In recent years, there has been a growing interest in the concept of trust within the domain of natural disaster management. Trust can be defined as a state of vulnerability where one party relies on another party with the expectation that the latter will carry out entrusted responsibilities without exploiting this inherent vulnerability. This comprehensive literature review is dedicated to the examination of research concerning community and institutional trust in the field of disaster risk reduction (DRR). Particular emphasis is placed on elucidating the influence of trust throughout the distinct phases of natural disaster management, namely prevention, preparedness, response, and recovery. The critical examination of the pertinent body of the literature demonstrates that trust plays a central role across the different phases of DRR, being positively associated with effective community responses and resilience. Hence, it becomes imperative to actively foster the development of trust at both institutional and community levels within the realm of DRR. This endeavor is essential for adequately preparing communities to confront natural disasters, crafting effective protocols to enhance community responsiveness and mitigate adverse consequences, and advancing strategies for successful reconstruction and recovery.

At different rates in different countries, one can observe the phenomenon of COVID-19 vaccine hesitancy. In June 2021, we surveyed 1,068 people in France and Italy to inquire about individual potential acceptance, focusing on time preferences, in a risk-return framework: getting the jab today, in a month, and in 3 months; perceived risks of vaccination and COVID-19; and expected benefit of the vaccine. We conducted a randomized controlled trial to understand the impact of daily stimuli, such as factual news about vaccines, on audience acceptance of vaccination. In the main experiment, participants were asked to read two different articles extracted from two Italian newspapers about vaccine-related thrombosis, one using a more abstract description and language and the other using a more anecdotical description and concrete language. We find that individual preferences for vaccination are variable and unstable over time, and individual choices of accepting, refusing, or delaying may be affected by the way news is written. To understand these dynamic preferences, we propose a new model based on seven categories of human behaviours that was validated by a neural network. We observe a treatment effect: participants who red the articles significantly shifted to vaccine hesitancy categories. Furthermore, we detect a peculiar gender effect, showing that the type of language that results in a higher vaccination rate for men is correlated with women’s lower vaccination rate and vice versa. This outcome should be taken into consideration for an appropriate gender-based communication campaign to achieve herd immunity.