With the rapid rise in the prevalence of non-tuberculous mycobacteria (NTM) diseases across the world, the microbiological diagnosis of NTM isolates is becoming increasingly important for the diagnosis and treatment of NTM disease. In this study, the clinical presentation, species distribution and drug susceptibility of patients with NTM disease visiting the Chongqing Public Health Medical Centre during March 2016–April 2019 were retrospectively analysed. Among the 146 patients with NTM disease, eight NTM species (complex) were identified. The predominant NTM species in these patients were identified to be Mycobacterium abscessus complex (53, 36.3%), M. intracellulare (38, 26%) and M. fortuitum (17, 11.7%). In addition, two or more species were isolated from 7.5% of the patients. Pulmonary NTM disease (142, 97.3%) showed the highest prevalence among the patients. It was observed that 40.1% of the patients with pulmonary NTM disease had chronic pulmonary obstructive disease and bronchiectasis, while 22.5% had prior tuberculosis. Male patients showed more association with the conditions of cough and haemoptysis than the female patients. In an in vitro antimicrobial susceptibility testing, most of the species showed susceptibility to linezolid, amikacin and clarithromycin, while M. fortuitum exhibited low susceptibility to tobramycin. In conclusion, the prevalence of NTM disease, especially that of the pulmonary NTM disease, is common in Southwest China. Species identification and drug susceptibility testing are thus extremely important to ensure appropriate treatment regimens for patient care and management.

Primary drug-resistant tuberculosis (DR-TB) contributes significantly to the global TB epidemic, particularly in countries with high TB burdens. This study aimed to investigate the characteristics of primary DR-TB prevalence in Chongqing, China, from 2012 to 2020. A total of 4546 newly diagnosed and 2769 relapse TB patients admitted to the hospital from 2012 to 2020 were included. Categorical variables were compared using Pearson chi-square test or Fisher exact test, as appropriate. Logistic regression analysis was performed to determine factors associated with primary DR-TB. The rate of primary DR-TB was 24.5%, whereas that of acquired DR-TB was 67.8%. Among newly diagnosed TB cases, the percentage of DR-TB (from 48.9 to 44.2%), mono-resistant TB (from 11.8 to 9.7%), multidrug-resistant TB (MDR-TB; from 25.3 to 6.9%), and pre-extensive drug-resistant TB (from 13.7 to 5.8%) showed a decreasing trend from 2012 to 2020. Age from 15 to 64 years was a risk factor for the development of primary DR-TB (15–44 years: adjusted odds ratio = 2.227, 95% confidence interval: 1.053–4.710; 45–64 years: adjusted odds ratio = 2.223, 95% confidence interval: 1.048–4.717). The rates of primary DR-TB (P = .041) and MDR-TB (P = .007) were significantly higher in the age group of 15 to 64 years than in the age groups of ≤14 years and ≥65 years. Noticeably, rising trends of primary DR-TB (from 0 to 27.3%) and MDR-TB (from 0 to 9.1%) in the population of ≤14 years were observed from 2012 to 2020. Although the rate of primary DR-TB showed a downward trend, a rising drug-resistance rate among some particular subgroups was still observed. Further control of primary DR-TB should focus more on TB patients aged 15 to 64 years.

Pulmonary Tuberculosis (PTB) remains a serious infectious disease and a major global public health problem. Accurate prediction of PTB epidemics is essential to support health authorities in developing effective prevention and control strategies. This study proposed a novel two-stage hybrid prediction model that integrates a seasonal autoregressive integrated moving average (SARIMA) model and a support vector regression (SVR) model in parallel, followed in series by an extreme learning machine (ELM) optimized via the sparrow search algorithm. Furthermore, recognizing the notable spatial correlation characteristic of airborne PTB transmission, this study incorporates PTB incidence data from surrounding regions of the target area as additional input features to enhance the model with supplementary spatial information, thereby improving prediction accuracy. Validation using real-world PTB incidence data from Chongqing, China, demonstrates the superior performance of the proposed model, which reduces prediction errors by 18.47% to 77.38% compared to existing hybrid models. The inclusion of adjacent regional incidence data further significantly enhances predictive accuracy, reducing errors by 20.92% to 68.74%. The outcomes of this study are expected to facilitate earlier insights into PTB incidence trends and provide valuable support for public health decision-making in PTB prevention and control.

Objective: The epidemic of drug-resistant tuberculosis (DR-TB) has become a major concern in global TB control. This study aimed to investigate the patterns and trend of DR-TB epidemic between different time periods in Chongqing. Methods: A total of 985 and 835 culture positive TB patients with drug susceptibility testing (DST) results admitted to the hospital in 2016 and 2019, respectively, were included. Chi-square testing was used to compare the prevalence and trends of DR-TB in 2016 and 2019. Results: The proportion of previously treated TB cases with culture positivity was 45.7% in 2019, significantly higher than that in 2016 (39.1%, P = 0.004). The overall rate of drug resistance in 2019 was 43.1%, higher than that in 2016 (40.2%). The rates of multi-drug resistant TB (MDR-TB) and pre-extensively drug resistant TB (pre-XDR-TB) increased significantly from 2016 to 2019 among all TB cases (MDR: 25% vs 33.4%, P < 0.001 and pre-XDR: 7.1% vs 12.8%, P < 0.001, respectively) and previously treated TB cases (MDR: 46.5% vs 56%, P = 0.008 and pre-XDR: 13.2% vs 21.5%, P = 0.003, respectively). Conclusions: Our findings indicated that the prevalence of DR-TB remains high in Chongqing. The trend of resistance to anti-TB drugs beccame worse between 2016 and 2019. Moreover, acquired MDR may play a major role in MDR-TB epidemic in Chongqing. Therefore, rapid diagnosis and effective treatment of TB patients will be important to reduce the burden of DR-TB in Chongqing.