The National Institute for Transforming India (NITI) Aayog has developed the Composite Water Management Index (CWMI) to enable effective water management in Indian states in the face of extreme water stress. The Index and this associated report are expected to: (1) establish a clear baseline and ben...chmark for state-level performance on key water indicators; (2) uncover and explain how states have progressed on water issues over time, including identifying high-performers and under-performers, thereby inculcating a culture of constructive competition among states; and, (3) identify areas for deeper engagement and investment on the part of the states. Eventually, NITI Aayog plans to develop the index into a composite, national-level data management platform for all water resources in India.
more
An historic opportunity to end AIDS as a public health threat by 2030 and launch a new era of sustainability
A decade of progress has inspired the once unthinkable—that the AIDS epidemic can be ended as a public health threat. The global community has embraced the bold idea to end the AIDS ep...idemic as a target of the 2030 Agenda for Sustainable Development. Governments from around the world have committed to a Fast-Track agenda and a set of ambitious but attainable milestones to be achieved by 2020 in order to end the AIDS epidemic by 2030, as set out in the United Nations General Assembly Political Declaration on Ending AIDS. Regular reporting through UNAIDS reinforces accountability for results.
more
PLOSONE| https://doi.org/10.1371/journal.pone.0204882October17,2018
A catalyst for transformation in the United Nations to deliver health results for women, children and adolescents in support of the Sustainable Development Goals
The primary objectives of the 2017 TMIS are to measure the level of ownership and use of mosquito nets; assess coverage of intermittent preventive treatment for pregnant women; identify treatment practices, including the use of specific antimalarial medications to treat malaria among c...hildren age 6-59 months; measure the prevalence of malaria and anemia among children age 6-59 months; and assess knowledge, attitudes, and practices among adults with malaria.
This table provides estimates of key indicators for the country as a whole and for each of the 31 geographic regions in Tanzania. A comprehensive analysis of the 2017 TMIS data will be presented in a final report.
more
Accessed Online June 2018 | When assessing potential opportunities for family planning, it is important to consider a wide range of areas related to demand for contraception, availability and access to services, quality and equity, and the enabling environment. This opportunity brief brings together... a range of data sources to allow for exploration of these key areas. This brief is meant to provide an overview of key data and population segmentations to spark conversations about prioritization and potential impact. Further analysis, including additional segmentation by residence or region may reveal additional nuances.
more
Key Malaria Indicators from the 2017 Rwanda Malaria Indicator Survey - The table in this key indicator report provides estimates of key indicators for the country as a whole and for each of the five provinces in Rwanda.
This WHO information note provides an updated list of recommended criteria for selecting RDTs for malaria, and highlights the performance of RDTs evaluated by the WHO malaria RDT product testing programme. It also provides an overview of additional considerations in the procurement of rapid tests.
Poverty, HIV and other disease burdens, coupled with common mental disorders including alcohol and other substance use disorders, posttraumatic stress disorder, clinical and postnatal depression, distress, and anxiety, impact how caregivers meet the needs of children. When mental health is not consi...dered or addressed, there can be a significant impact on an individual, their family and the community.
more
DHS Further Analysis Reports No. 115
Mental health disorders remain widely under-reported — in our section on Data Quality & Definitions we discuss the challenges of dealing with this data. Figures presented in this entry should be taken as estimates of mental health disorder prevalence — they do not strictly reflect diagnosis data... (which would provide the global perspective on diagnosis, rather than actual prevalence differences), but are imputed from a combination of medical, epidemiological data, surveys and meta-regression modelling where raw data is unavailable. Further information can be found here.
Accessed April 15, 2019
more
Int Nurs Rev. 2018 Mar;65(1):78-92. doi: 10.1111/inr.12391. Epub 2017 May 25.