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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Based on further analysis of the 2004 Kenya Service Provision Assessment Survey
Ebola messages based on their qualitative research done in hotspot areas of Bombali and Urban Freetown, Jan-Feb 2015
A paper presented at the 10th International Congress on Infectious Disease, Singapore
A project of the FIGO Committee for Women’s Sexual and Reproductive Rights (WSRR)
(African Development Bank policy research document 1)
The report examines financing in the battle against malaria, focusing on the role of foreign aid. It analyzes whether or not a disease such as malaria can be controlled or eliminated in Africa without health aid. It also presents a theoretic...al model of the economics of malaria and shows how health aid can help avoid the “disease trap.” While calling for increased funding from international sources to fight malaria, it also recommends that African countries step up their own efforts, including on domestic resource mobilization. In 2016, governments of endemic countries contributed 31% of the estimated total of US $ 2.7 billion.
Between 2000 and 2014, malaria control efforts were scaled up and worldwide deaths were cut in half. But declining health aid and deprioritized vertical aid (as for malaria), despite its potentially great efficiency, have led to rising numbers of cases. In 2016, 216 million cases of malaria were reported, up from 211 million in 2015. Africa was home to 90% of all malaria cases and 91% of malaria deaths in 2016. Progress appears to have stalled in the global fight against the disease.
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AIDS Research and Therapy 2015, 12:12 (24 April 2015)
This handbook was designed primarily as a tool for district clinical specialist teams (DCSTs), and for the provincial specialists who will guide and support their work. This handbook will also be useful to managers of health facilities, heads of clinical units and nurses, doctors and allied health w...orkers at the coalface of clinical care. This handbook will be of interest to district managers and other members of the district management team who are dedicated to developing the capacity of the district health system to respond
effectively to the health needs of the population they serve. It will help them understand the role of the DCSTs and the type of
activities they need to engage in to improve the quality of care
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PLOS ONE | DOI:10.1371/journal.pone.0133869 July 28, 2015, p.1-16
Statistical Report No 24: 2014
PLoS ONE 12(7): e0180996. https://doi.org/10.1371/journal.pone.0180996