BACKGROUND National or regional population-based HIV prevalence surveys have small sample sizes at district or sub-district levels; this leads to wide confidence intervals when estimating HIV prevalence at district level for programme monitoring and decision making. Health facility programme data, collected during service delivery is widely available, but since people self-select for HIV testing, HIV prevalence estimates based on it, is subject to selection bias. We present a statistical annealing technique, Hybrid Prevalence Estimation (HPE), that combines a small population-based survey sample with a facility-based sample to generate district level HIV prevalence estimates with associated confidence intervals. METHODS We apply the HPE methodology to combine the 2011 Uganda AIDS indicator survey with the 2011 health facility HIV testing data to obtain HIV prevalence estimates for districts in Uganda. Multilevel logistic regression was used to obtain the propensity of testing for HIV in a health facility, and the propensity to test was used to combine the population survey and health facility HIV testing data to obtain the HPEs. We assessed comparability of the HPEs and survey-based estimates using Bland Altman analysis. RESULTS The estimates ranged from 0.012 to 0.178 and had narrower confidence intervals compared to survey-based estimates. The average difference between HPEs and population survey estimates was 0.00 (95% CI - 0.04, 0.04). The HPE standard errors were 28.9% (95% CI 23.4-34.4) reduced, compared to survey-based standard errors. Overall reduction in HPE standard errors compared survey-based standard errors ranged from 5.4 to 95%. CONCLUSIONS Facility data can be combined with population survey data to obtain more accurate HIV prevalence estimates for geographical areas with small population survey sample sizes. We recommend use of the methodology by district level managers to obtain more accurate HIV prevalence estimates to guide decision making without incurring additional data collection costs.BACKGROUND Both depression and cancer are economically burdensome. However, how depression affects the healthcare expenditures of elderly cancer patients from payers' and patients' perspectives is largely unknown. This study investigated whether depression resulted in higher healthcare expenditures among these patients from both payers' and patients' perspectives and identified health service use categories associated with increased expenditures. METHODS From the Medicare Current Beneficiary Survey (MCBS)-Medicare database, we identified breast, lung and prostate cancer patients aged 65 years and over who were newly diagnosed between 2007 and 2012.  https://www.selleckchem.com/products/pd-1-pd-l1-inhibitor-3.html  Presence of depression was based on self-reports from the surveys. We used generalized linear models (GLM) and two-part models to examine the impact of depression on healthcare expenditures during the first two years of cancer diagnosis controlling for a vast array of covariates. We stratified the analyses of total healthcare expenditures by healthcare services and payers. RESULTS Out of the 710 elderly breast, lung and prostate cancer patients in our study cohort, 128 (17.7%) reported depression. Individuals with depression had $11,454 higher total healthcare expenditures, $8213 higher medical provider expenditures and $405 higher other services expenditures compared to their counterparts without depression. Also, they were significantly more likely to have inpatient services. For payers, they incurred $8280 and $1270 higher expenditures from Medicare's and patients' perspectives, respectively. CONCLUSIONS Elderly cancer patients with depression have significantly higher healthcare expenditures from both payers' and patients' perspectives and over different expenditure types. More research is needed in depression screening, diagnosis and treatment for this population.BACKGROUND The study aims at identifying long-term trends and patterns of current smoking by age, gender, and education in Russia, including the most recent period from 2008 during which tobacco control policies were implemented, and to estimate the impact on mortality of any reductions in prevalence. We present an in-depth analysis based on an unprecedentedly large array of survey data. METHODS We examined pooled micro-data on smoking from 17 rounds of the Russian Longitudinal Monitoring Study of 1996-2016, 11 other surveys conducted in Russia in 1975-2017, and two comparator surveys from England and the USA. Standardization by age and education, regression and meta-analysis were used to estimate trends in the prevalence of current smoking by gender, age, and educational patterns. RESULTS From the mid-1970s to the mid-2000s smoking prevalence among men was relatively stable at around 60%, after which time prevalence declined in every age and educational group. Among women, trends in smoking were more heterogmortality seen in Russia since 2005.BACKGROUND Ubiquitously distributed benzene is a known hematotoxin. Increasing evidence has suggested that erythroid-related hematologic parameters may be sensitive to benzene exposure. Fat content, which is also closely associated with erythroid-related hematologic parameters, may affect the distribution and/or metabolism of benzene, and eventually benzene-induced toxicity. METHODS To explore the influence of benzene exposure, fat content, and their interactions on erythroid-related hematologic parameters, we recruited 1669 petrochemical workers and measured their urinary S-phenylmercapturic acid (SPMA) concentration and erythroid-related hematological parameters. Indices for fat content included body fat percentage (BF%), plasma total cholesterol (TC) and triglycerides (TG), and occurrence of fatty liver. RESULTS The dose-response curve revealed U-shaped nonlinear relationships of SPMA with hematocrit (HCT) and mean corpuscular hemoglobin concentration (MCHC) (P-overall less then  0.001, and P-nonlinear less then  0.015), as well as positive linear associations and r-shaped nonlinear relationships of continuous fat content indices with erythroid-related hematological parameters (P-overall ≤0.005). We also observed modification effects of fat content on the associations between benzene exposure and erythroid-related hematological parameters, with workers of lower or higher BF% and TG more sensitive to benzene-induced elevation of MCHC (Pinteraction = 0.021) and benzene-induced decrease of HCT (Pinteraction = 0.050), respectively. We also found that some erythroid-related hematologic parameters differed between subgroups of workers with different SPMA levels and fat content combination. CONCLUSIONS Our study suggested that benzene exposure, fat content, and their interactions may affect erythroid-related hematological parameters in petrochemical workers in a complex manner that are worthy of further investigation.