Regional distribution of Mycobacterium tuberculosis infection and resistance to rifampicin and isoniazid as determined by high-resolution melt analysis

Abstract

Abstract Background Identifying the transmission mode and resistance mechanism of Mycobacterium tuberculosis (MTB) is key to prevent disease transmission. However, there is a lack of regional data. Therefore, the aim of this study was to identify risk factors associated with the transmission of MTB and regional patterns of resistance to isoniazid (INH) and rifampicin (RFP), as well as the prevalence of multidrug-resistant tuberculosis (MDR-TB). Methods High-resolution melt (HRM) analysis was conducted using sputum, alveolar lavage fluid, and pleural fluid samples collected from 17,515 patients with suspected or confirmed MTB infection in the downtown area and nine counties of Luoyang City from 2019 to 2021. Results Of the 17,515 patients, 82.6% resided in rural areas, and 96.0% appeared for an initial screening. The HRM positivity rate was 16.8%, with a higher rate in males than females (18.0% vs. 14.1%, p < 0.001). As expected, a positive sputum smear was correlated with a positive result for HRM analysis. By age, the highest rates of MTB infection occurred in males (22.9%) aged 26–30 years and females (28.1%) aged 21–25. The rates of resistance to RFP and INH and the incidence of MDR were higher in males than females (20.5% vs. 16.1%, p < 0.001, 15.9% vs. 12.0%, p < 0.001 and 12.9% vs. 10.2%, p < 0.001, respectively). The HRM positivity rate was much higher in previously treated patients than those newly diagnosed for MTB infection. Notably, males at the initial screening had significantly higher rates of HRM positive, INH resistance, RFP resistance, and MDR-TB than females (all, p < 0.05), but not those previously treated for MTB infection. The HRM positivity and drug resistance rates were much higher in the urban vs. rural population. By multivariate analyses, previous treatment, age < 51 years, residing in an urban area, and male sex were significantly and positively associated with drug resistance after adjusting for smear results and year of testing. Conclusion Males were at higher risks for MTB infection and drug resistance, while a younger age was associated with MTB infection, resistance to INH and RFP, and MDR-TB. Further comprehensive monitoring of resistance patterns is needed to control the spread of MTB infection and manage drug resistance locally.

Keywords

• Multidrug-resistant tuberculosis
• Transmission
• Molecular epidemiology
• Resistance model