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
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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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The DHS report itself explains the purpose was, “to obtain and provide information on basic indicators of social progress including fertility, childhood mortality, reproductive and child health, nutritional status of children, and awareness of HIV
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/AIDS and other health-related issues” in PNG. This is important because a DHS then provides the evidence base for PNG officials themselves to track progress in PNG over time, compare trends with other comparable countries, and then allocate financial and human resources to where they are needed most.
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The LDHS provides an opportunity to inform policy and provide data for planning, implementation, and monitoring and evaluation of national health programs. It is designed to provide up-to-date information on health indicators including fertility levels, sexual activity, fertility preferences, awaren
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ess and use of family
planning methods, breastfeeding practices, nutritional status of children, early childhood and maternal mortality, maternal and child health, and awareness and behaviors regarding HIV/AIDS and other sexually transmitted infections. The study also incorporated measurements of HIV, hepatitis B, and hepatitis Cprevalence along with seroprevalence of Ebola virus disease antibodies, the results of which will be included in future addendums. In addition to presenting national estimates, the report provides estimates of key indicators for both rural and urban areas, the country’s 15 counties, and the capital, Monrovia.
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The intended purpose of this compendium is to provide program managers, organizations, and policy makers with a menu of indicators to better “know their HIV epidemic/know their response” from a gender perspective. The indicators in the compendiu
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m are all either part of existing indicators used in studies or by countries or have been adapted from existing indicators to address the intersection of gender and HIV. The indicators can be measured through existing data collection and information systems (e.g. routine program monitoring, surveys) in most country contexts, though some may require special studies or research.
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The 2015-16 MDHS is a national sample survey that provides up-to-date information on fertility levels; marriage; fertility preferences; awareness and use of family planning methods; child feeding practices; nutrition; adult and childhood mortality; awareness and attitudes regarding HIV/AIDS; women
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s empowerment; and domestic violence. The target groups were women and men age 15-49 residing in randomly selected households across the country. In addition to national estimates, the report provides estimates of key indicators for both urban and rural areas in Myanmar and also for the 15 states and regions.
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DHS Comparative Reports No. 42
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delivery, and timely postnatal care (PNC).This s
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tudy uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12regions.We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use.We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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Barriers to the prompt and effective diagnosis and treatment of malaria exist at both the community and health facility level. Household surveys measure malaria case management at the population level with standard indicators that assess treatment-s
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eeking behavior, access to diagnostic testing, and access to appropriate treatment. Performance on these indicators varies widely from country to country. Among countries with Demographic and Health Surveys (DHS) or Malaria Indicator Surveys (MIS) completed between 2014 and 2016, advice and treatment was sought for a median of 47% of children under age 5 with fever.
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The objective of the evaluation is to understand whether the CHW program has achieved its intended objectives, thus contributing to the overarching objectives defined in the HSSP III of improving the health status of the population by “Ensuring un
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iversal accessibility of quality health services for all Rwandans”.
This evaluation has focused on CHWs, who are selected, trained and deployed by the MoH to deliver a defined set of tasks at community level. CHWs are the central element of the Community Health Policy and of the community health strategy plan (CHSP) of the MoH.
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