News 2026

Achieving universal health coverage (UHC), including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all is officially an agreed target (3.8) for health in the Sustainable Development Goals (SDGs). Critical to attaining UHC is a formal monitoring mechanism to assess progress.

The Workshop on Data Governance, Innovation and Quality Assurance in a Changing Data Ecosystem for the Asia-Pacific Region will take place from 13 to 16 October 2026 in Chiba, Japan. The workshop is jointly organised by the United Nations Statistics Division (UNSD) and the United Nations Statistical Institute for Asia and the Pacific (SIAP), with the support of the Office of the Director-General for Policy Planning on Statistical Policy, Ministry of Internal Affairs and Communications (MIC), Government of Japan.

Population and housing censuses are the most comprehensive and authoritative data sources on the size and characteristics of a country’s population. They form a cornerstone of national statistical systems, generating essential social, economic, and demographic data. These data provide the baseline evidence required for planning, policy development, implementation, and monitoring across geographical levels, sectors, as well as for research and analysis.

Domestic production in the Pacific is limited by the lack of resources and technologies, geographic isolation, high costs, and insufficient economies of scale. As such, Pacific economies are heavily reliant on international trade to supply their basic commodities and more complex machinery, and to expand their market base. International merchandise trade statistics (IMTS) is crucial to monitor and analyze trade flows, production and consumption. Timely and high-quality trade statistics will better guide the development of trade and economic policies and infrastructure planning. 

Adopted by the 56th Session of the United Nations Statistical Commission, the 2025 System of National Accounts (2025 SNA) serves as the internationally recognized standard for compiling measures of economic activity. The basic theoretical framework of the 2008 SNA is retained in the updated framework. The 2025 SNA gives more prominence to certain aspects of the economy, such as globalization, digitalization, informality, and emerging financial issues.

Household consumption and expenditure surveys (HCES) have been typically undertaken to compile information for important macroeconomic indicators, such as consumer price indices, and to provide input into national accounts. With time, the use of HCES has been extended to welfare and poverty analysis, and more recently to food security and nutrition analysis. The food data collected in HCES provides core information for these types of analyses.

Effective measurement of poverty is essential for understanding the scale, depth and distribution of deprivation, and for designing policies that respond to the needs of the poorest and most vulnerable. Accurate, timely, and comparable poverty statistics enable governments to better target interventions, monitor progress, and assess the impact of economic and social shocks.  In the context of the Sustainable Development Goals, particularly SDG 1 (No Poverty), robust poverty measurement is indispensable for ensuring that policy responses are evidence-based and effective.

The numbers of refugees and internally displaced persons (IDPs) have increased rapidly in recent years, with UNHCR estimating over 117.8 million forcibly displaced persons by the end of 2025. Similarly, the issue of statelessness continues to persist in society, with 4.5 million people currently estimated to be stateless.

This course is an advanced course in data visualization, conceived as an extension of  SIAP’s facilitated course “Data Visualization for Official Statistics and SDG Indicators,”  last conducted in 2024, or, alternatively, of the self-paced course “Principles of Data Visualization for Official Statistics and SDG Indicators,” available on SIAP’s e-learning platform. 

The System of Environmental-Economic Accounting (SEEA) provides the agreed upon statistical framework for measuring the relationship between the environment and the economy. It is comprised of two complimentary international statistical standards: the SEEA Central Framework (SEEA CF) and the SEEA Ecosystem Accounting (SEEA EA). The SEEA CF takes a resource-based approach to measuring the supply and use of environmental resources and availability of environmental assets. The SEEA EA takes a holistic and spatially explicit approach to compiling accounts on ecosystems.

Across Asia and the Pacific, violence against women and girls is taking increasingly complex and lethal forms—from gender-related killings(femicide/feminicide) to rapidly evolving technology-facilitated abuse—yet both remain insufficiently measured due to persistent gaps in definitions, reporting, and integrated data systems.

Climate change is one of the most pressing issues of our time. Its impacts on well-being are far reaching, including impacts on health and the economy. Humans have contributed to climate change largely through economic activities which are intrinsically linked to climate change. Our supply and use of energy for example has led to increased emissions of greenhouse gases which have resulted in global warming.

In recent years, the data landscape has evolved rapidly, creating for National Statistical Offices (NSOs) both significant opportunities for innovation and important challenges in maintaining data quality and reliability. In response to these developments, the Statistical Institute for Asia and the Pacific (SIAP) and the Ministry of Data And Statistics (MODS) are organizing a Regional Training on Data Science for Official Statistics, recognizing both the opportunities and the challenges associated with integrating Data Science methods and tools into NSO processes. 

The training aims to strengthen the capacity of heads of National Statistics Offices to lead their own organisations and position them in the larger data ecosystem. This training session follows similar sessions run successfully by PARIS21 and SIAP in the region. 

The United Nations Statistical Institute for Asia and the Pacific (SIAP) and the United Nations Statistics Division (UNSD), in cooperation with the Department of Economic and Social Affairs (DESA) Small Island Developing States (SIDS) Unit and the Secretariat for the Pacific Community, are organizing an Energy Statistics Training Workshop for Pacific SIDS. The Workshop will be held in Port Moresby, Papua New Guinea from 29 April – 1 May 2026.

National statistical systems are increasingly using administrative data to compile official statistics. Such data can be utilized to better meet the increasing demands for new statistics and indicators that are highly disaggregated. Administrative data is not collected for the primary purpose of compiling official statistics, and statisticians need to ensure that the data meets certain criteria before using it to produce official statistics.

The 2025 System of National Accounts (2025 SNA) and Balance of Payments and Integrated Investment Position Manual, 7th edition (BPM7) provide more visibility to digital activities, products and transactions in macroeconomic accounts given its tremendous impact on production, consumption, prices, trade, labour, and other aspects of the economy. Measurement issues associated with digitalization are elaborated in the 2025 SNA and BPM7, as well as in the accompanying guidance notes and manuals.

Identifying and responding to the needs of users for data and statistics is at the heart of the mission of National Statistical Offices (NSOs) and national statistical systems. NSOs already undertake many activities interacting with different users such as preparing press releases to aid journalists and communicate with the public at large and organizing launch events/workshops to disseminate important results from surveys and censuses. In general, the NSO interacts with users towards the tail end of the statistical production process when the data is disseminated.