Are vulnerable communities digitally left behind in social responses to natural disasters? An evidence from Hurricane Sandy with Twitter data

2019 ◽  
Vol 108 ◽  
pp. 1-8 ◽  
Author(s):  
Zheye Wang ◽  
Nina S.N. Lam ◽  
Nick Obradovich ◽  
Xinyue Ye
Keyword(s):  
Natural Disasters ◽  
Hurricane Sandy ◽  
Social Responses ◽  
Vulnerable Communities ◽  
Left Behind ◽  
Twitter Data

scholarly journals Return Migration after Natural Disasters

2017 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Mikiyasu Nakayama ◽  
Nicholas Nicholas Bryner ◽  
Satoru Mimura
Keyword(s):  
United States ◽  
Natural Disasters ◽  
Hurricane Katrina ◽  
Case Studies ◽  
Return Migration ◽  
The United States ◽  
Hurricane Sandy ◽  
Indian Ocean Tsunami ◽  
Special Issue ◽  
Post Disaster

This special issue features policy priorities, public perceptions, and policy options for addressing post-disaster return migration in the United States, Japan, and a couple of Asian countries. It includes a series of case studies in these countries, which are based on a sustained dialogue among scholars and policymakers about whether and how to incentivize the return of displaced persons, considering social, economic, and environmental concerns. The research team, composed of researchers from Indonesia, Japan, Sri Lanka, and the United States, undertook a collaborative and interdisciplinary research process to improve understanding about how to respond to the needs of those displaced by natural disasters and to develop policy approaches for addressing post-disaster return. The research focused on the following three key issues: objectives of return migration (whether to return, in what configuration, etc.), priorities and perceptions that influence evacuees’ decision-making regarding return, and policies and practices that are used to pursue return objectives. This special issue includes ten articles on the following disaster cases: the Great East Japan Earthquake in 2011, Hurricane Katrina in 2005 and Hurricane Sandy in 2012, the Great Indian Ocean Tsunami in 2004, and the Great Sumatra Island Earthquake in 2009. Important lessons for the future were secured out of these case studies, covering the entire phase of return, namely planning, implementation, and monitoring.

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.

Exploring Insurance and Natural Disaster Tweets Using Text Analytics

2017 ◽  
Vol 4 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Tylor Huizinga ◽  
Anteneh Ayanso ◽  
Miranda Smoor ◽  
Ted Wronski
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Association Rule ◽  
Association Rule Mining ◽  
Insurance Companies ◽  
Insurance Company ◽  
Text Analytics ◽  
Rule Mining ◽  
Twitter Data ◽  
The World

This study explores twitter data about insurance and natural disasters to gain business insights using text analytics. The program R was used to obtain tweets that included the word ‘insurance' in combination with other natural disaster words (e.g., snow, ice, flood, etc.). Tweets related to six top Canadian insurance companies as well as the top five insurance companies from the rest of the world, including the new entrant Google Insurance, was collected for this study. A total of 11,495 natural disaster tweets and 19,318 insurance company tweets were analyzed using association rule mining. The authors' analysis identified several strong rules that have implications for insurance products and services. These findings show the potential text mining applications offer for insurance companies in designing their products and services.

scholarly journals A comparison of burn related injuries following the natural disaster Super Storm Hurricane Sandy to the National Burn Repository of the American Burn Association

2016 ◽  
Vol 4 ◽  
pp. 1-4 ◽  
Author(s):  
Michael Kalina ◽  
Grigoriy Malyutin ◽  
Michael L. Cooper
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Burn Injury ◽  
Total Body Surface Area ◽  
Retrospective Chart Review ◽  
Hospital Length ◽  
Outcome Data ◽  
Hurricane Sandy ◽  
University Hospital ◽  
Hospital Length Of Stay

Abstract Background Burn related injuries from natural disasters are not well described and natural disasters are not identified as an etiology of burn injury in the National Burn Repository (NBR) of the American Burn Association. The natural disaster Super Storm Hurricane Sandy had devastating effects. Our goal was to detail the burn related injuries following this natural disaster and to compare the data to the NBR. Methods This was a retrospective chart review of thirty four patients who sustained burn related injuries following Super Storm Hurricane Sandy (SSHS) and were managed at Staten Island University Hospital Burn Center. Institutional Review Board approval was obtained. Data variables included age, gender, race, past medical history (PMHx), burn type, percentage total body surface area (%TBSA), hospital length of stay (HLOS), and mortality. We compared data from SSHS to the 2003-2013 NBR. Categorical data were summarized using frequency counts, percentages and Clopper-Pearson 95 % confidence interval for proportion. Continuous outcome data were summarized by descriptive statistics. Data analyses performed with SAS® System Version 9.3 (SAS Institute Inc., Cary, NC) and p < 0.05 was significant. Results In the SSHS group, average age was 36 + 24 years, range 1-80 years, and 44.1 % were males (15/34, 95 % CI: 27.2 - 62.1). Caucasians comprised 58.8 %, (20/34, 95 % CI: 40.7, 75.4) and 73.5 % had no PMHx (25/34, 95 % CI: 55.6, 87.1). The most common burn type was scald, 55.9 %, (19/34, 95 % CI: 37.9, 72.8) and %TBSA ranged 1 %–47 %, average of 7 % + 12 %. The average HLOS was 13 + 26 days, range of 1–113 days. Mortality was 2.9 % (1/34, 95 % CI: 0.07–15). In comparison, the NBR reported an average age of 32 years and 69 % were males. Caucasians comprised 59.1 %. The most common burn type was flame, 43.2 % and the %TBSA ranged 1 %–9.9 %. HLOS ranged 8.4–10.2 days and mortality was 3.4 %. Conclusion We conclude that burn related injuries following a natural disaster differ as compared to those most commonly reported in the NBR.

