AI Insight
This study examines how pandemic risk is represented within the Shared Socioeconomic Pathways (SSPs), a framework widely used to model global environmental and social change scenarios. The researchers found that the SSP framework captures most drivers of pathogen spillover from animals to humans and many factors affecting pandemic spread, with pandemic risk lowest in the sustainable development scenario (SSP1) and highest in the fragmented world scenario (SSP3). The analysis reveals that climate change and pandemic risk share common drivers including ecosystem degradation, intensive animal agriculture, and governance weaknesses, suggesting these threats should be understood as interconnected components of a broader global crisis.
Why it matters
This research provides a tool for integrating pandemic risk assessment into existing climate and environmental change modeling frameworks, potentially improving preparedness planning. By demonstrating that pandemic risk and climate change share underlying drivers, the findings support coordinated policy approaches that address multiple global threats simultaneously rather than in isolation.
⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
For over a decade, the Shared Socioeconomic Pathways (SSPs) have served as the principal framework for quantitative modeling of the socioeconomic dimensions of global environmental change. The SSP scenarios describe many of the ecological and social processes thought to shape pandemic risk, including the emergence of novel pathogens (accelerated by processes such as deforestation, livestock intensification, and land-use change) and their subsequent spread (mediated by factors such as inequality, human mobility, and health system capacity). However, the SSP framework has not been widely incorporated into pandemic risk assessment. Here, we assess how pandemic risk is embedded in the SSP framework, and find that the framework captures most of the social-environmental drivers of pathogen spillover, and many of the social-economic drivers of pandemic spread and impacts. Because climate change and pandemics share many drivers and risk factors– including ecosystem degradation, animal agriculture, and weak governance–SSP scenarios characterized by higher barriers to climate adaptation also generally imply lower chances of outbreak containment, and greater pandemic impacts on vulnerable populations. Pandemic risk is therefore lowest in SSP1 and highest in SSP3, but SSP5 shows that frequent spillover and effective containment can coexist. These findings suggest that pandemic risk can be understood as part of a broader polycrisis, linking climate change, biodiversity loss, and global health. We suggest that new scenario extensions, or entirely novel frameworks, will ultimately be needed to capture possible shifts in the global health landscape; however, in the meantime, scenario frameworks from the environmental sciences could be valuable tools for initiatives to quantify future pandemic risks.