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The COVID-19 pandemic demonstrated the fragility of international, national, regional, and local risk management systems. It revealed an urgent need to improve risk planning, preparedness, and communication strategies. In parallel, it created an opportunity to drastically re-think and transform societal processes and policies to prevent future shocks originating not only from health, but also combined with those related to climate change and biodiversity loss. In this perspective, we examine how to improve integrated risk assessment and management (IRAM) capacities to address interconnected shocks. We present the results from a series of workshops within the framework of the University of Zurich and University of Geneva. Initiative "Shaping Resilient Societies: A Multi-Stakeholder Approach to Create a Responsive Society". This initiative gathered experts from multiple disciplines to discuss their perspectives on resilience; here we present the key messages of the "Pandemics, Climate and Sustainability” thinking group. We identify a roadmap and selected research areas concerning the improvement of IRAM analysis capacities, practices, policies. We recommend the development of robust data systems and science-policy advice systems to address combined shocks emerging from health, biodiversity loss and climate change. We posit that further developing the IRAM framework to include these recommendations will improve societal preparedness and response capacity and will provide more empirical evidence supporting decision-making and the selection of strategies and measures for integrated risk reduction.

The severe impact of global crises, such as COVID-19 and climate change, is plausibly reshaping the way in which people perceive risks. In this paper, we examine and compare how global crises and local disasters influence public perceptions of multiple hazards in Italy and Sweden. To this end, we integrate information about the occurrence of hazardous events with the results of two nationwide surveys. These included more than 4000 participants and were conducted in two different phases of the COVID-19 pandemic corresponding to low (August 2020) and high (November 2020) levels of infection rates. We found that, in both countries, people are more worried about risks related to experienced events. This is in line with the cognitive process known as the availability heuristic: individuals assess the risk associated with a given hazard based on how easily it comes to their mind. Epidemics, for example, are perceived as less likely and more impactful in Italy compared to Sweden. This outcome can be explained by cross-country differences in the impact of, as well as governmental responses to, COVID-19. Notwithstanding the ongoing pandemic, people in both Italy and Sweden are highly concerned about climate change, and they rank it as the most likely threat.

Scholars have unravelled the complexities and underlying uncertainties in coupled human and water systems in various fields and disciplines. These complexities, however, are not always reflected in the way in which the dynamics of human–water systems are modelled. One reason is the lack of social data time series, which may be provided by longitudinal surveys. Here, we show the value of collecting longitudinal survey data to enrich sociohydrological modelling of flood risk. To illustrate, we compare and contrast two different approaches (repeated cross-sectional and panel) for collecting longitudinal data and explore changes in flood risk awareness and preparedness in a municipality hit by a flash flood in 2018. We found that risk awareness has not changed significantly in the timeframe under study (1 year). Perceived preparedness increased only among those respondents who suffered low damage during the flood event. We also found gender differences across both approaches for most of the variables explored. Lastly, we argue that results that are consistent across the two approaches can be used for the parametrisation of sociohydrological models. We posit that there is a need to enhance the representation of socio-demographic heterogeneity in modelling human–water systems in order to better support risk management.