Multidrug-resistant tuberculosis (MDR-TB) disease burden in China: a systematic review and spatio-temporal analysis

Background: Surveillance data on the proportion of incident TB cases with MDR was limited and there is no systematic study of MDR-TB in China to date. Our aim was to estimate MDR-TB disease burden in 2012 and change trends during 2003-2012 using spatio-temporal systematic analysis. Methods: We systematically searched Chinese and English databases for primary articles and reviews that contain MDR-TB survey data about China during the period of 2003-2012. We estimated the proportion of incident TB cases with MDR in cities which had no data to report in 2012 by Kriging spatial interpolation analysis. The primary outcomes were the proportion of incident TB cases with MDR at 2012 and the change trend during 2003-2012. Results: Total 487 articles met the screening criteria, including 450 in Chinese and 37 in English, and have been used in analysis. The proportion of incident TB cases with MDR among all cases in 2012 showed clear geographic differences. From 2003 to 2012, the proportion of incident TB cases with MDR in all, new and previously treated TB cases were higher during 2006-2009 and significantly lower during 2010-2012 in comparison with the period during 2003-2005 (P < 0.0167). The estimated median proportion of incident TB cases with MDR among all cases, as well as in new and previously treated cases in 2012 was 12.8% (IQR 9.8-17.3%), 5.4% (4.5-7.3%) and 28.5% (20.5-30.9%) respectively, which led to an estimate of 121,600 (IQR93,000-164,350) MDR-TB cases in China. Conclusions: This estimate of MDR-TB burden is considerably higher than data reported by the Chinese fifth national tuberculosis epidemiological sampling survey in 2010 but close to the WHO report, which implies that detailed investigations of MDR-TB burden in China is needed. This research provides data to guide public health decisions at various scales; methods described here can be extended to estimate of the other chronic diseases as well.National Natural Science Foundation of China [U1611264, 61571001]SCI(E)REVIEW1