Dataset Information

A population-based genomic epidemiological study of the source of tuberculosis infections in an emerging city: Shenzhen, China.

ABSTRACT:

Background

Tuberculosis (TB) in emerging cities is often a disease of recent immigrants, and understanding this epidemiology is crucial for designing effective control and prevention strategies.

Methods

We conducted a retrospective population-based genomic epidemiological study of culture-positive pulmonary TB patients diagnosed between June 2014 and November 2017 in the Bao'an District of Shenzhen, a Chinese city with dramatic recent growth. After whole genome sequencing, transmission clusters were defined as strains differing by no more than 12 SNPs.

Findings

Of 1696 culture-positive TB patients, 93•8% (1591/1696) were migrants, with 51•6% (821/1591) employed in housekeeping or unemployed. Of the 1460 migrants with known residence time, 47•7% (697/1460) developed TB within two years after arriving in Bao'an. Only 12•2% (207/1696) of Bao'an isolates were in genomic clusters, indicating that recent transmission was not the primary cause of TB in Bao'an. The isolates' median terminal branch length was 56 SNPs, more than could have accumulated since the arrival of the migrants in Bao'an. The migrants' isolates had genotypic distributions similar to those in their home provinces. One strain isolated in Bao'an belonged to a clade circulating in the patient's home province, providing further evidence that the strains were brought to Bao'an with the migrants.

Interpretation

TB in the Bao'an District is principally caused by reactivation of infections acquired by migrants in their home provinces. Nearly half developed TB within two years after arriving in Bao'an, suggesting a need for increased TB screening of migrants, especially housekeeping workers and the unemployed.

Funding

Sanming Project of Medicine in Shenzhen; National Science and Technology Major Project of China; Natural Science Foundation of China.

SUBMITTER: Yang T

PROVIDER: S-EPMC8315418 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Massive internal migration from rural to urban areas poses new challenges for tuberculosis control in China. We aimed to combine genomic, spatial, and epidemiological data to describe the dynamics of tuberculosis in an urban setting with large numbers of migrants. METHODS:We did a population-based study of culture-positive Mycobacterium tuberculosis isolates in Songjiang, Shanghai. We used whole-genome sequencing to discriminate apparent genetic clusters of M tuberculosis sharing identical variable-number-tandem-repeat (VNTR) patterns, and analysed the relations between proximity of residence and the risk of genomically clustered M tuberculosis. Finally, we used genomic, spatial, and epidemiological data to estimate time of infection and transmission links among migrants and residents. FINDINGS:Between Jan 1, 2009, and Dec 31, 2015, 1620 cases of culture-positive tuberculosis were recorded, 1211 (75%) of which occurred among internal migrants. 150 (69%) of 218 people sharing identical VNTR patterns had isolates within ten single-nucleotide polymorphisms (SNPs) of at least one other strain, consistent with recent transmission of M tuberculosis. Pairs of strains collected from individuals living in close proximity were more likely to be genetically similar than those from individuals who lived far away-for every additional km of distance between patients' homes, the odds that genotypically matched strains were within ten SNPs of each other decreased by about 10% (OR 0·89 [95% CI 0·87-0·91]; p<0·0001). We inferred that transmission from residents to migrants occurs as commonly as transmission from migrants to residents, and we estimated that more than two-thirds of migrants in genomic clusters were infected locally after migration. INTERPRETATION:The primary mechanism driving local incidence of tuberculosis in urban centres is local transmission between both migrants and residents. Combined analysis of epidemiological, genomic, and spatial data contributes to a richer understanding of local transmission dynamics and should inform the design of more effective interventions. FUNDING:National Natural Science Foundation of China, National Science and Technology Major Project of China, and US National Institutes of Health.