Policy and Legal Opportunities for HIV Testing Services and Civil Society Engagement
Module 5
Monitoring and Evaluation
October 2018
Module 5: Monitoring and evaluation. This module is for people responsible for monitoring PrEP programmes at the national and site levels. It provides information on how to monitor PrEP for safety and effectiveness, suggesting core and additiona...l indicators for site-level, national and global reporting.
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The 2019 SLDHS is a national sample survey that provides up-to-date information on demographic and health indicators. The sample was selected using a stratified, two-stage cluster design, with enumeration areas (EAs) as the sampling units for the first stage. The second stage was a complete listing ...of households carried out in each of the 578 selected EAs. The target groups were women age 15-49 and men age 15-59 in
randomly selected households across the country. A representative sample of approximately 13,872 households was selected for the survey. Half of the households (6,936) were selected for biomarker and men’s interview. The men’s survey was conducted in half (50%) of the sample households, and all men age 15-59 in these households were included. In this subsample, one eligible woman in each household was randomly selected to be asked additional questions about domestic violence.
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SRHR, HIV AND AIDS Governance Manual
Towards the Elimination of Mother-to-Child Transmission of HIV and keeping mothers Alive. 2012-2015
Conflict and Health 2015, 9:8 doi:10.1186/s13031-015-0035-8
Follow up to the Maseru Declaration. ZIMBABWE COUNTRY REPORT
Reporting Period: January 2013 - December 2013
The Haiti Earthquake and Cholera Emergency appeal (MDRHT018) was implemented by the International Federation of Red Cross and Red Crescent Societies (IFRC) in collaboration with the Haitian Red Cross Society (HRCS) following the devastating earthquake on 14 August 2021, and the cholera outbreak on 2... October 2022.
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DHS Further Analysis Reports No 102
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.
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