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Aims: To analyze whether patient verbal aggression would be related to emotional exhaustion and whether this relationship would be mediated by work–family conflict and moderated by dehumanization and resilience. Background: Although patient verbal aggression has been identified as one of the most experienced forms of aggression, its effects on Italian health care providers during the pandemic are still poorly known. Methods: A total of 197 Italian health care professionals completed paper‐and‐pencil questionnaires. Descriptive statistics and moderated mediation analyses were performed. Results: Patient verbal aggression was positively related to health care professionals' emotional exhaustion, both directly and indirectly, as mediated by work–family conflict. Health care providers were more likely to become emotionally exhausted when they had low resilience and, simultaneously, tended to ascribe patients non‐uniquely human traits. Conclusions: Patient verbal aggression may spill over onto health care professionals' family lives. Dehumanization represents an ineffective coping strategy that exacerbates the effects of aggression on work–family conflict, whereas resilience represents a protective resource against emotional exhaustion. Implications for nursing management: Hospital organisations could benefit from providing their staff with stress management interventions, aggression management, psychological support and psychological resilience training programmes. These programmes should incorporate coping skills on establishing work–home boundaries and balancing empathy with cognitive problem‐solving abilities. [ABSTRACT FROM AUTHOR]

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI's application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act swiftly and thereby enhance containment of outbreaks. [ABSTRACT FROM AUTHOR]