How should humanitarian organisations prepare and respond to COVID-19 in humanitarian settings in low- and middle-income countries?
This Rapid Learning Review outlines 14 actions, insights and ideas for humanitarian actors to consider in their COVID-19 responses. It summarises and synthesises the... best available knowledge and guidance for developing a health response to COVID-19 in low- and middle-income settings as at April 2020
The paper, supported by the UN Under-Secretary-General for Humanitarian Affairs and Emergency Relief Coordinator Mark Lowcock, will be updated throughout 2020 to reflect emerging knowledge and evidence on the most effective approaches to respond to the COVID-19 Pandemic.
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A Systematic Review and Meta-analysis
Clinical Infectious Diseases® 2016;62(12):1586–94
Knowledge based upon a descriptive literature review of applied research
BMC Medicine (2015) 13:42 DOI 10.1186/s12916-014-0263-6
This guide focuses on the evaluation of psychosocial programs that are aligned with two main goals: - To promote psychosocial wellbeing by promoting an environment that provides appropriate care, opportunities for development and protects children from exposure to situations that are harmful to thei...r psychosocial wellbeing, and - To respond to psychosocial problems by strengthening social and psychological supports for children who have been exposed to situations that affect their psychological development.
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Lessons from the STEP-TB Project.
Accessed November 2017.
How safe is our hospital sanitation? An example from a public hospital
Int J Hyg Environ Health. 2019 Jun; 222(5): 765–777. doi: 10.1016/j.ijheh.2019.05.004;
To develop updated estimates in response to new exposure and exposure-response data of the
burden of diarrhoea, respiratory infections, malnutrition, schistosomiasis, malaria, soil-transmitted helminth
infec...tions and trachoma from exposure to inadequate drinking-water, sanitation and hygiene behaviours
(WASH) with a focus on low- and middle-income countries.
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The checklist tool described in this handbook is intended for EU/EEA public health authorities who need to assess the capacity for communicable disease prevention and control at migrant reception/detention centres hosting migrants for weeks/months (medium-term) in order to identify gaps and set prio...rities for development.
Using this tool, the aim is to monitor and support capacity development to prevent the onset and improve the management of communicable disease outbreaks at medium-term migration reception/detention centres, both on a day-to-day basis and in the event of a sudden influx of migrants.
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Clinical Infectious Diseases
1586 - 1594 • CID 2016:62 (15 June) • HIV/AIDS
DHS Analytical Studies No. 51
Child Health, Family Planning, Geographic Information, HIV, Malaria, Maternal Health
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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