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124 results for “eVACUATE”
2017 Hurricane Irma Evacuation Survey Data
<p>Following Hurricane Irma in 2017, an online survey was distributed by researchers from the University of California, Berkeley to collect information on the individual choices of those impacted by the storm in Florida. Collected from October to December 2017, the data includes questions regarding risk perceptions, communications, evacuation decisions, potential usage of the sharing economy in disasters, opinions of evacuation management, and demographic information. The survey was distributed with the assistance of local partners (i.e., transportation agencies, emergency management agencies, local city and county governments, CBOs, and news outlets). Partners were allowed to post the survey using electronic communication methods including but not limited to: Facebook, Twitter, Nextdoor, agency websites, news websites, email listservs, and alert subscription services. The survey received 1,263 valid responses, of which 921 were completed. Subsequent papers using this data retained 645 cleaned survey responses for discrete choice modeling, based on the respondents' completion of key choice and demographic questions. The survey was incentivized with the chance to win one of five $200 gift cards. The survey questions are included in a separate PDF document. Please note that Q173-Q197 in the survey questions were not asked to respondents and no data was collected. </p> <p><strong>We request that those who download the data send a courtesy email to the lead author, Dr. Stephen Wong (swong1392@gmail.com). To ensure that any new research makes unique contributions to knowledge and does not duplicate past analyses, users are requested to read and cite publications using this data including:</strong></p> <p>Wong, S., Pel, A., Shaheen, S., Chorus, C. (2020). Fleeing from Hurricane Irma: Empirical Analysis of Evacuation Behavior Using Discrete Choice Theory. <em>Transportation Research Part D: Disasters and Resilience Section</em>. Retrieved from <a href="https://doi.org/10.1016/j.trd.2020.102227">https://www.sciencedirect.com/science/article/pii/S1361920919312866</a>. <strong>Note: The data file can also be accessed via this journal article. </strong></p> <p>Wong, S., Walker, J., & Shaheen, S. (2020). Bridging the Gap between Evacuations and the Sharing Economy. <em>Transportation</em>.<em> </em>Retrieved from <a href="https://link.springer.com/article/10.1007/s11116-020-10101-3">https://link.springer.com/article/10.1007/s11116-020-10101-3</a>.</p> <p>Wong, S.,<strong> </strong>Shaheen, S., & Walker, J. (2018). Understanding Evacuee Behavior: A Case Study of Hurricane Irma. Report. Retrieved from <a href="https://escholarship.org/uc/item/9370z127">https://escholarship.org/uc/item/9370z127</a></p> <p> </p> <p>Additional framing work on evacuations can be found here:</p> <p>Wong, S.<strong> </strong>(2020). Compliance, Congestion, and Social Equity: Tackling Critical Evacuation Challenges through the Sharing Economy, Joint Choice Modeling, and Regret Minimization. University of California, Berkeley. Dissertation. Retrieved from <a href="https://escholarship.org/uc/item/9b51w7h6">https://escholarship.org/uc/item/9b51w7h6</a>.</p>
Data for: Experimental data about the evacuation of preschool children from nursery schools, Part II: Movement characteristics and behaviour
<p>These datasets contain supplementary material for the article " Experimental data about the evacuation of preschool children from nursery schools, Part II: Movement characteristics and behaviour " accepted to Fire Safety Journal on April 16, 2023 (DOI <a href="https://doi.org/10.1016/j.firesaf.2023.103797">10.1016/j.firesaf.2023.103797</a>). The article presents experimental data sets on the evacuation movement and behaviour of preschool children observed during 15 evacuation drills in 10 nursery schools in the Czech Republic involving 970 children (3-7 years of age) and 87 staff members. </p> <p>In the presented spreadsheets, raw experimental data on speed-density and flow-density relationships are provided separately for corridors, straight staircases (flights, landings, and entire staircase), and doorways. The movement travel speed ('Speed') is expressed in [m·s<sup>-1</sup>], specific flow ('Flow') in [pers·s<sup>-1</sup>·m<sup>-1</sup>], density variable is