Through public-private partnerships, the government of Rwanda can make more efficient use of public resources by targeting and meeting the needs of specific populations and thus help ensure family planning services and products will be available to
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all Rwandans in the long term. This report aims to inform stakeholders working to strengthen family planning through multisectoral partnerships about Rwanda’s family market.
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This manual is a resource for Health Counselors working in Family Physician Clinics (FPC) as part of the MANAS program. This program is for common mental disorders like depressio
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n and anxiety seen in primary health care facilitieslike the FPC; since depression is the commonest disorder within this group of stress related mental health problems, in the manual we refer to these problems simply as ‘Depression’. The aim of the MANAS program is to integrate the recognition and treatment of Depression into routine primary health care.In the MANAS program, a range of effective treatments will be provided for patients with Depression. These treatments are matched to the individual requirements of patients to both improve the effectiveness of the treatments and to use the limited resources efficiently.
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Training Manual for Community Health Workers
Scaling Up Mental Health Care In Rural India
October 2018
This publication was produced at the request of the United States Agency for International Development. It was prepared independently by David Lowe, David Hales, Britt Herstad, Billy Pick, Aisuluu Bolotbaeva, and Gulgun Jonboboeva.
As the global community aims to fulfill its commitments to the UN Sustainable Development Goals, and the achievement of universal health coverage, dozens of countries have committed to the expansion of community health workers (CHWs) as the front line of their healthcare systems [1, 2]. Robust resea
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rch demonstrates CHWs improve access to care, reduce maternal, newborn, and child mortality, improve clinical outcomes for chronic diseases, and prevent disease outbreaks [3].
To support the operationalization of quality CHW program design and implementation, USAID, UNICEF, the Community Health Impact Coalition, and Initiatives Inc. have updated and adapted the Community Health Worker Assessment and Improvement Matrix (CHW AIM) Program Functionality Matrix [12]. This tool can be used to identify design and implementation gaps in both small- and national-scale CHW programs, and close gaps in policy and practice.
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The Compendium of data and evidence-related tools for use in TB planning and programming was developed as a companion document to the People-centred framework for tuberculosis programme planning
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and prioritization – user guide, published by the World Health Organization (WHO) in 2019. The compendium is intended to support implementation of the people-centred framework user guide. It can also be used independently to inform decisions taken by national tuberculosis (TB) programmes about the implementation of the tools included in this document.
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The five hepatitis viruses have different epidemiological profiles, and their impact, duration, and transmission route also vary. The most common transmission routes contributing to the spread of hepatitis are exposure to infected blood via blood transfusion or unsafe injection practices, consumptio
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n of contaminated food and drinking water, and transmission from mother to child during pregnancy and delivery. Also, unsafe injection practices, including the use of unsterile needles and syringes, serve as a major pathway for the spread of hepatitis B and C, and reducing transmission of both diseases requires addressing these practices.
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The Facilitator’s Guide for the basic-needs based Response Options Analysis and Planning (ROAP) is a step-by-step guide comprising tools and templates to carry out a multi-sectoral response analysis and
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planning of response options, in a sudden-onset or chronic crisis.
Being that so, the Guide is conceived to be applied hand in hand with the BNA Guidance and Toolbox, and other assessments methodologies. It is expected to assist in analysing data from different sources - including humanitarian staff’ own
knowledge and experience on the sector, cash, protection matters - to come up with response decisions
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LESOTHO COPDAM BASELINE STUDY 2013
Within an Australian context, the medium to long-term health impacts of climate change are likely to be wide, varied and amplify many existing disorders and health inequities. How the health system responds to these challenges will be best considered in the context of existing health facilities and
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services. This paper provides a snapshot of the understanding that Australian health planners have of the potential health impacts of climate change.
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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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