As global challenges become increasingly interconnected, the Advancing Systems Analysis Program continued to develop innovative approaches for understanding complexity and supporting better decisions. In 2025, the program’s research revealed new insights into urban sustainability, resilience in an era of polycrisis, public health, and sustainable development.
Citizen science and the challenge of measuring urban sustainability
Cities are expected to track sustainability progress with data that are often incomplete, outdated, or available only at national level. Research led by IIASA in collaboration with UN‑Habitat finds that citizen science could address these gaps and support nearly 70% of global sustainability indicators, yet is currently used in only 4% of cases.
The study provides the first comprehensive review of how citizen science can contribute to the Global Urban Monitoring Framework (UMF), developed by UN‑Habitat. The UMF brings together 77 urban indicators drawn from the Sustainable Development Goals and other international frameworks and is increasingly used to track progress toward safe, resilient, and sustainable cities.
Researchers found that citizen science aligns with 52 of the 77 indicators, particularly in environmental and social areas such as air quality, biodiversity, access to basic services, public space, mobility, and community wellbeing. Yet it currently contributes directly to only three indicators.
“This study highlights a missed opportunity in how cities track sustainability,” says co-lead author Inian Moorthy. “Citizen science is suitable for contributing to most of the framework we reviewed, but it is currently contributing to only a handful of indicators.”
An analysis of 466 cities also revealed that fewer than 20% of indicators are reported at city level, leaving local realities underrepresented. The findings suggest the main barrier is not data scarcity but integration. By incorporating citizen science into official monitoring, cities can strengthen sustainability assessments and better reflect lived urban experience.
Further information: pure.iiasa.ac.at/21224
Resilience investments in a world of polycrisis
As global crises become more interconnected, policymakers face growing challenges in managing risks that span sectors and regions. IIASA research highlights how investments in disaster risk reduction can generate benefits far beyond preventing losses.
The concept of polycrisis – a situation where multiple crises interact and reinforce each other – has gained increasing attention in recent years in policy circles. Climate change, economic instability, energy security, and food systems are closely linked, meaning that shocks in one area can cascade across others.
The research extends the Triple Dividend of Resilience (TDR) framework, which shows that investments in disaster risk reduction (DRR) and climate change adaptation (CCA) can generate multiple benefits. In addition to reducing disaster losses, such measures can unlock development opportunities and create co-benefits such as safer infrastructure or more energy‑efficient housing.
Despite growing recognition of these advantages, investment in risk reduction remains insufficient. The researchers suggest this gap is partly due to limited awareness of the broader social and economic gains that resilience measures can deliver, as well as challenges in measuring these benefits across sectors and scales.
“Sustainable-oriented investments ought to do more than prevent risks. They may also create additional benefits for society as well as support development and transformation,” says lead author Reinhard Mechler. “Recognizing all these resilience dividends can help policymakers make better decisions.”
The research also informed a webinar on Coping with polycrisis and systemic risks, where experts discussed how approaches such as integrated risk assessment and adaptive governance can help manage cascading crises and strengthen resilience.
Further information: pure.iiasa.ac.at/20802
Smarter SDG priorities for greater impact in China
Achieving the Sustainable Development Goals (SDGs) requires careful prioritization of efforts, especially when resources are limited and targets interact in complex ways. A 2025 study presents an analytical model to help policymakers identify where action is most urgent, where greater investment is needed, and where progress can be achieved more efficiently.
The study introduces a three-dimensional model that integrates systemic impact, feasibility, and urgency. Unlike many existing approaches, it captures both high-order synergies and trade-offs across the SDG network. It distinguishes between temporal priority, reflecting how urgently a target requires action, and resource priority, indicating the level of investment needed. This supports more targeted and cost-effective strategies.
Applied to China using network and time-series data from the Institute for Global Environmental Strategies SDG Interlinkages database, the model distinguishes between time-critical targets and those constrained primarily by structural barriers. It shows that only 12% of SDG targets require immediate action, particularly in biodiversity conservation and forest management. In contrast, 27% are less time-sensitive but face systemic obstacles requiring greater resource investment, especially under SDG 12 (Responsible Consumption and Production), SDG 15 (Life on Land), and SDG 16 (Peace, Justice, and Strong Institutions). In contrast, SDG 13 (Climate Action) benefits from positive spillovers and can advance with more moderate inputs.
“Effective SDG implementation is not just about doing more, but about acting strategically,” says lead author Yuanhui Wang, a former Young Scientists Summer Program participant from Beijing Normal University, China. “Our model helps identify where interventions can deliver the greatest systemic benefits.”
The framework offers a clear, transferable tool to maximize overall SDG impact.
Further information: pure.iiasa.ac.at/20925
Tracking compliance with social‑distancing using digital platform activity data
Digital platform activity data from mobility to e-shopping can reveal how closely people follow social-distancing measures and how this behavior influences pandemic dynamics as shown by IIASA-led research.
During the early stages of the COVID-19 pandemic, social distancing was the main policy to slow virus transmission. It came with social and economic costs, however, and its effectiveness varied across locations and over time. Understanding how closely people follow social-distancing guidelines is crucial for designing effective public health responses.
Researchers explored whether digital platform activity data could help measure people-to-people contact intensity in real time. Using the case of Yandex’s self-isolation index, an indicator built from aggregated user activity data, the team analyzed self-isolation patterns in Moscow and St. Petersburg, Russia, during the COVID-19 outbreak.
The researchers applied statistical methods inspired by the classical infectious-disease model (SEIR) to test whether changes in the self-isolation index are linked with the dynamics of the outbreak reflected by the official records of new COVID-19 cases and deaths. The analysis found evidence supporting this hypothesis and uncovered policy-relevant delays between introduction of social-distancing measures and observable effects.
“Our results show that digital activity indicators can provide a reliable picture of how people adjust their behavior during a pandemic,” says lead author Piotr Zebrowski. “This kind of real time information can help governments calibrate social-distancing policies effectively.”
The findings highlight the potential of commercial digital platforms to serve as unique, rapid, and scalable data sources for monitoring public behavior and supporting evidence-based responses to future health crises.
Further information: pure.iiasa.ac.at/21005