Therapeutics Information and Pharmacovigilance Centre | TIPC
A Resource Book of Inclusive Practices
2nd edition - Published in 2003, the first WHO/HAI medicine prices manual Medicine Prices – A
New Approach to Measurement Draft for field-testing provides a draft methodology and tools to conduct national medicine prices and availability surveys. This second edition of the survey manual has been... updated to reflect the wealth of practical
experience in conducting medicine prices and availability surveys garnered in the project’s first two phases.
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This handbook reflects and updates the work that ECLAC has done in recent decades to establish a methodology for estimating the economic consequences of a disaster, and thus determine the financing required to rebuild and return the affected area to normal. The handbook's third edition strengthens p...rocedures for estimating the effects of disasters, for distinguishing between losses and additional costs and systematizing the links that exist between different sectors of the economy
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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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DHS Further Analysis Reports No. 109 - This report documents trends in key child nutrition indicators in Rwanda. Data from the Demographic and Health Surveys (DHS) in 2005, 2010, and 2014-15 were analyzed, disaggregated by selected equity-related variables, and tested for trends. Over the survey per...iod, Rwanda had high rates of exclusive breastfeeding, with regional variation. Rates of continued breastfeeding were also high but generally decreased as mother’s education and household wealth increased in all survey years. Complementary feeding practices varied by region, mother’s education, household wealth, urban-rural residence, and sex of the child.
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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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Vision 2030
Accessed: 17.11.2019