More than 3 million Pinoys register for Phil ID
(Newsletter: CRVS Insight November (2) 2020)
The CRVS community in Asia and the Pacific has reflected on where it stands at the midpoint of the CRVS Decade (2015-2024) during the Second Ministerial Conference. Following this celebration of progress, many of our partners and member countries are leading actions to fill the remaining gaps. To learn more about CRVS in Asia and the Pacific, please subscribe to our newsletter, which offers a monthly panorama of CRVS actions throughout the region Previous editions can be found here. |
(Newsletter: CRVS Insight November (2) 2020)
(Newsletter: CRVS Insight November (2) 2020)
(Newsletter: CRVS Insight November (2) 2020)
On Nov. 15, 2020, the Global Grants Program within Bloomberg Philanthropies Data for Health (D4H) Initiative launched a new request for proposals.
(Newsletter: CRVS Insight November (2) 2020)
In preparation for the Second Ministerial Conference on Civil Registration and Vital Statistics in Asia and Pacific, the Child Rights Coalition Asia, World Vision, and UN ESCAP will, over the coming months, conduct:
Newsletter: CRVS Insight November 2020 (2)
The CRVS Partnership for Asia and the Pacific is composed of different international organizations and development partners involved in programs related to the improvement of CRVS systems in the Asia-Pacific region. The Partnership meets regularly to discuss preparations for upcoming events and engage in round table information sharing meant to enable project alignment.
"The Good, the Bad and the Ugly: Revelations from reviews of national statistical systems"
(Newsletter: CRVS Insight November 2020)
(Newsletter: CRVS Insight November 2020)
The Sustainable Development Goals (SDGs) set an ambitious agenda to produce relevant, reliable and timely data. The quantity and breadth of data required to monitor and evaluate the SDGs presents a considerable challenge to national statistical systems. Therefore, National Statistical Offices (NSOs) have a major role in making the best use of existing data sources.