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Short Abstract

For more than three decades, DHS provided vital demographic and health data on population, health, HIV, and nutrition in over 90 countries. Its termination by the US administration leaves major gaps in tracking the Sustainable Development Goals, particularly in low- and middle-income countries.

Abstract

For more than three decades, DHS provided vital demographic and health data on population, health, HIV, and nutrition in over 90 countries. Its termination by the US administration leaves major gaps in tracking the UN Sustainable Development Goals (SDGs), particularly in low- and middle-income countries.

This issue has highlighted the key risks of overreliance on a single country or institution to provide a global, top-down survey approach that places minimal responsibility and financial investment on individual countries for their own data collection. Moreover, the increasing financial pressures on statistical systems and their ability to monitor the SDGs extend beyond LMICs and the US. Many high-income countries, particularly European ones, are experiencing similar challenges as national budgets are being diverted to increased defense spending. Along with these budget cuts comes a risk that perceived efficiency gains from AI are increasingly viewed as a pretense to put further budgetary pressure on National Statistical Offices (NSOs). In this evolving environment, the authors argue that citizen science, which to date has been considered as a complementary approach to official statistics, may now need to play a more central role, and become more integrated into national and global data ecosystems.