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BackgroundIn 2005, China established an internet-based Tuberculosis Information Management System (TBIMS) to monitor changes in tuberculosis (TB). Many scholars have conducted epidemiological research using TBIMS; however, few studies assessing control strategies have been performed based on this platform data. Henan province is a high TB incidence area in China where, in addition to following the nationwide TB strategies, a series of local intervention combinations have been implemented. ObjectiveOur study aims to evaluate the impact of nationwide TB intervention combinations on epidemiological changes and determine whether Henan province can achieve the World Health Organization’s (WHO) goal of reducing TB incidence by 50% and TB mortality by 75% by the year 2025. MethodsWe used descriptive statistical methods to show the spatial and temporal distribution of pulmonary tuberculosis (PTB) reported to the TBIMS database from 2005 to 2018, and logistic regression analysis was performed to identify the risk factors of bacteriological-positive TB. The dynamic compartmental model and Bayesian melding approach was adopted to estimate the burden of TB under the impact of different TB control policies. ResultsIn total, 976,526 PTB cases were notified to the TBIMS in Henan in a period of 14 years. Although the overall incidence of PTB declined from 91.4/105 to 58.5/105, and the overall incidence of bacteriological-positive PTB declined from 44.5/105 to 14.7/105, the WHO’s 2025 goal could not be met. The distribution of high incidence and poverty-stricken counties were basically overlapped. Men, farmers and herdsmen (in rural areas), and subjects aged ≥60 years were more likely to develop bacteriological-positive PTB. The increasing treatment success for drug-susceptible tuberculosis and multidrug-resistant tuberculosis has not provided the desired reduction in incidence and mortality. ConclusionsTo achieve the targeted goal, while improving the cure rate of TB, new active (rather than passive) detection and intervention strategies should be formulated based on epidemiological characteristics in Henan province.

Canonical correlation analysis (CCA) is a popular statistical tool in multivariate analysis. A regularized version is often used to stabilize the estimate. Motivated by recent interests in sketching estimates for linear regression problems which try to address the computational problem associated with massive data sets, here we investigate the sketched estimation for CCA, which includes the random subsampling approach as a special case. Some theoretical results are established based on perturbation theory. The method is also illustrated via some Monte Carlo studies and a real data analysis. [ABSTRACT FROM AUTHOR]

Generalized Additive Partial Linear Models (GAPLMs) are appealing for model interpretation and prediction. However, for GAPLMs, the covariates and the degree of smoothing in the nonparametric parts are often difficult to determine in practice. To address this model selection uncertainty issue, we develop a computationally feasible Model Averaging (MA) procedure. The model weights are data-driven and selected based on multifold Cross-Validation (CV) (instead of leave-one-out) for computational saving. When all the candidate models are misspecified, we show that the proposed MA estimator for GAPLMs is asymptotically optimal in the sense of achieving the lowest possible Kullback-Leibler loss. In the other scenario where the candidate model set contains at least one quasi-correct model, the weights chosen by the multifold CV are asymptotically concentrated on the quasi-correct models. As a by-product, we propose a variable importance measure to quantify the importances of the predictors in GAPLMs based on the MA weights. It is shown to be able to asymptotically identify the variables in the true model. Moreover, when the number of candidate models is very large, a model screening method is provided. Numerical experiments show the superiority of the proposed MA method over some existing model averaging and selection methods. for this article are available online. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of comparing the population means of two groups of independent observations. An approximate randomization test procedure based on the test statistic of Chen & Qin (2010) is proposed. The asymptotic behaviour of the test statistic, as well as the randomized statistic, is studied under weak conditions. In our theoretical framework, observations are not assumed to be identically distributed even within groups. No condition on the eigenstructure of the covariance matrices is imposed. Furthermore, the sample sizes of the two groups are allowed to be unbalanced. Under general conditions, all possible asymptotic distributions of the test statistic are obtained. We derive the asymptotic level and local power of the approximate randomization test procedure. Our theoretical results show that the proposed test procedure can adapt to all possible asymptotic distributions of the test statistic, always has the correct test level asymptotically and has good power behaviour. Our numerical experiments show that the proposed test procedure has favourable performance compared with several alternative test procedures. [ABSTRACT FROM AUTHOR]

The public health interventions to mitigate coronavirus disease 2019 (COVID‐19) could also potentially reduce the global activity of influenza. However, this strategy's impact on other common infectious diseases is unknown. We collected data of 10 respiratory infectious (RI) diseases, influenza‐like illnesses (ILIs), and seven gastrointestinal infectious (GI) diseases during 2015–2020 in China and applied two proportional tests to check the differences in the yearly incidence and mortality, and case‐fatality rates (CFRs) over the years 2015–2020. The results showed that the overall RI activity decreased by 7.47%, from 181.64 in 2015–2019 to 168.08 per 100 000 in 2020 (p < 0.001); however, the incidence of influenza was seen to have a 16.08% escalation (p < 0.001). In contrast, the average weekly ILI percentage and positive influenza virus rate decreased by 6.25% and 61.94%, respectively, in 2020 compared to the previous 5 years (all p < 0.001). The overall incidence of GI decreased by 45.28%, from 253.73 in 2015–2019 to 138.84 in 2020 per 100 000 (p < 0.001), and with the greatest decline seen in hand, foot, and mouth disease (HFMD) (64.66%; p < 0.001). The mortality and CFRs from RI increased by 128.49% and 146.95%, respectively, in 2020, compared to 2015–2019 (p < 0.001). However, the mortality rates and CFRs of seven GI decreased by 70.56% and 46.12%, respectively (p < 0.001). In conclusion, China's COVID‐19 elimination/containment strategy is very effective in reducing the incidence rates of RI and GI, and ILI activity, as well as the mortality and CFRs of GI diseases. Key Points: COVID‐19 elimination strategy in China decreased the activity of respiratory infectious diseases (RI) and influenza‐like illnesses. A 16.08% escalation was seen in influenza in 2020 compared to 2015–2019. The mortality of RI increased slightly in 2020 compared to 2015–2019. COVID‐19 elimination strategy in China decreased dramatically the activity and mortality of gastrointestinal infectious diseases. [ABSTRACT FROM AUTHOR]