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ObjectivesThis study addresses the lack of empirical studies about the epidemic of syphilis among middle-aged female sex workers (FSWs). The objectives of this study were to investigate prevalence of syphilis, and its potential risk factors among middle-aged FSWs in China.DesignA cross-sectional study with respondent-driven sampling (RDS).SettingA multisite study conducted at three Chinese cites (Nanning, Hefei, and Qingdao) with different levels of sexually transmitted diseases in 2014.Participants1245 middle-aged female sex workers who were over 35 years old (about 400 per study site).Main outcome measuresUnprotected commercial sex, and syphilis and HIV infection were biologically tested and measured.ResultsThe RDS-adjusted prevalence of active syphilis was 17.3% in Hefei, 9.9% in Qingdao, and 5.4% in Nanning. The RDS-adjusted prevalence of prevalent syphilis was between 6.8% and 33.6% in the three cities. The proportion of unprotected sex in the past 48 h verified by the prostate-specific antigen test (PSA) was between 27.8% and 42.4%. Multiple log-binomial regression analyses indicate that middle-aged FSWs who had 5 or more clients in the past week prior to interviews and engaged in unprotected sex were more likely to be active syphilitic cases. Middle-aged FSWs who had rural residency were less likely to be active syphilitic cases.ConclusionsIn contrast with previous studies that reported low prevalence of syphilis and high prevalence of protected sex among FSWs in China, both the prevalence of syphilis and unprotected sex were high among middle-aged FSWs. Evidence-based intervention programmes should be developed and evaluated among this vulnerable population in China and other countries with similar settings.

Abstract Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang.

Abstract Background China is a country that is most seriously affected by hemorrhagic fever with renal syndrome (HFRS) with 90% of HFRS cases reported globally. At present, HFRS is getting worse with increasing cases and natural foci in China. Therefore, there is an urgent need for monitoring and predicting HFRS incidence to make the control of HFRS more effective. In this study, we applied a stochastic autoregressive integrated moving average (ARIMA) model with the objective of monitoring and short-term forecasting HFRS incidence in China. Methods Chinese HFRS data from 1975 to 2008 were used to fit ARIMA model. Akaike Information Criterion (AIC) and Ljung-Box test were used to evaluate the constructed models. Subsequently, the fitted ARIMA model was applied to obtain the fitted HFRS incidence from 1978 to 2008 and contrast with corresponding observed values. To assess the validity of the proposed model, the mean absolute percentage error (MAPE) between the observed and fitted HFRS incidence (1978-2008) was calculated. Finally, the fitted ARIMA model was used to forecast the incidence of HFRS of the years 2009 to 2011. All analyses were performed using SAS9.1 with a significant level of p < 0.05. Results The goodness-of-fit test of the optimum ARIMA (0,3,1) model showed non-significant autocorrelations in the residuals of the model (Ljung-Box Q statistic = 5.95,P = 0.3113). The fitted values made by ARIMA (0,3,1) model for years 1978-2008 closely followed the observed values for the same years, with a mean absolute percentage error (MAPE) of 12.20%. The forecast values from 2009 to 2011 were 0.69, 0.86, and 1.21per 100,000 population, respectively. Conclusion ARIMA models applied to historical HFRS incidence data are an important tool for HFRS surveillance in China. This study shows that accurate forecasting of the HFRS incidence is possible using an ARIMA model. If predicted values from this study are accurate, China can expect a rise in HFRS incidence.

Abstract Background Female commercial sex workers (FSWs) are at high risk of human immunodeficiency virus (HIV) transmission in China. This study was designed to examine the predictors of condom use with clients during vaginal intercourse among FSWs based on the Information-Motivation-Behavioral Skills (IMB) model and to describe the relationships between IMB model constructs. Methods A cross-sectional study was conducted in Jinan of Shandong Province, from May to October, 2009. Participants (N = 432) were recruited using Respondent-Driven Sampling (RDS). A self-administered questionnaire was used to collect data. Structural equation modeling was used to assess the IMB model. Results A total of 427 (98.8%) participants completed their questionnaires. Condom use was significantly predicted by social referents support, experiences with and attitudes toward condoms, self-efficacy, and health behaviors and condom use skills. Significant indirect predictors of condom use mediated through behavioral skills included HIV knowledge, social referents support, and substance use. Conclusions These results suggest that the IMB model could be used to predict condom use among Chinese FSWs. Further research is warranted to develop preventive interventions on the basis of the IMB model to promote condom use among FSWs in China.