BackgroundIn recent years, drug resistant tuberculosis (DR-TB) particularly the emergence of multi-drug-resistant tuberculosis (MDR-TB) has become a major public health issue. The most recent study regarding the prevalence of drug-resistant tuberculosis in mainland China was a meta-analysis published in 2011, and the subjects from the included studies were mostly enrolled before 2008, thus making it now obsolete. Current data on the national prevalence of DR-TB is needed. This review aims to provide a comprehensive and up-to-date assessment of the status of DR-TB epidemic in mainland China.MethodsA systematic review and meta-analysis of studies regarding the prevalence of drug-resistant tuberculosis in mainland China was performed. Pubmed/MEDLINE, EMBASE, the Cochrane central database, the Chinese Biomedical Literature Database and the China National Knowledge Infrastructure Database were searched for studies relevant to drug-resistant tuberculosis that were published between January 1, 2012 and May 18, 2015. Comprehensive Meta-Analysis (V2.2, Biostat) software was used to analyse the data.ResultsA total of fifty-nine articles, published from 2012 to 2015, were included in our review. The result of this meta-analysis demonstrated that among new cases, the rate of resistance to any drug was 20.1% (18.0%–22.3%; n/N = 7203/34314) and among retreatment cases, the rate was 49.8% (46.0%–53.6%; n/N = 4155/8291). Multi-drug resistance among new and retreatment cases was 4.8% (4.0%–5.7%; n/N = 2300/42946) and 26.3% (23.1%–29.7%; n/N = 3125/11589) respectively. The results were significantly heterogeneous (p<0.001, I2 tests). Resistance to isoniazid was the most common resistance observed, and HRSE (H: isoniazid; R: rifampicin; S: streptomycin; E: ethambutol) was the most common form for MDR among both new and retreatment cases. Different drug resistance patterns were found by subgroup analysis according to geographic areas, subject enrolment time, and methods of drug susceptibility test (DST).ConclusionsThe prevalence of resistance to any drug evidently dropped for both new and retreatment cases, and multi-drug resistance declined among new cases but became more prevalent among retreatment cases compared to the data before 2008. Therefore, drug-resistant tuberculosis, particularly multi-drug-resistant tuberculosis among retreatment TB cases is a public health issue in China that requires a constant attention in order to prevent increase in MDR-TB cases.
BackgroundA prediction model for tuberculosis incidence is needed in China which may be used as a decision-supportive tool for planning health interventions and allocating health resources.MethodsThe autoregressive integrated moving average (ARIMA) model was first constructed with the data of tuberculosis report rate in Hubei Province from Jan 2004 to Dec 2011.The data from Jan 2012 to Jun 2012 were used to validate the model. Then the generalized regression neural network (GRNN)-ARIMA combination model was established based on the constructed ARIMA model. Finally, the fitting and prediction accuracy of the two models was evaluated.ResultsA total of 465,960 cases were reported between Jan 2004 and Dec 2011 in Hubei Province. The report rate of tuberculosis was highest in 2005 (119.932 per 100,000 population) and lowest in 2010 (84.724 per 100,000 population). The time series of tuberculosis report rate show a gradual secular decline and a striking seasonal variation. The ARIMA (2, 1, 0) × (0, 1, 1)12 model was selected from several plausible ARIMA models. The residual mean square error of the GRNN-ARIMA model and ARIMA model were 0.4467 and 0.6521 in training part, and 0.0958 and 0.1133 in validation part, respectively. The mean absolute error and mean absolute percentage error of the hybrid model were also less than the ARIMA model.Discussion and ConclusionsThe gradual decline in tuberculosis report rate may be attributed to the effect of intensive measures on tuberculosis. The striking seasonal variation may have resulted from several factors. We suppose that a delay in the surveillance system may also have contributed to the variation. According to the fitting and prediction accuracy, the hybrid model outperforms the traditional ARIMA model, which may facilitate the allocation of health resources in China.