expressed in the units of [pers·m<sup>−2</sup>] ('Density1') and [m<sup>−2</sup>·m<sup>−2</sup>] ('Density2'). Observations made for the different age groups of children are distinguished by letters: 'J' – Junior, 'S' – Senior, 'S+' - Senior+, 'M' – Mixed. In speed-density data sets, observations for walking children are denoted as 'W', for running children as 'R' (e.g., 'JW' – Junior walking). Speed-density data points that were calculated by excluding waiting times of children (only in the spreadsheets for corridors and landings of straight staircases) are marked 'M' after age group denotation (e.g., 'SWM-Speed' – modified speed data points for Senior walking children).</p>
2018 Carr Wildfire Evacuation Survey Data
<p>Following the 2018 Carr Wildfire, an online survey was distributed by researchers from the University of California, Berkeley to collect information on the individual choices of those impacted by the fires in the Redding, California area. Collected from March to April 2019, the data includes questions regarding risk perceptions, communications, evacuation decisions, potential usage of the sharing economy in disasters, opinions of evacuation management, and demographic information. The survey was distributed with the assistance of local partners (i.e., transportation agencies, emergency management agencies, local city and county governments, CBOs, and news outlets). Partners were allowed to post the survey using electronic communication methods including but not limited to: Facebook, Twitter, Nextdoor, agency websites, news websites, email listservs, and alert subscription services. The survey received 647 valid responses, of which 338 were completed. Subsequent papers using this data retained 284 cleaned survey responses for discrete choice modeling, based on the respondents' completion of key choice and demographic questions. The survey was incentivized with the chance to win one of ten $200 gift cards. The survey questions are included in a separate Word document.</p> <p>We request that those who download the data send a courtesy email to the lead author, Dr. Stephen Wong (swong1392@gmail.com). To ensure that any new research makes unique contributions to knowledge and does not duplicate past analyses, users are requested to read and cite publications using this data including:</p> <p>Wong, S., Broader, J., Walker, J. & Shaheen, S. (2021). Understanding California Wildfire Evacuee Behavior and Joint Choice-Making. Retrieved from <a href="https://escholarship.org/uc/item/4fm7d34j">https://escholarship.org/uc/item/4fm7d34j</a></p> <p>Wong, S., Walker, J., & Shaheen, S. (2020). Role of Trust and Compassion in Resource Sharing in Evacuations: A Case Study of the 2017 and 2018 California Wildfire. <em>International Journal of Disaster Risk Reduction. </em><a href="https://escholarship.org/content/qt1zm0q2qc/qt1zm0q2qc.pdf">https://www.sciencedirect.com/science/article/abs/pii/S2212420920314023</a></p> <p>Wong, S., Broader, J., Shaheen, S. (2020). Review of California Wildfire Evacuations from 2017 to 2019. Retrieved from <a href="https://escholarship.org/uc/item/5w85z07g">https://escholarship.org/uc/item/5w85z07g</a></p> <p>Wong, S. & Shaheen, S. (2019). Current State of the Sharing Economy and Evacuations: Lessons from California. SB 1 Report. Retrieved from <a href="https://escholarship.org/uc/item/16s8d37x">https://escholarship.org/uc/item/16s8d37x</a></p> <p> </p> <p>Additional framing work on evacuations can be found here:</p> <p>Wong, S. (2020). Compliance, Congestion, and Social Equity: Tackling Critical Evacuation Challenges through the Sharing Economy, Joint Choice Modeling, and Regret Minimization. University of California, Berkeley. Dissertation. <a href="https://escholarship.org/uc/item/9b51w7h6">https://escholarship.org/uc/item/9b51w7h6</a></p>
2017 December California Wildfires Evacuation Survey Data
