We investigated the migration patterns of hepatitis C virus (HCV) in China. Partial E1 and/or NS5B sequences from 411 volunteer blood donors sampled in 17 provinces and municipalities located in five large regions, the north-northeast, northwest, southwest, central south, and southeast, were characterized. The sequences were classified into eight subtypes (1a, n ‫؍‬ 3; 1b, n ‫؍‬ 183; 2a, n ‫؍‬ 83; 3a, n ‫؍‬ 30; 3b, n ‫؍‬ 44; 6a, n ‫؍‬ 55; 6n, n ‫؍‬ 10; 6v, n ‫؍‬ 1) and a new subtype candidate. Bayesian evolutionary analysis by sampling trees of the E1 sequences of the five major subtypes revealed distinct migration patterns. Subtype 1b showed four groups: one is prevalent nationwide with possible origins in the north-northeast; two are locally epidemic in the central south and northwest, respectively, and have spread sporadically to other regions; and the fourth one is likely linked to the long-distance dispersion among intravenous drug users from the northwest. Subtype 2a showed two groups: the larger one was mainly restricted to the northwest and seemed to show a trend toward migration via the Silk Road; the smaller one was geographically mixed and may represent descendants of those that spread widely during the contaminated plasma campaign in the 1990s. Subtype 3a exhibited three well-separated geographic groups that may be epidemically unrelated: one showed origins in the northwest, one showed origins in the southwest, and the other showed origins in the central south. In contrast, subtype 3b had a mixture of geographic origins, suggesting migrations from the southwest to the northwest and sporadically to other regions. Structurally resembling the tree for subtype 3a, the tree for subtype 6a showed four groups that may indicate migrations from the central south to southeast, southwest, and northwest. Strikingly, no subtype 6a strain was identified in the north-northeast. IMPORTANCEWith a population of greater than 1.3 billion and a territory of >9.6 million square kilometers, China has a total of 34 provinces and municipalities. In such a vast country, the epidemic history and migration trends of HCV are thought to be unique and complex but variable among regions and are unlikely to be represented by those observed in only one or at best a few provinces and municipalities. However, due to the difficulties in recruiting patients, all previous studies for this purpose have been based only on data from limited regions, and therefore, geographical biases were unavoidable. In this study, such biases were greatly reduced because we utilized samples collected from volunteer blood donors in 17 provinces and municipalities. To our knowledge, this is the first study in which the HCV isolates represented such a large portion of the country, and thus, the results should shed light on the current understanding of HCV molecular epidemiology.

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Qualified donations after routine blood donor screening still carry potential risk for transmitting HEV. HEV antigen screening could be one measure to reduce the risk of HEV transmission by blood transfusion.

Whether B19 NAT screening of blood and blood products should be launched in China, larger studies are needed to facilitate an informed decision.

Background There is little data on HIV prevalence, incidence or residual risks for transfusion transmitted HIV infection among Chinese blood donors. Methods Donations from five Chinese blood centers in 2008–2010 were screened using two rounds of ELISA testing for anti-HIV-1/2. A reactive result in either or both rounds led to Western Blot confirmatory testing. HIV prevalence and demographic correlates among first time donors, incidence rate and demographic correlates among repeat donors were examined. Weighted multivariable logistic regression analysis examined correlates of HIV confirmatory status among first time donors. Residual risks for transfusion transmitted HIV infection were evaluated based on incidence among repeat donors. Results Among 821,320 donations, 40% came from repeat donors.1,837 (0.34%) first time and 577 (0.17%) repeat donations screened reactive for anti-HIV-1/2, among which 1,310 and 419 were tested by Western Blot. 233 (17.7%) first time and 44 (10.5%) repeat donations were confirmed positive. Estimated prevalence was 66 infections per 100,000 (95% CI: 59–74) first time donors. Estimated incidence was 9/100,000 (95% CI: 7–12) person-years among repeat donors. Weighted multivariable logistic regression analysis indicate that first time donors 26–45 years old were 1.6–1.8 times likely to be HIV positive than those 25 years and younger. Donors with some college or above education were less likely to be HIV positive than those with middle school education, ORs ranging from 0.35 to 0.60. Minority were 1.6 times likely to be HIV positive than Han majority donors (OR: 1.6; CI: 1.2–2.1). No difference in prevalence was found between gender. Current HIV TTI residual risk was 5.4 (1.2–12.5) infections per million whole blood donations. Conclusion Despite the declining HIV epidemic China, estimated residual risks for transfusion transmitted HIV infection are still high, highlighting the potential blood safety yield of NAT implementation in donation screening.

Despite a steady increase in total blood collections and voluntary non-remunerated blood donors, China continues to have many challenges with its blood donation system. The country's donation rate remains low at 9‰, with over 60% of donors being first-time donors. Generally there is a lack of adequate public awareness about blood donation. The conservative donor selection criteria, the relatively long donation interval, and the small donation volume have further limited blood supply. To ensure a sufficient and safe blood supply that meets the increasing clinical need for blood products, there is an urgent need to strengthen the country's blood donor management. This comprehensive effort should include educating and motivating more individuals especially from the rural areas to be involved in blood donation, developing rational and evidence-based selection criteria for donor eligibility, designing a donor follow-up mechanism to encourage more future donations, assessing the current donor testing strategy, improving donor service and care, building regional and national shared donor deferral database, and enhancing the transparency of the blood donation system to gain more trust from the general public. The purpose of the review is to provide an overview of the key process of and challenges with the blood donor management system in China.

In China compared to the United States, donations are made by younger donors and donors give infrequently and make smaller WB donations. To help ensure supply adequacy, continued efforts are needed to have donors give larger volumes of WB in China.

Passively-generated data, such as GPS data and cellular data, bring tremendous opportunities for human mobility analysis and transportation applications. Since their primary purposes are often nontransportation related, the passively-generated data need to be processed to extract trips. Most existing trip extraction methods rely on data that are generated via a single positioning technology such as GPS or triangulation through cellular towers (thereby called single-sourced data), and methods to extract trips from data generated via multiple positioning technologies (or, multi-sourced data) are absent. And yet, multi-sourced data are now increasingly common. Generated using multiple technologies (e.g., GPS, cellular network-and WiFi-based), multi-sourced data contain high variances in their temporal and spatial properties. In this study, we propose a "Divide, Conquer and Integrate" (DCI) framework to extract trips from multi-sourced data. We evaluate the proposed framework by applying it to an app-based data, which is multi-sourced and has high variances in both location accuracy and observation interval (i.e. time interval between two consecutive observations). On a manually labeled sample of the app-based data, the framework outperforms the state-of-the-art SVM model that is designed for GPS data. The effectiveness of the framework is also illustrated by consistent mobility patterns obtained from the app-based data and an externally collected household travel survey data for the same region and the same period.