This report investigates the impact of potential misclassification of samples on HIV prevalence estimates for 23 surveys conducted from 2010-2014. In addition to visual inspection of laboratory results, we examined how accounting for potential misclassification of HIV status through Bayesian latent ...class models affected the prevalence estimates. Two types of Bayesian models were specified: a model that only uses the individual dichotomous test results and a continuous model that uses the quantitative information of the EIA (i.e., the signal-to-cutoff values). Overall, we found that adjusted prevalence estimates matched the surveys’ original results, with overlapping uncertainty intervals. This suggested that misclassification of HIV status should not affect the prevalence estimates in most surveys. However, our analyses suggested that two surveys may be problematic. The prevalence could have been overestimated in the Uganda AIDS Indicator Survey 2011 and the Zambia Demographic and Health Survey 2013-14, although the magnitude of overestimation remains difficult to ascertain. Interpreting results from the Uganda survey is difficult because of the lack of internal quality control and potential violation of the multivariate normality assumption of the continuous Bayesian latent class model. In conclusion, despite the limitations of our latent class models, our analyses suggest that prevalence estimates from most of the surveys reviewed are not affected by sample misclassification.
more
This is the story of how an experiment in the north of Ghana changed the health of a nation. How health staff in remote and rural areas are working tirelessly to prevent the deaths of mothers and children. How a radical approach to health research, known as embedded research, has revolutionized how ...the government delivers health services under difficult circumstances.
more
FOLLOW-UP TO THE 2011 POLITICAL DECLARATION ON HIV/AIDS: INTENSIFYING EFFORTS TO ELIMINATE HIV/AIDS | Reporting Period: January – December 2014
DHS Working Papers No. 103
No publication date indicated.
Chronic Dis Int - Volume 3 Issue 1 - 2016
ISSN 2379-7983