Version 1: March 9, 2021. A living document
In order to better understand the contributing factors of undernutrition in LIFT program areas and the links between child nutritional status and independent variables of programmatic importance to LIFT (such as income, livelihoods, food security, and water, sanitation and hygiene [WASH]), LEARN com...missioned a secondary analysis of nutrition-related data from the 2013 LIFT Household Survey. The purpose of this report is to present the findings of this analysis.
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The primary aim of this assessment is to evaluate current approaches to malaria surveillance in Myanmar and to provide a set of practical and feasible recommendations to further strengthen the surveillance system in the short to medium term. The assessment focuses on the surveillance of malaria case...s (as distinct from more general surveillance to support monitoring and evaluation) and, more specifically, on instruments and systems to collect, collate, report and analyse malaria data as a basis for informing malaria control policy and practice.
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DEVELOPMENT BULLETIN | No.74, June 2011 | Editor: Pamela Thomas | Features and case studies | Progress with implementing conventions and strategies | Progress with capacity building | Progress with disability-inclusive education | Disability-inclusive research | Innovative inclusion | Review of urba...nisation in the Pacific | Development assistance and disability
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Health Systems in Transition. Vol. 5 No.3 2015
Rashtriya Bal Swasthya Karykram (RBSK). Operational Guidelines
The Road to Recovery. This synthesis report is based on three national studies on the evolution of the Ebola epidemic and its impact on Guinea, Liberia and Sierra Leone
The frequency of infectious disease epidemics is increasing, and the role of the health sector in the management of epidemics is crucial in terms of response. In the context of infectious disease epidemics, the use of climate-informed early warning systems (EWS) has the potential to increase the eff...ectiveness of disease control by intervening before or at the beginning of the epidemic curve, instead of during the downward slope.
Currently, the initiation of interventions is heavily reliant on routine disease surveillance systems – data that often arrive too late for preventative response. However, forecasting of disease outbreaks using surveillance and weather information shows promising potential – there also remains further scope to examine seasonal climate forecasts. By combining these elements in new EWS based on computational models, it will be possible to improve both the timeliness and impact of disease control. The World Health Organization (WHO) is strengthening existing surveillance systems for infectious diseases to enable the development of more robust and timely EWS, which has resulted in the rapid development and innovation of EWS for disease outbreaks.
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