The Infection Prevention and Control (IPC) Guidelines aim to support healthcare workers improve quality and safety health care. The Guidelines further aim to promote and facilitate the overall goal of IPC by providing evidence-based recommendations on the critical aspects of IPC, focusing on the fun...damental principles and priority action areas. All health service organizations should consider the risk of healthcare-associated infection(s) (HAI) and antimicrobial resistance (AMR) transmission to implement these recommendations. The IPC Guidelines also set national standards for the prevention and control of HAIs and to ensure compliance to the National Quality Standards.
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Children in refugee situations face many potential dangers, such as violence, abuse, exploitation, discrimination, separation from their families, trafficking and military recruitment. The impact of these experiences can be devastating and long-lasting. Children have different needs from adults and ...these needs can only be identified and met if they are approached in a way that is specific to children.
The impact of the COVID-19 global pandemic has exacerbated the dangers faced by children in refugee situations and laid bare the need for their protection and for ensuring that all their human rights are upheld all the time.
The goal of this publication is to share examples of approaches by members of the Initiative that have proven effective for children.
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Health Systems in Transition. Vol. 5 No.3 2015
Testimonies from Humanitarian Workers with Disabilities.
By reading the first-hand accounts, we hear how persons with disabilities, not through any particular talent or skill but from unique knowledge gained through life experience, are ideally placed to provide insights, ideas and leadership, to s...upply essential data, and to fill the gaps in humanitarian response that cause this exclusion.
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Cureus 2024 Jan 16;16(1):e52358. doi: 10.7759/cureus.52358
Twenty-Fourth Annual Trachoma Control Program Review, Summary Proceedings
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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