Guidelines
June 2017
HIV strategic information for impact
Technical Brief
HIV patient monitoring and case surveillance
WHO/HIV/2017.11
UNAIDS 2018 / Guidance
Guidance for policy-makers, and people living with, at risk of or affected by HIV
UNAIDS 2017 / Reference
Generating evidence for policy and action on HIV and social protection
Translating Community Research Into Global Policy Reform For National Action: A Checklist For Community Engagement To Implement The WHO Consolidated Guideline On The Sexual And Reproductive Health And Rights Of Women Living With HIV
3rd edition | December 2018
Bull World Health Organ 2015;93:457–467 | doi: http://dx.doi.org/10.2471/BLT.14.147215
Accountability for the global health sector strategies, 2016–2021
WHO/CDS/HIV/19.7
Policy Brief
November 2014
It's time to deliver differently.
Accessed: 13.11.2019
l’IMC et le gain de poids gestationnel sont des facteurs déterminants des risques de
résultats de grossesse, de la santé de la mère et de l’enfant. Cette étude analyse l’incidence de la
nutrition chez les femmes enceintes sur la santé néonatale au Bénin. Les résultats d’estimation... par les
équations simultanées montrent que le gain de poids gestationnel insuffisant ou excessif a des effets
néfastes aussi bien sur la santé de la mère que sur celui de l’enfant. L’étude montre que la majorité des
femmes béninoises étudiées, avec un IMC faible ou normal n’atteignent pas le gain de poids
gestationnel recommandé en fin de grossesse. La plupart des nouveau-nés de petits poids de naissance
sont nés de femme dont l’IMC est normal, ce qui renforce la théorie bien connue que l’IMC n’est pas un
bon indicateur de la malnutrition chez la femme enceinte.
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World Health Organization Department of Reproductive Health and Research
Brocher Foundation, Hermance, Geneva, Switzerland, 27–29 April 2016
The classification of digital health interventions (DHIs) categorizes the different ways in which digital and mobile technologies are being used to support health system needs. Historically, the diverse communities working in digital health—including government stakeholders, technologists, clinic...ians, implementers, network operators, researchers, donors— have lacked a mutually understandable language with which to assess and articulate functionality. A shared and standardized vocabulary was recognized as necessary to identify gaps and duplication, evaluate effectiveness, and facilitate alignment across different digital health implementations. Targeted primarily at public health audiences, this Classification framework aims to promote an accessible and bridging language for health program planners to articulate functionalities of digital health implementations.
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