Journal of HIV AIDS surveillance & epidemiology最新文献

{"title":"Factors associated with repeated refusal to participate in longitudinal population-based HIV surveillance in rural South Africa: an observational study, regression analyses.","authors":"Katie Giordano, Till Bärnighausen, Nuala McGrath, Rachel Snow, Siobán Harlow, Marie-Louise Newell","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>For many estimation purposes, individuals who repeatedly refuse to participate in longitudinal HIV surveillance pose a bigger threat to valid inferences than individuals who participate at least occasionally. We investigate the determinants of repeated refusal to consent to HIV testing in a population-based longitudinal surveillance in rural South Africa.</p><p><strong>Methods: </strong>We used data from two years (2005 & 2006) of the annual HIV surveillance conducted by the Africa Centre for Health and Population Studies, linking the HIV surveillance data to demographic and socioeconomic data. The outcome for the analysis was \"repeated refusal\". Demographic variables included sex, age, highest educational attainment, and place of residence. We also included a measure of wealth and the variable \"ever had sex\". To compare the association of each variable with the outcome, unadjusted odds ratios and standard errors were estimated. Multivariable logistic regression was used to estimate adjusted odds ratios and their standard errors. Data were analyzed using STATA 10.0.</p><p><strong>Results: </strong>Of 15,557 eligible individuals, 46% refused to test for HIV in both rounds. Males were significantly more likely than females to repeatedly refuse testing. Holding all other variables constant, individuals in the middle age groups were more likely to repeatedly refuse testing compared with younger and older age groups. The odds of repeated refusal increased with increasing level of education and relative wealth. People living in urban areas were significantly more likely to repeatedly refuse an HIV test than people living in peri-urban or rural areas. Compared to those who had ever had sex, both males and females who had not yet had sex were significantly more likely to refuse to participate.</p><p><strong>Conclusions: </strong>The likelihood of repeated refusal to test for HIV in this longitudinal surveillance increases with education, wealth, urbanization, and primary sexual abstinence. Since the factors determining repeated HIV testing refusal are likely associated with HIV status, it is critical that selection effects are controlled for in the analysis of HIV surveillance data. Interventions to increase consent to HIV testing should consider targeting the relatively well educated and wealthy, people in urban areas, and individuals who have not yet sexually debuted.</p>","PeriodicalId":89415,"journal":{"name":"Journal of HIV AIDS surveillance & epidemiology","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33327867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating HIV Incidence in Populations Using Tests for Recent Infection: Issues, Challenges and the Way Forward.","authors":"Timothy D Mastro, Andrea A Kim, Timothy Hallett, Thomas Rehle, Alex Welte, Oliver Laeyendecker, Tom Oluoch, Jesus M Garcia-Calleja","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>INTRODUCTION: HIV incidence is the rate of new infections in a population over time. HIV incidence is a critical indicator needed to assess the status and trends of the HIV epidemic in populations and guide and assess the impact of prevention interventions. METHODS: Several methods exist for estimating population-level HIV incidence: direct observation of HIV incidence through longitudinal follow-up of persons at risk for new HIV infection, indirect measurement of HIV incidence using data on HIV prevalence and mortality in a population, and direct measurement of HIV incidence through use of tests for recent infection (TRIs) that can differentiate \"recent\" from \"non-recent\" infections based on biomarkers in cross-sectional specimens. Given the limitations in measuring directly observed incidence and the assumptions needed for indirect measurements of incidence, there is an increasing demand for TRIs for HIV incidence surveillance and program monitoring and evaluation purposes. RESULTS: Over ten years since the introduction of the first TRI, a number of low-, middle-, and high-income countries have integrated this method into their HIV surveillance systems to monitor HIV incidence in the population. However, the accuracy of these assays for measuring HIV incidence has been unsatisfactory to date, mainly due to misclassification of chronic infections as recent infection on the assay. To improve the accuracy of TRIs for measuring incidence, countries are recommended to apply case-based adjustments, formula-based adjustments using local correction factors, or laboratory-based adjustment to minimize error related to assay misclassification. Multiple tests may be used in a recent infection testing algorithm (RITA) to obtain more accurate HIV incidence estimates. CONCLUSION: There continues to be a high demand for improved TRIs and RITAs to monitor HIV incidence, determine prevention priorities, and assess impact of interventions. Current TRIs have noted limitations, but with appropriate adjustments, interpreted in parallel with other epidemiologic data, may still provide useful information on new infections in a population. New TRIs and RITAs with improved accuracy and performance are needed and development of these tools should be supported.</p>","PeriodicalId":89415,"journal":{"name":"Journal of HIV AIDS surveillance & epidemiology","volume":"2 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3130510/pdf/nihms283044.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29995707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}