Predicting community resilience and recovery after a disaster

Climate Report

After 9/11, I was asked by the Baltimore City Health Commissioner to help prepare the city for a radiation terrorism event, because my entire career up until that point had been in radiation-based medical imaging. I didn’t know anything about public health preparedness at the time, but I found it very fulfilling to work with the city health department and other first responders, especially fire and police. Public health preparedness science and research is more than multi-disciplinary, it’s trans-disciplinary, which is what makes it fun.

Master the VocabularyConnecting behavioral and social science

The Johns Hopkins Center for Public Health Preparedness has a particular interest in the mental and behavioral health challenges that people, organizations, and jurisdictions face during and after disasters. If you look at the disaster literature you will see references to dysfunction, which can be caused by either physical or psychological trauma. After a disaster, the number of people with psychological trauma exceeds the number of people with physical injury by as much as 40 to 1, but there is much more research and emergency response focus on the physical effects of a disaster rather than the psychosocial effects. Our interest and expertise in the behavioral science of disasters was the main reason that CDC’s Office of Public Health Preparedness and Response asked us to work on an innovative model and index to measure resilience in the United States.

Understanding resilience in disasters

You can think about resilience on two levels – on the individual level and at the community level. For individuals, we are interested in three things: psychological resistance before a disaster, resilience during a disaster, and recovery after the disaster. Resilience at this level reflects the ability of someone to spring back after experiencing trauma from a disaster. We think about community resilience like an ecosystem. In any ecosystem there is a minimum requirement for the system to successfully function and survive. The same is true for a community. So when we think about community resilience, we must not only think about the ability of a community to return to its pre-event level of functioning, but also assess how that community is working at its lowest point after a disaster and determine if that is a level where it can still function successfully – or even at all.

Modeling resilience

Example of COPEWELL model output showing overall pre-disaster resilience for all US counties.
Example of COPEWELL model output showing overall pre-disaster resilience for all US counties.

We approached our colleagues at the University of Delaware Disaster Research Center, who are experts in the sociological factors in disasters that lead to emergent collective behavior. This phenomenon refers to a group of every-day people coming together to aid the formal emergency response. The COPEWELL (“Composite of Post-Event Well-Being”) project was born out of this collaboration between experts in the psychological and sociological impacts of disasters on individuals and communities, along with experts in engineering, modeling, public health and healthcare, and other domains.

We realized that a static model with a single score for resilience would not capture the way a system changes over time and the many interrelated parts that make up a community. We came up with a system dynamics model, which allowed us to input different factors that characterize a community, including housing, communication, healthcare, and transportation. We then throw a disaster at the model and see how the community responds. Depending on the type of natural disaster or public health emergency, how a community functions plays out differently over time. For example, a pandemic usually builds slowly and reaches a peak before gradually decreasing, while a severe weather event spikes quickly and exponentially decreases. Different communities have different inherent characteristics that determine how well they can resist the negative effects of an event and how quickly they can recover. What is unique about COPEWELL is that it is a whole community model, not just a public health model, and looks at how the community functions over time, which allows you to derive a measure of resilience.

Putting the data to work

The COPEWELL model has been used to predict resilience after a disaster in all 3,100+ counties in the United States. We’ve also explored using the model at a more granular level, including at the neighborhood level in New York City. Experts are working on a web-based platform for the model that stakeholders such as government leaders and public health officials can use in their communities.

In addition to supporting the project, CDC has provided technical assistance and expertise to translate and apply the model in practice. Once more fully validated, the results from the model can be used to help identify and evaluate interventions to improve community resilience and accelerate recovery after a disaster.

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Source: CDC