简介：AbstractBackground:Despite almost two decades of well-funded and comprehensive response efforts by the Chinese Government, human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) remains a major problem in China. Yet, few studies have recently examined long-term trends in HIV/AIDS prevalence, incidence, and mortality at the national level. This study aimed to determine the prevalence, incidence, and mortality trends for HIV/AIDS over the past 28 years in China.Methods:We conducted a descriptive, epidemiological, secondary analysis of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 data. To evaluate trends in prevalence, incidence, and mortality over the study period from 1990 to 2017, we calculated values for annual percentage change (APC) and corresponding 95% confidence intervals (CIs) using joinpoint regression analysis.Results:A significant increase in HIV/AIDS prevalence was observed for 1990 to 2009 (APC: 10.7; 95% CI: 10.4, 11.0; P < 0.001), and then remained stable for 2009 to 2017 (APC: 0.7; 95% CI: -0.3, 1.7; P = 0.1). A significant increase in HIV incidence was also observed for 1990 to 2005 (APC: 13.0; 95% CI: 12.6, 13.4; P < 0.001), and then a significant decrease was detected for 2005 to 2017 (APC: -6.5; 95% CI: -7.0, -6.1; P < 0.001). A significant increase in AIDS-related mortality rate was detected for 1990 to 2004 (APC: 10.3; 95% CI: 9.3, 11.3; P < 0.001), followed by a period of stability for 2004 to 2013 (APC: 1.3; 95% CI: -0.7, 3.3; P = 0.2), and then another significant increase for 2013 to 2017 (APC: 15.3; 95% CI: 8.7, 22.2; P < 0.001).Conclusions:Although prevalence has stabilized and incidence has declined, AIDS-related mortality has risen sharply in recent years. These findings suggest more must be done to bring people into treatment earlier, retain them in treatment more effectively, actively seek to reenter them in treatment if they dropout, and improve the quality of treatment and care regimens.

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简介：AbstractBackground:As COVID-19 makes its way around the globe, each nation must decide when and how to respond. Yet many knowledge gaps persist, and many countries lack the capacity to develop complex models to assess risk and response. This paper aimed to meet this need by developing a model that uses case reporting data as input and provides a four-tiered risk assessment output.Methods:We used publicly available, country/territory level case reporting data to determine median seeding number, mean seeding time (ST), and several measures of mean doubling time (DT) for COVID-19. We then structured our model as a coordinate plane with ST on the x-axis, DT on the y-axis, and mean ST and mean DT dividing the plane into four quadrants, each assigned a risk level. Sensitivity analysis was performed and countries/territories early in their outbreaks were assessed for risk.Results:Our main finding was that among 45 countries/territories evaluated, 87% were at high risk for their outbreaks entering a rapid growth phase epidemic. We furthermore found that the model was sensitive to changes in DT, and that these changes were consistent with what is officially known of cases reported and control strategies implemented in those countries.Conclusions:Our main finding is that the ST/DT Model can be used to produce meaningful assessments of the risk of escalation in country/territory-level COVID-19 epidemics using only case reporting data. Our model can help support timely, decisive action at the national level as leaders and other decision makers face of the serious public health threat that is COVID-19.