Equality of care in Emergency Management: Shelters & Equipment

Equality of care in Emergency Management ensures that the lives of our special needs population are valued proportionately to any other human life. Displaced individuals requiring additional support and resources face the highest morbidity rate during and post a natural disaster. Maintaining awareness of “at-risk” individuals is a top priority of Emergency Managers and prudent community members alike. Often it is up to the local Emergency Management Professionals (EMP) to plan for functional access during emergency situations. Weather a standalone Special Needs Shelter #SpNS or a distribution center for inventoried essential tools, prepositioning qualified Special Needs Shelter Equipment #SpNSE and having a facility identified to stand up a shelter is considered #bestpractice.

In a statement to the U.S. House of Representatives Subcomitte on Emergency Preparedness, the U.S. National Council on Disability (NCD) argued that “… Frustratingly … people with disabilities and others with access and functional needs in emergencies are frequently overlooked or have their needs minimized, despite the urgency that surrounds the need to account for people with disabilities in all phases of emergency management, including mitigation, preparedness, response, and recovery” [1]

SpNS are designed to accommodate individuals with physical, sensory, mental health, and cognitive conditions during emergencies. These shelters provide a safer environment for temporary residence, baseline medical care, communications support, and they must meet ADA standards for facility codes, and be outfitted with ADA compliant equipment. A SpNS is not a hospital, but often extreme conditions transform the mission into an improvised medical facility. Individuals requiring functional access typically need an elevated level of care and they often have a nurse who accompanies them if that union was not severed because of the catastrophic event. It is important to recognize that not all counties have a SpNS and often rural counties cannot secure the funding necessary to procure qualified SpNSE necessary for standing up a temporary SpNS.

It is widely recognized that individuals with special needs are among the most vulnerable during natural disasters, due to their reliance on specialized medical equipment that is not always available during emergency situations. Some examples of SpNSE typically made available at SpNS follows:

1. Accessible Facilities: ADA compliant ramps, handrails, and wide doorways to accommodate mobility aids.

2. Medical Equipment: ADA compliant Cots, oxygen concentrators, wheelchairs, crutches, and numerous miscellaneous medical devices.

3. Communication Tools: Devices to aid those with hearing or visual impairments, such as TTY devices and braille signage.

4. Comfort Items: ADA compliant Cots with soil resistant mattresses, Weighted blankets, noise-cancelling headphones, and other items to help manage sensory overload.

SpNSE is held to the highest standard, this equipment must meet the needs of our most at risk populations during the most extreme conditions our Earth has to offer. These realities underscore the importance of inclusive disaster Readiness, Response, and Recovery #R3 strategies.

Investing in these shelters and their equipment is not just about compliance with regulations - it's about inclusivity, empathy, and ensuring everyone in our community has access to safety and care during emergencies. As we continue to improve our emergency management strategies, let's remember the importance of special-needs shelters and the critical role they play in our community. Let's strive to equip them with the best tools and resources, to provide the highest level of care for those who need it most. #EmergencyManagement #SpecialNeeds #Inclusivity #CommunitySafety #Westcot #innovation

J. Shaun Taylor

@XbombModifiedTrailers

@IntegrityMedicalSolutions

The Benefits of Investing in a Mobile Command Center

The case for investing in a mobile command center (MCC) for police departments and other public safety agencies is strong – they’re easily customizable, can be as high-tech as you need them to be, and they’re appropriate for a wide variety of use cases.

With the proper mobile command center, police officers and first responders have the ability to host all of their necessary functions in a single area, all while being able to move throughout their community as needed.

As public safety technology and 911 Communications continue to evolve, the benefits for investing in a mobile command center are as compelling as ever.

TO READ ON, CLICK HERE TO VISIT THIS BLOG POST BY LISA MACGILLIVRAY AT CHICOMM BLOG.

Leveraging Big Data And AI For Disaster Resilience And Recovery

By Alyson Chapman, Texas A&M University College of Engineering June 13, 2023

In a world where natural hazards can strike at any time with devastating consequences, reducing their impacts in advance may seem impossible.

The unpredictability of these events and their effects makes it challenging to anticipate and respond appropriately, leaving individuals and communities vulnerable to their destructive effects.

In 2017, Hurricane Harvey made landfall along the Texas coast as a category four hurricane and slowed to nearly 5 mph as it moved inland. Palacios experienced a storm surge exceeding 8 feet. The storm dumped 56 inches of rain in the Friendswood area and more than 60 inches near Nederland and Groves. The National Hurricane Center reported $125 million in damage because of Hurricane Harvey.

Now, researchers from the Zachry Department of Civil and Environmental Engineering at Texas A&M University have created models using big data and artificial intelligence (AI) to help communities prepare for future natural disasters, assess the impacts and monitor the recovery in near real time. They used data from Harvey to test these AI-centric solutions.

Led by Dr. Ali Mostafavi, Zachry Career Development Associate Professor, the Urban Resilience.AI Lab is leveraging AI and big data for predictive risk analysis, predictive infrastructure failure assessment, situational awareness during the event, monitoring of recovery and rapid assessment of the impacts of disasters.

“When facing hazards, there are certain capabilities that AI and data science approaches provide or enhance that can improve the resiliency of communities to these disasters,” Mostafavi said. “Our vision over the past four or five years has been to improve disaster resilience by developing different classes of AI-based models that could provide foresights and insights critical for mitigation, preparedness, response and recovery.”

The growth of data from different types of sensors — from physical, social and other sensing technologies — has given researchers tremendous information to work with in creating these models.

“These days, cities and communities are essentially data factories. You can evaluate sensor data related to the condition of the community facing hazards from the traffic network cameras, people’s cell phone activities, power outage data, flood gauge data, satellite images and many other sources of technology that harness the heartbeat of the community,” Mostafavi said. “As our cities and communities become smarter with information and communication technologies, the amount of data generated grows.”

Mostafavi and his team in the Urban Resilience.AI Lab are taking the lead in harnessing community-scale big data to develop AI-based models with the potential to impact communities before, during and after a natural disaster or crisis.

Road Inundation Prediction

Roads are essential in urban cities, allowing goods, information and people to move from place to place. But during times of disaster, such as floods, road networks can be damaged or blocked, which impacts access to services such as hospitals, shelters and grocery stores. During floods in urban areas, vehicle accidents resulting from driving on flooded roads have been identified as a leading cause of fatalities, highlighting the failures of road networks.

Researchers have developed a deep-learning framework to effectively predict near-future flooding of roads. They tested the framework using three models, and the results showed that it can accurately predict the flooding status of roads with 98% precision and recall values of 96%. Researchers validated the models using the 2017 Hurricane Harvey flooding.

Knowing the flooding status of roads can help affected communities avoid flooded streets and aid emergency management agencies in planning evacuations and delivery of resources.

To read the rest of this article, visit https://today.tamu.edu/2023/06/13/leveraging-big-data-and-ai-for-disaster-resilience-and-recovery/