SIAP/Shuji Fukuyama
Dr Shanlong Ding, Technical Officer of the Health Information and Digital Health unit with participants in a group photo of the SIAP-JICA training course. The course strengthens knowledge and skills in statistical and health information topics.
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Strengthening health and sanitation statistics capacity across Asia and the Pacific

4 August 2026
Departmental update
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The WHO Regional Office for the Western Pacific supported a two-day training module on Health and Sanitation Statistics on 27–28 July 2026 at the Statistical Institute for Asia and the Pacific (SIAP) in Chiba, Japan. The module formed part of the SIAP–Japan International Cooperation Agency (JICA) course on Theory and Practices in Official Statistics for Monitoring Sustainable Development Goals (SDGs).

Nine national statistical officers from Azerbaijan, Cambodia, Egypt, Kiribati, Lao People's Democratic Republic, Madagascar, Malaysia, Papua New Guinea and Tonga participated in the training.

National statistical offices play a central role in monitoring progress towards the SDGs. However, health and sanitation indicators present unique methodological challenges. Recent revisions to the universal health coverage (UHC) and financial protection indicators, often misunderstood definitions of water and sanitation service levels, and the complexity of excess mortality estimation all require strong statistical capacity and clear understanding of the underlying methods.

The training aimed to strengthen participants’ ability not only to produce key health and sanitation indicators, but also to interpret, communicate and justify the methods used to generate them.

The first day focused on indicator measurement. Participants worked through the updated 2025 methodological revisions of the UHC Service Coverage Index (SDG indicator 3.8.1) and catastrophic health spending (SDG indicator 3.8.2), and drinking water and sanitation service ladders (SDG indicators 6.1 and 6.2). Practical exercises guided participants through the calculation of each indicator before using AI-assisted tools to verify results.

On the second day, participants learned to access indicator data directly from the WHO Global Health Observatory and the United Nations SDG database using open-source R packages developed by the Regional Office. They also examined excess mortality estimation and the International Health Regulations (2005) State Party Self-Assessment Annual Reporting (SPAR) tool, which provide complementary perspectives on the impact of public health events and countries’ preparedness capacities.

As a final exercise, participants developed their own dashboards to visualize and communicate health and sanitation indicators.

Key elements of the training included:

  • Methodological revisions to SDG indicators 3.8.1 and 3.8.2 require that reported figures always specify which version was used, as pre- and post-revision values are not comparable.
  • National averages can mask substantial inequalities, highlighting the importance of disaggregated analyses, including by urban and rural population groups.
  • Excess mortality estimates are sensitive to methodological choices, underscoring the need for transparent reporting of assumptions and methods.
  • AI tools can accelerate statistical production, but responsibility for validation, methodological decisions and interpretation remains with human analysts.

Participant engagement was particularly strong during the AI-focused sessions, with several participants configuring AI-assisted coding environments during the course. The Regional Office will continue supporting Member States in strengthening the production, analysis and communication of official health statistics to advance evidence-informed decision-making and SDG monitoring.

The training was delivered in partnership with SIAP and JICA.