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How Big Data Is Boosting Emergency Preparedness

We never feel prepared when disaster strikes – from the devastation of Hurricanes Katrina and Sandy to the Pacific earthquake that moved the main island of Japan and caused several meltdowns at a nuclear power plant in 2011, the destruction of both natural and manmade disasters can seem both immeasurable and unpredictable.

 

The rise of big data, however, is making it increasingly possible for communities and organizations to predict when a disaster will strike, preparing individuals and getting them to safety or allowing them to minimize overall harm. The key comes from preemptive disaster management, from the data gathering and modeling and notification systems developed during the intervening calm. We should be looking to these data systems as our best hope for allaying uncertainty and fear.

 

Voluntary Preparation Matters

 

One way that data systems are helping communities prepare for emergencies is by allowing people to submit preemptive data that could be of value in an emergency, such as information about the makeup of their household. Do you need local first respondents to know that one of your children is deaf or someone in the household uses a wheelchair, so that this information can be taken into account in a rescue? There are programs that let people do just that.

 

Crafting Communications Systems

 

Another vital aspect of disaster preparedness is gathering communications data. All communities should have an emergency communications system in place that allows a central informational hub to send out alerts before, during, and after an event. Such a system can help people locate clean food and water or emergency housing, find an open evacuation route, or locate missing individuals.

 

Gun Activity Predicts Emergencies

 

The more data we have on a particular activity, from airline delay patterns to shooting injuries of all kinds, the better we can model future scenarios – it’s time to put such modeling capacities to work. With the number of mass shootings the U.S. has seen recently, the ability to model gun violence patterns is more pressing than ever before.

Currently, the major problem is that we track the number of homicides that occur, but we don’t track the total number of people shot. Knowing how many people were shot would be more valuable from a data perspective and would allow us to determine the likelihood of future gun violence.Consider, for example, that in 2000, the Baltimore police chief called non-fatal shootings “unfinished business,” giving a clear sense of the intention of such violence, yet those initial shootings wouldn’t be tracked.

 

Data Builds Resiliency

 

Communities are often remarkably resilient in the wake of tragedy, but at this point in time, that resiliency stems largely from internal, human resources, not from the act of careful preparation. To further boost this trait, FEMA is actively improving flood monitoring software , the National Institute for Building Services is reviewing studies on hazard mitigation and updating their reports, and the United States Geological Survey is trying to make its current streamflow data more useful to environmental management.

 

The more we know about our environment and the more data-backed precautions we take as communities, the more likely we are to be able to predict the outcomes of hurricanes, earthquakes, and similar disasters – while acting accordingly.

 

When disaster strikes, people tend to feel helpless – and in the moment, that may well be the case. However, by preparing for an emergency before it strikes, we reduce the likelihood that we’ll be trapped or isolated from communication and we can even take steps to reduce the final damage before disaster strikes, by shoring up buildings or creating evacuation plans. We can only do these things, however, because of the power of data collection and predictive modeling. It’s time we use that power to its fullest.

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