Abstract

BackgroundThe detection of drug-resistant tuberculosis (DR-TB) is a major health concern in China. We aim to summarize interventions related to the screening and detection of DR-TB in Jiangsu Province, analyse their impact, and highlight policy implications for improving the prevention and control of DR-TB.MethodsWe selected six prefectures from south, central and north Jiangsu Province. We reviewed policy documents between 2008 and 2019, and extracted routine TB patient registration data from the TB Information Management System (TBIMS) between 2013 and 2019. We used the High-quality Health System Framework to structure the analysis. We performed statistical analysis and logistic regression to assess the impact of different policy interventions on DR-TB detection.ResultsThree prefectures in Jiangsu introduced DR-TB related interventions between 2008 and 2010 in partnership with the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund) and the Bill & Melinda Gates Foundation (Gates Foundation). By 2017, all prefectures in Jiangsu had implemented provincial level DR-TB policies, such as use of rapid molecular tests (RMT), and expanded drug susceptibility testing (DST) for populations at risk of DR-TB. The percentage of pulmonary TB cases confirmed by bacteriology increased from 30.0% in 2013 to over 50.0% in all prefectures by 2019, indicating that the implementation of new diagnostics has provided more sensitive testing results than the traditional smear microscopy. At the same time, the proportion of bacteriologically confirmed cases tested for drug resistance has increased substantially, indicating that the intervention of expanding the coverage of DST has reached more of the population at risk of DR-TB. Prefectures that implemented interventions with support from the Global Fund and the Gates Foundation had better detection performance of DR-TB patiens compared to those did not receive external support. However, the disparities in DR-TB detection across prefectures significantly narrowed after the implementation of provincial DR-TB polices.ConclusionsThe introduction of new diagnostics, including RMT, have improved the detection of DR-TB. Prefectures that received support from the Global Fund and the Gates Foundation had better detection of DR-TB. Additionally, the implementation of provincial DR-TB polices led to improvements in the detection of DR-TB across all prefectures.

Highlights

  • The detection of drug-resistant tuberculosis (DR-TB) is a major health concern in China

  • After controlling for demographic factors (e.g., TB history, residency and diagnosis agency), our findings show that the following types of patients were significantly more likely to be tested for drug resistance: patients with drug susceptibility testing (DST) coverage of biologically confirmed TB cases (3.84 times), smear-positive TB patients (2.54 times), and smear-positive TB patients and smear-negative but culture-positive TB patients (2.30 times)

  • Our study found that Jiangsu Province has implemented a series of interventions to improve DR-TB control and prevention, such as workforce increases, the use of rapid molecular tests (RMT) devices, and allocation of special funds focused on DR-TB

Read more

Summary

Introduction

The detection of drug-resistant tuberculosis (DR-TB) is a major health concern in China. Tuberculosis (TB) is a communicable disease that remains a key global health concern. In 2017, TB led to the highest number of deaths and the second highest disability-adjusted life years (DALYs) among all communicable diseases globally [1]. Drug-resistant TB (DR-TB) continues to remain a public health threat in China. Compared to regular TB, MDR/rifampicin-resistant(RR)-TB is more resource intensive and has a longer treatment course. The treatment success rate for RR-TB is not even 60% [5, 6]. In 2018, less than one fourth of MDR/ RR-TB patients around the world were estimated to be detected, and of those that were detected, only 60% had initiated treatment [6]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call