Xiao-Yan Ding1, Wen-Hui Mao2, Wei Lu1, Hao Yu1, Qiao Liu1, Peng Lu1, Hui Jiang3, Xing Zhang4, Feng Lu5, Jie Xu6, Chong-Qiao Zhong7, Jin-Liu Hu8, Wei-Xi Jiang9, Lei Guo2, Sheng-Lan Tang10, Li-Mei Zhu1. 1. Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, 210009, Jiangsu, China. 2. Duke Global Health Institute, Duke University, 310 Trent Dr, Durham, NC, 27710, USA. 3. Zhenjiang Center for Disease Control and Prevention, No. 9 South Huangshan Road, Zhenjiang, 212000, Jiangsu, China. 4. Changzhou Center for Disease Control and Prevention, No. 28 Jianshen Road, Changzhou, 213000, Jiangsu, China. 5. Nantong Center for Disease Control and Prevention, No. 189 South Gongnong Road, Nantong, 226007, Jiangsu, China. 6. Yangzhou Center for Disease Control and Prevention, No. 36 East Yanfu Road, Yangzhou, 225001, Jiangsu, China. 7. Lianyungang Center for Disease Control and Prevention, No. 161 Middle Hailian Road, Lianyungang, Jiangsu, China. 8. Huai'an Center for Disease Control and Prevention, No. 6 Meigao Road, Huaian, 223001, Jiangsu, China. 9. Duke Kunshan University, Kunshan, Jiangsu, China. 10. Duke Global Health Institute, Duke University, 310 Trent Dr, Durham, NC, 27710, USA. shenglan.tang@duke.edu.
Abstract
BACKGROUND: The 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. METHODS: We 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. RESULTS: Three 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. CONCLUSIONS: The 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.
BACKGROUND: The 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. METHODS: We selected six prefectures from south, central and north Jiangsu Province. We reviewed policy documents between 2008 and 2019, and extracted routine TBpatient 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. RESULTS: Three 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. CONCLUSIONS: The 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.
Authors: Ji Lecai; Peierdun Mijiti; Hong Chuangyue; Li Mingzhen; Gao Qian; Tan Weiguo; Chen Jihong Journal: Infect Drug Resist Date: 2021-10-27 Impact factor: 4.003