BackgroundAlthough there was a report about the seasonal variation in Wuhan city, it only analyzed the prevalence data of pulmonary tuberculosis (TB) cases, and just studied the seasonality by subgroup of smear positive and negative from 2006 to 2010 by spectral analysis. In this study, we investigated the seasonality of the total newly notified pulmonary TB cases by subgroups such as time period, sex, age, occupation, district, and sputum smear result from 2004 to 2013 in Wuhan by a popular seasonal adjustment model (TRAMO-SEATS).MethodsMonthly pulmonary TB cases from 2004 to 2013 in Wuhan were analyzed by the TRAMO-SEATS seasonal adjustment program. Seasonal amplitude was calculated and compared within the subgroups.ResultsFrom 2004 to 2013, there were 77.76 thousand newly notified pulmonary TB cases in Wuhan, China. There was a dominant peak spring peak (March) with seasonal amplitude of 56.81% and a second summer peak (September) of 43.40%, compared with the trough month (December). The spring seasonal amplitude in 2004–2008 was higher than that of 2009–2013(P<0.05). There were no statistical differences for spring seasonal amplitude within subgroups of gender, age, district, and sputum smear result (P>0.05). However, there were significant differences in spring seasonal amplitude by occupation, with amplitude ranging from 59.37% to 113.22% (P<0.05). The summer seasonal amplitude in 2004–2008 was higher than that of 2009–2013(P<0.05). There were no statistical differences in summer seasonal amplitude within subgroups of gender, district, sputum smear result(P>0.05). There were significant differences in summer seasonal amplitude by age, with amplitude ranging from 36.05% to 100.09% (P<0.05). Also, there were significant differences in summer seasonal amplitude by occupation, with amplitude ranging from 43.40% to 109.88% (P<0.05).ConclusionsThere was an apparent seasonal variation in pulmonary TB cases in Wuhan. We speculated that spring peak in our study was most likely caused by the increased reactivation of the latent TB due to vitamin D deficiency and high PM2.5 concentration, while the summer peak was mainly resulted from the enhanced winter transmission due to indoor crowding in winter, overcrowding of public transportation over the period of the Spring Festival and health care seeking delay in winter.
We investigated the seasonality of tuberculosis (TB) in Wuhan, China, to evaluate the increased risk of disease transmission during each season and to develop an effective TB control strategy. We applied spectral analysis to the weekly prevalence data of sputum smear positive (SSP) and sputum smear negative (SSN) pulmonary TB reported from 2006 to 2010. Cases of both SSP and SSN feature 1·0- and 0·5-year periodic modes. The least squares method was used to fit curves to the two periodic modes for SSP and SSN data. The curves demonstrated dominant peaks in spring similar to cases reported previously for other locations. Notably for SSP, dominant peaks were also observed in summer. The spring peaks of SSP and SSN were explained in terms of poorly ventilated and humid rooms and vitamin D deficiency. For the summer peaks of SSP, summer influenza epidemics in Wuhan may contribute to the increase in TB prevalence.
How multidrug-resistant tuberculosis (MDR-TB) spreads and expands in Wuhan population is not clear. The study aimed to determine the transmission patterns of MDR-TB in Wuhan city, China, including 149 patients with MDR-TB. Tuberculosis isolates were genotyped by deletion-targeted multiplex polymerase chain reaction, mycobacterial interspersed repetitive unit-variable number tandem repeat typing, and sequencing of drug resistance-associated genes. The risk factors of genomic-clustering were analyzed with logistic regression. The genomic-clustering patients were deeply investigated. The analysis identified 111 unique and 11 clustered genotypes (38 isolates). The clustering rate was 25.50% and the minimum estimate proportion of recent transmission was 18.12%. Two clusters (5 isolates) shared the same mutation, the remain 9 clusters (33 isolates) had different mutation. Logistic regression showed that older than 60 years (adjusted OR 2.360, 95% CI:1.052-5.292) was an independent factor associated with the genomic-clustering of MDR-TB. Among the 38 genomic-clustering cases, 14 cases had epidemiological transmission links. The most common type of transmission link was social contact. The local transmission of MDR-TB in Wuhan was really an issue. The elderly population might be the high-risk groups for transmission of MDR-TB, and the community or public transportation might be the main transmission places.
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