Data visualization: Changing the way we respond to disasters

As our country responds to the COVID-19 global pandemic, we find ourselves with fewer emergency response resources each day. Even though states are starting to reopen, we still have a battle at hand.

While facing an unprecedented event, the possibility of other emergencies unfolding are not placed on hold. In fact, June marked the beginning of the 2020 hurricane season, which is projected to be 50-percent more severe than previous years.

According to the National Oceanic and Atmospheric Association (NOAA), between 1980 and 2019, the annual average for weather/climate disasters was 6.6 events per year (CPI-adjusted). However, the annual average for the past five years (2015-2019) has been 13.8 events per year (CPI-adjusted).

Under a continued growth in greenhouse emission, natural disasters are expected to occur more often in the coming years according to an analysis by the International Monetary Fund. As the number of natural disasters continue to rise, communities face the difficult challenge of responding and recovering while reopening. We have no choice but to prepare ourselves accordingly to respond to multiple crises at once.

Navigating coronavirus and the impacts of hurricanes requires answers to questions not previously explored. This dilemma gives us much to tackle and understand, including:

  1. How do we social distance while in shelters?
  2. How can we tackle responses with a low count of first responders?
  3. If hospitals are destroyed, how can we treat patients and handle emergencies?

The answers lie in data analytics. Through the use of collecting and reporting the appropriate data, we can measure and address performance concerns to improve processes, allowing emergency response agencies to shorten the recovery cycle after a disaster as well as shorten response times.

Deploying analytics and decision science can help us address and solve complex problems such as the ones we face today. Combining data visualization technology with proprietary geospatial and machine learning driven techniques, the collection of historical data demonstrates trends of high-risk periods and structures, allowing for proactive preparedness and responsiveness in an expedited timeline.

When originally analyzing the impact of a hurricane, only wind swaths were examined. However, data analytics disclosed that precipitation and hurricane type are also influencers. After a hurricane has made an impact, data has been helpful with understanding where damage has occurred and the emergency response actions that need to take place in the given area. Through the dashboard deployment of damage breakdown and evacuation and shelter options, teams are able to expedite the recovery process and allocate resources more effectively. Additionally, data analytics can accelerate federal assistance applications, allowing states to recover and reopen more quickly.

With data visualization tools, government and emergency response leaders are empowered to make informed decisions during crises such as when a shelter in place mandate should be made and what it should look like. Through the utilization of data analytics, we can broaden our thought processes and think critically to reimagine how we respond to disasters.

Heather Gittings is Principle Strategic Advisor at Qlik.


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