of recent transmission. Spatial and epidemiological analysis unveiled significant transmission hotspots, especially in densely populated urban areas, involving various public places such as medical institutions, farmlands, markets, and cardrooms. The study emphasizes the pivotal role of Beijing strains and urban-based TB transmission in the western mountainous regions in Zhejiang, highlighting the urgent requirement for specific interventions to mitigate the impact of TB in these unique communities.
期刊介绍:
(aka Journal of Molecular Epidemiology and Evolutionary Genetics of Infectious Diseases -- MEEGID)
Infectious diseases constitute one of the main challenges to medical science in the coming century. The impressive development of molecular megatechnologies and of bioinformatics have greatly increased our knowledge of the evolution, transmission and pathogenicity of infectious diseases. Research has shown that host susceptibility to many infectious diseases has a genetic basis. Furthermore, much is now known on the molecular epidemiology, evolution and virulence of pathogenic agents, as well as their resistance to drugs, vaccines, and antibiotics. Equally, research on the genetics of disease vectors has greatly improved our understanding of their systematics, has increased our capacity to identify target populations for control or intervention, and has provided detailed information on the mechanisms of insecticide resistance.
However, the genetics and evolutionary biology of hosts, pathogens and vectors have tended to develop as three separate fields of research. This artificial compartmentalisation is of concern due to our growing appreciation of the strong co-evolutionary interactions among hosts, pathogens and vectors.
Infection, Genetics and Evolution and its companion congress [MEEGID](http://www.meegidconference.com/) (for Molecular Epidemiology and Evolutionary Genetics of Infectious Diseases) are the main forum acting for the cross-fertilization between evolutionary science and biomedical research on infectious diseases.
Infection, Genetics and Evolution is the only journal that welcomes articles dealing with the genetics and evolutionary biology of hosts, pathogens and vectors, and coevolution processes among them in relation to infection and disease manifestation. All infectious models enter the scope of the journal, including pathogens of humans, animals and plants, either parasites, fungi, bacteria, viruses or prions. The journal welcomes articles dealing with genetics, population genetics, genomics, postgenomics, gene expression, evolutionary biology, population dynamics, mathematical modeling and bioinformatics. We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services .