Background: With the increasing of ageing population, tuberculosis in the elderly brings a challenge for the tuberculosis (TB) control in China. Enough social support can promote the treatment adherence and outcome of the elderly patients with TB. Exploring effective interventions to improve the social support of patients is of great significance for TB management and control. Methods: A community-based, repeated measurement trial was conducted. Patients with TB >65 years of age were allocated into the intervention or control group. Patients in the intervention group received comprehensive social support interventions, while those in the control group received health education alone. The social support level of patients was measured at baseline and at the first, third and sixth months during the intervention to assess the effectiveness of comprehensive social support interventions. Results: A total of 201 patients were recruited into the study. Compared with the control group, social support for patients in the intervention group increased significantly over time (β_group*time=0.61, P<0.01) in the following three dimensions: objective support (β_group*time=0.15, P<0.05), subjective support (β_group*time=0.32, P<0.05) and support utilisation (β_group*time=0.16, P<0.05). The change in the scores in the control group was not statistically significant. Conclusions: The intervention programme in communities, including health education, psychotherapy and family and community support interventions, can improve the social support for elderly patients with TB compared with single health education. Trial registration number: ChiCTR-IOR-16009232

A 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. The 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. A 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. The 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.

The incidence of tuberculosis (TB) and its risk factors in China remains unclear. This study examined TB incidence and relative risk factors in rural areas of China. Participants (n = 177,529) were recruited in Xiangtan County (in the central area of China) and in Danyang County (in the eastern area of China) in 2009 and a followed-up study was conducted for one year. The incidence density of pulmonary TB and smear-positive TB were 91.6 (95% CI: 78.7, 106.0) per 100,000 person-year and 36.7 (95% CI: 33.1, 52.4) per 100,000 person-year respectively in Xiangtan, and 47.3 (95% CI: 38.2, 57.5) per 100,000 person-year and 22.7 (95% CI: 16.5, 30.8) per 100,000 person-year in Danyang. The medical history of TB was associated with TB, with the relative risk (RR) of 7.00 (95% CI: 2.76, 17.18) in Xiangtan and that of 31.08 (95% CI: 13.22, 73.10) in Danyang. The association between TB and per capita living space over median was found in Xiangtan, with the RR of 1.86 (95% CI: 1.15, 3.01). No association was found between TB and the insurance status, the contact history with TB, the history of diabetes, smoking, or per capita annual income. The host genetic susceptibility, and social factors such as education and income could be considered in future studies.

Few studies have examined, in a prospective cohort study, factors causing delay of access to tuberculosis (TB) diagnosis among new, active TB patients. A prospective cohort study (2009-2011) was carried out among 408 889 Chinese. Data on known/potential influencing factors were obtained from baseline questionnaires. We used stepwise logistic regression models to analyze the association between several known/potential influencing factors and diagnosis delay, assessed the current situation, and explored determinants of diagnosis delay. During follow-up and final visits, 202 new, active TB patients were found. Median patient delay was 5.4 (quartile 2.7-26) weeks, health system delay was 0 (quartile 0-1.6) weeks, and diagnosis delay was 9.9 (quartile 3.1-28.1) weeks. The influencing factors on patient delay were age and duration of symptoms. Smoking and sputum smear status were influencing factors for health system delay, and duration of symptoms was one of the factors for diagnosis delay. These findings provide information on the current situation of diagnosis delay and evidence for specific strategy development for TB control in China.