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Publication Years
798
2286
305
9
Category
1590
236
226
159
148
101
16
2
Toolboxes
432
297
184
112
101
90
57
55
51
50
46
40
40
39
38
34
31
26
24
20
11
11
10
4
2
1
Monitoring and Evaluation Toolkit: HIV, TB and Malaria and Health Systems Strenghtening
The Global Fund
(2011)
The TB section of the toolkit presents selected (a) programmatic output and (b) outcome and impact indicators for TB. In addition to recommended monitoring programs and measuring the outcomes and impact of TB programs, indicators for the strengthening of health systems, strengthening of community sy
...
stems and some indicators that measure quality of services are also included.
more
This publication by UNAIDS, UNDP and the International Organisation for Migration examines various dimensions related to migration and HIV and AIDS.
HIV Prevalence Patterns by Age and sex: Exploring Differences among 19 Countries
Chaitra Gopalappa, John Stover & Carel Pretorius
ICF International Calverton, Maryland, USA
(2013)
C2
DHS Analytical Studies No. 40
DHS Working Papers No. 111 | Zimbabwe Working Papers No. 12
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 miscl
...
assification 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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Poverty, HIV and other disease burdens, coupled with common mental disorders including alcohol and other substance use disorders, posttraumatic stress disorder, clinical and postnatal depression, distress, and anxiety, impact how caregivers meet the
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needs of children. When mental health is not considered or addressed, there can be a significant impact on an individual, their family and the community.
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