Advancing pandemic preparedness: A Scenario-and-Respond framework for disease “X”

Pandemics, caused by unknown high-consequence pathogens, referred to as Disease “X”, pose extreme yet plausible threats to public health security. Their inherent unpredictability challenges conventional “predict-and-respond” paradigms, requiring more resilient, adaptive approaches to preparedness. This study proposes a shift toward a Scenario-and-Respond framework to enhance systemic resilience in the face of deep uncertainty. We developed an interdisciplinary Scenario-and-Respond framework integrating scenario construction, grounded theory, systematic literature review, expert elicitation, and epidemiological modeling. The framework was retrospectively applied to the 2009–2010 H1N1 influenza pandemic in Beijing, Guangdong and Sichuan to validate its validity, robustness, and utility for anticipatory governance. This study generated four plausible, high-impact transmission scenarios for Disease “X”, each driven by distinct combinations of disease transmissibility, disease severity, transmission contribution from asymptomatic cases, epidemiological features of infectious disease outbreaks and medical resource demand. These scenarios enabled dynamic risk assessment under uncertainty and were validated against empirical H1N1 data. These results demonstrate that scenario-based planning proposes a shift from the traditional “predict-and-respond” paradigm to a more adaptive “Scenario-and-Respond” decision-making framework. By replacing rigid prediction with flexible foresight, the Scenario-and-Respond framework offers a practical, resilience-oriented approach to pandemic preparedness. It provides actionable intelligence to strengthen adaptive capacity, reduce systemic vulnerability, and support safety-critical decisions in the face of emerging Disease “X” threats.