AMU Emergency Management Opinion Public Safety

Disaster Declaration Problems Again, Part II

As discussed in [link url=”https://amuedge.com/disaster-declaration-problems-again/” title=”my previous post”], it is important to gather the correct data and record the information in a format needed by the next level of government. This can ensure that a disaster declaration request has the best information possible to evaluate the need, and hopefully, approve the request for funds or resources.

Data Gathering

As noted in [link url=”https://amuedge.com/disaster-declaration-problems-again/” title=”part 1″], the declaration hinges on proving, through data, that the current level of government cannot adequately provide funding or resources for the current needs.

Data collection begins as the first responders hit the streets. The problem in most communities is a lack of data collection skills and a process that guides data collection. While some would argue that some communities might be overwhelmed and unable to perform this task, I would argue that they are already collecting the data to make their assets requests.

For example, if there are five commercial structures damaged in a certain area of town and there are also trapped persons; they are collecting this information to ask for a technical rescue team. Would it not make sense for them to take 30 seconds to a minute to advise their findings on a channel monitored by the local EMA? This way the local EMA can begin to plot this information and determine if local resources will meet the needs or if they should involve the state EMA to facilitate a quicker declaration.

Providing the first responders with a simple sheet that shows types or levels of damage will speed this information relay to the EMA or EOC.

GIS Participation

In addition to the first responders, the geographic information system (GIS) specialist has become one of the biggest assets in the EOC and the EMA.

The GIS specialist can utilize the layered mapping system to provide not only mapping but also data analysis. Each piece of data has a spatial component. For example, each house has an address, an XY Coordinate, and a valuation for tax purposes. Additionally, the census data for the same area may indicate poverty and an elderly population. 

From this data, one can identify an area that is flooded and has citizens who are not mobile and may not have the financial means to remove themselves from the situation and provide shelter beyond their primary residence.

All of these factors would provide a different need than the same location with a mid-30’s couple with an annual salary of $200,000. One could assume with the age and income that they could remove themselves and have financial means to afford temporary lodging until the insurance company provided a permanent fix.

Start Early

The quicker the application of the principles mentioned within, the greater the success with be when the community is looking for help during the worst of times. Be prepared.

Dr. Randall Hanifen serves as a shift commander at a medium-sized suburban fire department in the northern part of the Cincinnati area. Randall is the CEO/principal consultant of an emergency services consulting firm, providing analysis and solutions related to organizational structuring of fire and EMS organizations. He is the chairperson and operations manager for a county technical rescue team. From a state and national perspective, he serves as a taskforce leader for one of FEMA's urban search and rescue teams, which responds to presidential declared disasters. From an academic standpoint, Randall has a bachelor’s degree in fire administration, a master’s degree in executive fire service leadership, and a doctoral degree in business administration with a specialization in homeland security. He is the associate author of “Disaster Planning and Control” (Penwell, 2009), which provides first responders with guidance through all types of disasters.

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