Hurricane Sandy’s impact on the predisaster homeless and homeless shelter services in New Jersey

2016 ◽  
Vol 14 (1) ◽  
pp. 7 ◽  
Author(s):  
Marc R. Settembrino, PhD
Keyword(s):  
New Jersey ◽  
Emergency Response ◽  
Hurricane Sandy ◽  
Homeless Shelters ◽  
Atlantic City ◽  
Ethnographic Research ◽  
Homeless Shelter ◽  
Emergency Assistance ◽  
Management Literature ◽  
Shelter Services

Presently, there is little research on how people experiencing homelessness prepare for, respond to, and recover from disasters. Existing emergency management literature does not provide an understanding of how disasters affect homeless shelter services. The present study seeks to fill these gaps by examining how Hurricane Sandy impacted homeless shelters and their guests in New Jersey. Presenting findings from ethnographic research in Atlantic City and Hoboken, this study identifies several areas in which homeless shelters and their guests may be able to assist in emergency response and disaster recovery such as preparing meals for victims, sorting and processing donated items, and assisting victims in filing for emergency assistance.

Emergency evacuation orders: Considerations and lessons from Hurricane Sandy

2014 ◽  
Vol 12 (3) ◽  
pp. 219 ◽  
Author(s):  
Patrick D. O’Neil, PhD, Capt. USN (ret)
Keyword(s):  
New Jersey ◽  
Emergency Evacuation ◽  
Hurricane Sandy ◽  
The State ◽  
Atlantic City ◽  
Legal Authority ◽  
Emergency Shelter ◽  
Public Managers ◽  
Emergency Actions ◽  
The City

This article analyzes the problems surrounding the execution of emergency evacuation orders by evaluating Hurricane Sandy and the emergency actions taken by the State of New Jersey and the City of Atlantic City New Jersey. The analysis provides an overview of the legal authority granting emergency powers to governors and mayors to issue evacuation proclamations in addition to an evaluation of the New Jersey’s emergency evacuation mandate and subsequent compliance. The article concludes with provision of planning and preparedness recommendations for public managers facing similar hazards, including a recommendation for provision of emergency shelter contingencies within the threat zone in anticipation of citizen noncompliance evacuation orders.

EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013

Data Series ◽  
10.3133/ds887 ◽  
2014 ◽  
Author(s):  
C. Wayne Wright ◽  
Rodolfo J. Troche ◽  
Christine J. Kranenburg ◽  
Emily S. Klipp ◽  
Xan Fredericks ◽  
...  
Keyword(s):  
New Jersey ◽  
Hurricane Sandy ◽  
Barnegat Bay

EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface

Data Series ◽  
10.3133/ds767 ◽  
2014 ◽  
Author(s):  
C. Wayne Wright ◽  
Xan Fredericks ◽  
Rodolfo J. Troche ◽  
Emily S. Klipp ◽  
Christine J. Kranenburg ◽  
...  
Keyword(s):  
New Jersey ◽  
Hurricane Sandy ◽  
Coastal Topography

Crowdsourcing Incident Information for Emergency Response using Open Data Sources in Smart Cities

2018 ◽  
Vol 2672 (1) ◽  
pp. 198-208 ◽  
Author(s):  
Fan Zuo ◽  
Abdullah Kurkcu ◽  
Kaan Ozbay ◽  
Jingqin Gao
Keyword(s):  
Social Media ◽  
Prior Knowledge ◽  
Emergency Response ◽  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Smart Cities ◽  
Hurricane Sandy ◽  
Support Vector ◽  
Twitter Data ◽  
Emergency Events

Emergency events affect human security and safety as well as the integrity of the local infrastructure. Emergency response officials are required to make decisions using limited information and time. During emergency events, people post updates to social media networks, such as tweets, containing information about their status, help requests, incident reports, and other useful information. In this research project, the Latent Dirichlet Allocation (LDA) model is used to automatically classify incident-related tweets and incident types using Twitter data. Unlike the previous social media information models proposed in the related literature, the LDA is an unsupervised learning model which can be utilized directly without prior knowledge and preparation for data in order to save time during emergencies. Twitter data including messages and geolocation information during two recent events in New York City, the Chelsea explosion and Hurricane Sandy, are used as two case studies to test the accuracy of the LDA model for extracting incident-related tweets and labeling them by incident type. Results showed that the model could extract emergency events and classify them for both small and large-scale events, and the model’s hyper-parameters can be shared in a similar language environment to save model training time. Furthermore, the list of keywords generated by the model can be used as prior knowledge for emergency event classification and training of supervised classification models such as support vector machine and recurrent neural network.

scholarly journals Estuarine bed-sediment-quality data collected in New Jersey and New York after Hurricane Sandy, 2013

Data Series ◽  
10.3133/ds905 ◽  
2015 ◽  
Author(s):  
Jeffrey M. Fischer ◽  
Patrick J. Phillips ◽  
Timothy J. Reilly ◽  
Michael J. Focazio ◽  
Keith A. Loftin ◽  
...  
Keyword(s):  
New York ◽  
New Jersey ◽  
Sediment Quality ◽  
Hurricane Sandy ◽  
Quality Data ◽  
Bed Sediment

Abstract WP389: Improving Systems of Care With Stroke Severity Adjusted EMS Triaging and Bypass Criteria Protocols to a Comprehensive Stroke Center

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Mary E Deleener ◽  
Brett Greenfield
Keyword(s):  
New Jersey ◽  
Near Infrared ◽  
Assessment Tool ◽  
Systems Of Care ◽  
Hospital Setting ◽  
Large Vessel ◽  
Atlantic City ◽  
Stroke Severity ◽  
Comprehensive Stroke Center ◽  
Stroke Center

A validated pre-hospital assessment tool to detect severe strokes including intracranial hemorrhages and large vessel occlusions along with protocols for bypassing to comprehensive stroke centers remains an ongoing debate. The long term goals align with the emphasis of developing formalized stroke severity adjusted EMS triaging and bypass protocols to recognize both large vessel ischemic and intracerebral hemorrhagic stroke patients early in the pre-hospital setting with the utilization of a recognized, validated assessment tool, formal bypass criteria protocols, and formalized training for emergency medical service personnel. These goals align with the topic of careful selection of patients who meet strict criteria for bypassing acute stroke ready and primary stroke centers throughout the Southeastern New Jersey region which includes one acute ready hospital and two primary stroke centers to the closest Comprehensive Stroke Center in Atlantic City, New Jersey. The first specific aim is to analyze the EMS field diagnostic accuracy completed by both AtlantiCare EMS ACLS providers and Mid Atlantic Medevac EMS personnel. A therapeutic bypass yield will be analyzed in order to determine the effectiveness of the formalized training to conduct effective stroke severity EMS triaging assessments and a formal bypass protocol to the Comprehensive Stroke Center in Atlantic City, New Jersey. Sensitivity results of the near-infrared (NIR) technology device as a pre-scanning tool for hemorrhages prior to CT scan and operator error will be analyzed. Final diagnosis, CT results, and the need for comprehensive services will serve as the sole factor for the therapeutic bypass yield analysis. The second aim is to analyze the percentage of bypassed patients to the Comprehensive Stroke Center that undergo comprehensive interventions or medical services. Policy/Protocol Design (refer to images) IRB Information : FWA#00011915 and RP# 15-039ex IRB

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