Biru Yang

Late HIV diagnosis in Houston/Harris County, Texas, 2000-2007.

Abstract This cross-sectional study aimed to evaluate the prevalence and predictive factors associated with late HIV diagnoses in Houston, Texas using surveillance data. Study subjects were Houston/Harris County residents, 13 years or older, diagnosed with HIV and reported to the Houston Department of Health and Human Services. Late HIV diagnosis was defined as an AIDS diagnosis within three months of an HIV diagnosis. Logistic regression was used to investigate the association between late HIV diagnoses and predictive factors. We found 31% of the study population had late HIV diagnoses. The Hispanic population, men, older individuals, heterosexuals, and those diagnosed in private facilities were more likely to receive late HIV diagnoses. Sensitivity analysis was conducted to evaluate the effect of time from HIV to AIDS diagnosis on the prevalence of a late diagnosis, and on the predictors of late diagnosis. The sensitivity analysis showed time affects prevalence, but not the odds ratios of the risk factors for late diagnosis. This finding suggests HIV prevention programs should specifically target these populations at risk for late HIV diagnosis to encourage frequent HIV testing.

Characteristics and risk of syphilis diagnosis among HIV-infected male cohort: a population-based study in Houston, Texas.

Background This population-based study assessed the characteristics, timing, and risk of syphilis diagnoses among HIV-infected males in Houston, Texas. Methods A retrospective cohort of males newly diagnosed as having HIV between January 2000 and December 2002 was constructed using HIV surveillance data. These individuals were cross-referenced to sexually transmitted disease surveillance data to ascertain early syphilis diagnoses for the subsequent 10 years. Multivariable Cox regression was used to identify risk factors for syphilis diagnosis while controlling for the effects of covariates. Results Approximately 6% of the HIV-infected male cohort received early syphilis diagnoses during a 10-year period. Of these comorbid individuals, 40.8% received an incident syphilis diagnosis 5 years or more after their HIV diagnosis. Men who have sex with men (MSM) transmission risk was associated with significantly increased hazard of having a syphilis diagnosis in multivariable analysis (adjusted hazard ratio [HR] of a syphilis diagnosis, 5.24; 95% confidence interval, 3.41–8.05). Compared with men who were older than 40 years at HIV diagnosis, those 13 to 19 years old were 4.06 (2.18–7.55) times more likely to obtain a syphilis diagnosis. The HRs of having an HIV-syphilis comorbidity decreased as age increased. Compared with whites, non-Hispanic African Americans had 1.59 (1.11–2.26) times increased risk of having a subsequent syphilis diagnosis. Risk-stratified HRs showed that MSM had an increased risk of contracting syphilis in all race/ethnicity and age groups. Conclusions This study suggests that HIV-positive African Americans, youth, and MSM had increased risk of having a subsequent syphilis diagnosis. Targeting these groups with STI prevention messaging may be beneficial to reducing comorbidity.

Modeling and Forecasting Influenza-like Illness (ILI) in Houston, Texas Using Three Surveillance Data Capture Mechanisms

Objective The objective was to forecast and validate prediction estimates of influenza activity in Houston, TX using four years of historical influenza-like illness (ILI) from three surveillance data capture mechanisms. Background Using novel surveillance methods and historical data to estimate future trends of influenza-like illness can lead to early detection of influenza activity increases and decreases. Anticipating surges gives public health professionals more time to prepare and increase prevention efforts. Methods Data was obtained from three surveillance systems, Flu Near You, ILINet, and hospital emergency center (EC) visits, with diverse data capture mechanisms. Autoregressive integrated moving average (ARIMA) models were fitted to data from each source for week 27 of 2012 through week 26 of 2016 and used to forecast influenza-like activity for the subsequent 10 weeks. Estimates were then compared to actual ILI percentages for the same period. Results Forecasted estimates had wide confidence intervals that crossed zero. The forecasted trend direction differed by data source, resulting in lack of consensus about future influenza activity. ILINet forecasted estimates and actual percentages had the least differences. ILINet performed best when forecasting influenza activity in Houston, TX. Conclusion Though the three forecasted estimates did not agree on the trend directions, and thus, were considered imprecise predictors of long-term ILI activity based on existing data, pooling predictions and careful interpretations may be helpful for short term intervention efforts. Further work is needed to improve forecast accuracy considering the promise forecasting holds for seasonal influenza prevention and control, and pandemic preparedness.

Investigating Informatics Activity, Control, and Training Needs in Large, Medium, and Small Health Departments.

This article investigates informatics training needs in local health departments of different jurisdictional sizes.

Association between Influenza-like Illnesses and Social Determinants of Health by Census Tract in Houston/Harris County

The Houston Department of Health Department of Health and Human Services (HDHHS) monitors emergency departments (ED) chief complaints across the Houston metropolitan area, Harris County, and the surrounding jurisdictions by Real-time Outbreak Disease Surveillance (RODS). The influenza-like illnesses (ILI) data is collected by sentinel surveillance provider network of 12 physicians and RODS, an electronic syndromic surveillance database consisting of about 30 EDs in metropolitan Houston. Previous research indicates that there is a relationship between new HIV diagnoses and neighborhood poverty. However, there is limited research on health disparity to investigate the association between influenza-like illnesses (ILI) and social determinants of health (SDH), such as poverty. This cross-sectional study investigates the relationship between ILI and SDH.