Introduction: The 2021 European floods in Germany, Belgium, and the Netherlands significantly impacted healthcare. With climate change increasing flood risks, healthcare preparedness is essential. Floods affect healthcare directly and indirectly by disrupting patient access, damaging infrastructure and impeding care continuity. Our interdisciplinary research in the Netherlands systematically assesses flood impacts on healthcare, optimises disaster preparedness, patient logistics, and continuity and explores crisis governance, incorporating lessons from coronavirus disease-2019 (COVID-19). Methods: Our multi-sited, interdisciplinary project titled “Pandemic lessons for flood disaster preparedness” includes literature reviews on: (i) the (in) direct impacts of floods on healthcare, (ii) disaster decision-making strategies and (iii) patient logistics during crises. Empirically, ethnographic methods (interviews, focus groups, document analyses, and observations) will: (a) assess hospital flood preparedness, (b) explore decision-making and crisis management strategies and (c) analyse the dynamics of health system governance during floods. Data from these sources and flood scenarios will inform models on healthcare impacts and decision-making, culminating in a simulation game for research and training. Discussion: This study offers a comprehensive, interdisciplinary approach to understanding and improving healthcare system preparedness for floods. By integrating diverse fields such as healthcare governance, disaster risk management, logistics and hydraulic engineering, we provide a unique lens on resilience. A key strength is the incorporation of lessons from the COVID-19 pandemic, allowing us to draw parallels between pandemic response and flood preparedness. In addition, our simulation game serves as a robust tool for translating knowledge into practice. However, the study’s reliance on collaboration with busy healthcare and disaster response professionals may limit engagement. Moreover, the absence of direct public and patient involvement in the research design, though partially mitigated by engaging representative organizations, presents a potential limitation. Lastly, the challenge of obtaining real-time data from flood events could introduce recall bias, but triangulation of various data sources aims to address this issue. Despite these challenges, the study’s integration of long-term data from recent floods and focus on healthcare-specific crisis governance provides valuable insights for improving disaster preparedness.

Background Governments used travel bans during the COVID-19 pandemic to limit the introduction of new variant of concern (VoC). In the Netherlands, direct flights from South Africa were banned from 26 November 2021 onwards to curb Omicron (B.1.1.529) importation. Objectives This study retrospectively evaluated the effect of the South African travel ban and the timing of its implementation on subsequent Omicron infections in the Netherlands and, in order to help inform future decision-making, assessed alternative scenarios in which the reproduction number (R e) and volume of indirectly imported cases were varied. Design Descriptive analysis and modelling study. Outcome measure Time (days) from 26 November 2021 to reach 10 000 cumulative Omicron infections in the Netherlands. Methods To benchmark the direct importation rate of Omicron from South Africa, we used the proportion (n/N, %) of passengers arriving on two direct flights from South Africa to the Netherlands on 26 November 2021 with a positive PCR sequencing result for Omicron VoC infection. We scaled the number of directly-imported Omicron infections before and after the travel ban to the incidence in South Africa. We assumed that 10% of all cases continued to arrive via indirect routes, a 'failure rate' of 2% (ie, incoming Dutch citizens not adhering to quarantine on arrival) and an effective reproduction number (R e) of Omicron of 1.3. In subsequent analyses, we varied, within plausible limits, the R e (1.1-2.0) and proportion of indirectly-imported cases (0-20%). Results Compared with no travel ban, the travel ban achieved a 14-day delay in reaching 10 000 Omicron cases, with an additional day of delay if initiated 2 days earlier. If all indirect importation had been prevented (eg, European-wide travel ban), a 21-day delay could have been achieved. The travel ban's effect was negligible if R e was ≥2.0 and with a greater volume of ongoing importation. Conclusions Travel bans can delay the calendar timing of an outbreak but are substantially less effective for pathogens where importation cannot be fully controlled and tracing every imported case is unfeasible. When facing future disease outbreaks, we urge policy-makers to critically weigh up benefits against the known socioeconomic drawbacks of international travel restrictions.