Disasters are among the crises that can test the decision making skill of elected and appointed public officials from planning through response and recovery. The COVID‐19 crisis, a public health emergency rather than one with immediate damage to the built environment, has affected many aspects of community life. Experiences in responding to the pandemic will likely stimulate fresh planning initiatives for public health emergencies. How then should emergency planners approach planning and response tasks? The All‐Hazards approach has been a mainstay of both research and policymaking for over 40 years, but it has come under recent criticism. In this paper, we consider if the All‐Hazards approach to disaster management is still viable. Comparing the management needs that emerged in the pandemic with those of disasters from more familiar hazard agents, we conclude that the All‐Hazards approach is valid and can continue to guide policymakers in their hazard and disaster management activities.

Beginning slowly in the late 1970s, but accelerating in the 1990s, scholars in the engineering and social sciences tried to work across theoretical and cultural-disciplinary gaps to understand disasters holistically and to provide the science needed for policies that reduce risk. Alliances of social scientists and engineers specializing in structural, ocean, and environmental engineering have tackled problems relating, for example, to earthquakes and tsunamis, while at the same time advancing studies of crosscutting ideas such as community resilience. Much of that alliance began not in the basic research or laboratory world, but with partnerships of scholars working at the focal point of hazard-oriented policy systems and public education. This paper considers how scholars, research centers, and funding agencies have worked to advance an integrated research agenda.

When critical infrastructure system services are disrupted, households typically respond by reducing, delaying, or relocating their demand (e.g., delaying laundry), or augmenting supply (e.g., using a generator). While this phenomenon is well known, there has been little systematic empirical investigation of it. Focusing on electric power and water service interruptions and using revealed and stated preference survey data from Los Angeles County, California, we develop 24 mixed logit models, one each to predict the probability an individual undertakes a specified adaptation as a function of outage duration and characteristics of the individual. The analysis aims to determine: (1) how common different household adaptations are; (2) how adaptation implementation varies with infrastructure type, outage duration, and uses of the service; (3) what household characteristics are associated with implementation of different adaptations; and (4) how adaptations tend to occur together. The percentage of individuals who report doing an adaptation varies greatly across adaptations and outage durations, from 2% to 88%. In general, adaptations that require moving out of the home are the least common of those investigated. For electric power outages, adaptations that could be done at home are less likely as the outage duration increases, while those that require going somewhere are more likely as the duration increases. For water outages, all adaptations (except delaying consumption) are more likely as an outage lasts longer. Using electric power or water for medical devices and/or work and business has a large effect on the likelihood of implementing many adaptations. Preevent conservation habits are also associated with an increased likelihood of implementing adaptations. The influence of household characteristics varies greatly across adaptations. There is evidence that some adaptations tend to occur together (e.g., using water from lakes and the government) and others tend not to (e.g., delaying electricity use and going to a hotel). Knowing what kinds of adaptations are found among different segments of the population, how common they are, and when they are likely to be implemented can help policymakers know what sorts of crisis-coping behaviors to expect in their locality, and can help them to know the timeframe in which those adaptations would be implemented. This in turn can provide needed knowledge for how to support those adaptations. Such support could take the form of enhanced contacts and outreach in specific populations (e.g., medically fragile), advance planning (having materials on hand, or including adaptations in drills or exercises), or timely improvising as an event unfolds.