scholarly journals Type of Disaster Exposure Affects Functional Limitations of Older People 6 Years Later

2019 ◽  
Vol 75 (11) ◽  
pp. 2139-2146
Author(s):  
Rachel Pruchno ◽  
Maureen Wilson-Genderson ◽  
Allison R Heid ◽  
Francine P Cartwright
Keyword(s):  
Older People ◽  
Natural Disasters ◽  
Traumatic Stress ◽  
Functional Limitations ◽  
Hurricane Sandy ◽  
Ongoing Research ◽  
Property Loss ◽  
Traumatic Distress ◽  
Independent Effects ◽  
Disaster Exposure

Abstract Background Natural disasters, including earthquakes, tsunamis, tornadoes, and hurricanes, are traumatic events that simultaneously affect the lives of many people. Although much is known about the effects that natural disasters have on mental health, little is known about how natural disasters affect physical health. These analyses add to the literature by examining the ways in which four types of disaster exposure (geographic, peri-traumatic stress, personal and property loss, and poststorm hardship) experienced by older people during and after Hurricane Sandy affected functional limitations. Methods We analyzed five waves of data from the ORANJ BOWL panel (“Ongoing Research on Aging in New Jersey: Bettering Opportunities for Wellness in Life”) using multilevel mixed-effects models. Results We found that although peri-traumatic stress and poststorm hardship each had independent effects on functional limitations, the effects of peri-traumatic stress dominated and were evident 6 years after the hurricane. Geographic exposure and personal/property loss were not associated with functional limitations. Conclusions These findings add important information to what is known about older people who experience a natural disaster and suggest opportunities for intervention. Finding that an individual’s emotional response during the disaster plays an important role in the development of functional limitations suggests that reduction of exposure to traumatic stress during a storm (ie, evacuation from a storm area) may be important for older people. Likewise, interventions immediately after a disaster that target older people who experience high levels of peri-traumatic distress may be needed in order to alleviate functional limitations before they develop.

Community-based evaluation for the development of a sustainable disaster early warning system

2012 ◽  
Vol 10 (4) ◽  
pp. 293 ◽  
Author(s):  
Ashutosh Sutra Dhar, PhD ◽  
Mehedi Ahmed Ansary, PhD
Keyword(s):  
Pilot Study ◽  
Natural Disasters ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Loss Reduction ◽  
Community Based ◽  
Vulnerable Communities ◽  
Catastrophic Loss ◽  
Questionnaire Surveys

Early warning plays a major role in catastrophic loss reduction during natural disasters. An early warning system should address the needs of the disasterprone community for the system to be effective and sustainable. This article presents a community-based evaluation of an existing early warning system in a disaster- prone district of Bangladesh. The evaluation is based on several questionnaire surveys carried out within the vulnerable communities in the district. A new satellite- based early warning system was also deployed around the district on a pilot basis.The challenges for the new satellite-based system are discussed based on this pilot study. The study revealed that the community level questionnaire survey could be effective for the design of a sustainable early warning system.

scholarly journals The complexity of maladaptation strategies to disasters: The case of Muzarabani, Zimbabwe

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Siduduziwe Ncube-Phiri ◽  
Chipo Mundavanhu ◽  
Blessing Mucherera
Keyword(s):  
Natural Disasters ◽  
Emergency Services ◽  
Mitigation Strategies ◽  
Services Research ◽  
Vulnerable Communities ◽  
The Past ◽  
The World ◽  
Sustainable Utilisation ◽  
The Impact ◽  
Collaborative Efforts

Over the past decade disasters have increased both in complexity and multiplicity, worseningthe plight of vulnerable communities the world over. Many communities have devised copingmechanisms to mitigate the impact, but communities such as Muzarabani in Zimbabweremain susceptible to disasters. This article seeks to analyse whether the coping measuresapplied make the communities safe from or vulnerable to disasters. Information was obtainedthrough interviews, questionnaires and observations from four villages in Chadereka in theMuzarabani district. The results of this study indicated that households, government andnon-governmental organisations have come up with different mitigation strategies, suchas growing crops along river beds, livestock production, raised granaries and doorsteps,flood evacuation shelters and other emergency services. Research revealed that althoughviable, some of the strategies increased the community’s vulnerability. This article thereforerecommends sustainable utilisation of resources, and collaborative efforts to address the rootcauses, dynamic pressures and unsafe conditions in order to reduce the vulnerability of poorcommunities to natural disasters.

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