<p>Following the December Southern California Wildfires in 2017, an online survey was distributed by researchers from the University of California, Berkeley to collect information on the individual choices of those impacted by the fires in California. Collected from March to July 2018, the data includes questions regarding risk perceptions, communications, evacuation decisions, potential usage of the sharing economy in disasters, opinions of evacuation management, and demographic information. The survey was distributed with the assistance of local partners (i.e., transportation agencies, emergency management agencies, local city and county governments, CBOs, and news outlets). Partners were allowed to post the survey using electronic communication methods including but not limited to: Facebook, Twitter, Nextdoor, agency websites, news websites, email listservs, and alert subscription services. The survey received 552 valid responses, of which 303 were completed. Subsequent papers using this data retained 226 cleaned survey responses for discrete choice modeling, based on the respondents' completion of key choice and demographic questions. The survey was incentivized with the chance to win one of five $200 gift cards. The survey questions are included in a separate PDF document.</p> <p>We request that those who download the data send a courtesy email to the lead author, Dr. Stephen Wong (swong1392@gmail.com). To ensure that any new research makes unique contributions to knowledge and does not duplicate past analyses, users are requested to read and cite publications using this data including:</p> <p>Wong, S., Broader, J., Walker, J. & Shaheen, S. (2021). Understanding California Wildfire Evacuee Behavior and Joint Choice-Making. Retrieved from <a href="https://escholarship.org/uc/item/4fm7d34j">https://escholarship.org/uc/item/4fm7d34j</a></p> <p>Wong, S., Walker, J., & Shaheen, S. (2020). Role of Trust and Compassion in Resource Sharing in Evacuations: A Case Study of the 2017 and 2018 California Wildfire. <em>International Journal of Disaster Risk Reduction. </em><a href="https://escholarship.org/content/qt1zm0q2qc/qt1zm0q2qc.pdf">https://www.sciencedirect.com/science/article/abs/pii/S2212420920314023</a></p> <p>Wong, S., Chorus, C., Shaheen, S. & Walker, J. (2020). A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study. <em>Travel Behaviour and Society.</em> Retrieved from <a href="https://www.sciencedirect.com/science/article/pii/S2214367X19303291"> https://www.sciencedirect.com/science/article/pii/S2214367X19303291</a></p> <p>Wong, S., Broader, J., Shaheen, S. (2020). Review of California Wildfire Evacuations from 2017 to 2019. Retrieved from <a href="https://escholarship.org/uc/item/5w85z07g">https://escholarship.org/uc/item/5w85z07g</a></p> <p>Wong, S. & Shaheen, S. (2019). Current State of the Sharing Economy and Evacuations: Lessons from California. SB 1 Report. Retrieved from <a href="https://escholarship.org/uc/item/16s8d37x">https://escholarship.org/uc/item/16s8d37x</a></p> <p> </p> <p>Additional framing work on evacuations can be found here:</p> <p>Wong, S. (2020). Compliance, Congestion, and Social Equity: Tackling Critical Evacuation Challenges through the Sharing Economy, Joint Choice Modeling, and Regret Minimization. University of California, Berkeley. Dissertation. <a href="https://escholarship.org/uc/item/9b51w7h6">https://escholarship.org/uc/item/9b51w7h6</a></p>
Dataset of traffic dynamics during the 2019 Kincade Wildfire Evacuation
<p>This dataset has been sourced from the Performance Measurement System of the California Department of Transportation. The data has been processed, analysed, presented and summarized in the paper: <em>Rohaert et al., ‘Traffic dynamics during the 2019 Kincade wildfire evacuation’, [Submitted for peer-review to an international journal.], 2022.</em></p> <p><strong>CRediT author statement</strong></p> <p><strong>Arthur Rohaert: </strong>Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. <strong>Erica D. Kuligowski: </strong>Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing - review & editing. <strong>Adam Ardinge: </strong>Conceptualization, Formal analysis, Investigation, Methodology, Resources, Validation, Writing - review & editing. <strong>Jonathan Wahlqvist:</strong> Conceptualization, Formal analysis, Investigation, Methodology, Resources, Supervision, Validation, Writing - review & editing. <strong>Steven M.V. Gwynne: </strong>Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing - review & editing. <strong>Amanda Kimball: </strong>Conceptualization, Funding acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Validation, Writing - review & editing. <strong>Noureddine Bénichou: </strong>Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing - review & editing. <strong>Enrico Ronchi: </strong>Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing - original draft, Writing - review & editing</p> <p><strong>Acknowledgements</strong></p> <p>This work has been funded under award 60NANB20D191 from the National Institute of Standards and Technology (NIST), U.S. Department of Commerce. The authors would like to thank the WUI-NITY team (Guillermo Rein, Nikolaos Kalogeropoulos, Harry Mitchell, Max Kinateder, Maxime Berthiaume). The authors also acknowledge the technical panel of the project for their support and guidance: Carole Adam, Amy Christianson, Tom Cova, Lauren Folk, Abishek Gaur, Paolo Intini, Justice Jones, Bryan Klein, Chris Lautenberger, Ruggiero Lovreglio, Jerry McAdams, Ruddy Mell, Elise Miller-Hooks, Cathy Stephens, Steve Taylor, Sandra Vaiciulyte, Xilei Zhao, Rita Fahy, Lucian Deaton, and Michele Steinberg. </p> <p> </p>
Dataset for the article "Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes"
<p>This dataset include the data needed to create the socio-hydrological model to simulate human evacuation processes via a transportation network before a flood hits the residential area. Source code, in JAVA, for generating households in the agent-based model are also provided. </p>
HUMANE internal case study: eVACUATE #1
<p>This case study was conducted on 14 December 2015. The purpose was to evaluate the usefulness of the HUMANE approach as perceived by relevant developers (software engineers), and additionally ask if the HUMANE typology facilitates cross-disciplinary understanding.</p> <p>The files included here provide a summary of the analysis and the transcript from a semi-structured focus group.</p>
HUMANE external case study: eVACUATE #2
<p>This case study was conducted in September to October 2016 with the purpose of providing an external validation of the HUMANE typology and method. This eVACUATE case-study comprises four different engagements in order to ensure a comprehensive evaluation: a quantitative online survey on the HUMANE design patterns; a quantitative survey on the HUMANE typology used for characterising Human-Machine Networks (HMNs); and two focus groups evaluating the HUMANE method (covering the profiling process, network diagramming, implication analysis, and design pattern approach).</p> <p>A summary of results, along with focus group transcripts, surveys and survey results are included here.</p>
Canadian Wildfire Evacuation Data
<p>Database of wildfire evacuations across the forested regions of Canada from 1980 to 2019. The database provides the data evaluated in the publication titled, “Wildfire evacuation patterns and syndromes across Canada’s forested regions,” which was submitted to Ecological Applications in November, 2021. The data file provides information on each documented wildfire evacuation and the characteristics of the fire that most likely led to the evacuation. The information on wildfire evacuations includes the location, the estimated population, whether it is a First Nations reserve, the estimated number of evacuess in five broad categories, the date that the evacuation order was issued, the date the order ended, and the reason why the order was issued. This information was compiled from more than 2,000 news reports, which were found using keyword searches in the Canadian Reference Centre, Canadian Newsstand, Canadian Research Index, Canadian Business and Current Affairs, and Proquest. Additional data were acquired by contacting provincial and territorial emergency management agencies and the Royal Canadian Mounted Police, as described in Beverly and Bothwell (2011; Wildfire evacuations in Canada 1980-2007; Natural Hazards 59:571-596). The fire characteristics include the fire size, ignition source, day of year on which it was first reported, and the database from which these values were derived. The databases for the original fire data include the National Burned Area Composite (NBAC), the National Fire Database (NFDB) fire polygon data, and the NFDB fire point data. The fire databases are available to the public at the CWFIS datamart (https://cwfis.cfs.nrcan.gc.ca/datamart).</p>
Data Set on Content Excerpts from Relevant Literature for a Scoping Review of Evacuation Training Methods in Buildings
<p>This Excel-file contains a set of data from a scoping review on methods for fire evacuation training in buildings. The review follows the PRISMA approach (Transparent Reporting of Systematic Reviews and Meta-Analyses) and systematically identifies 73 sources among scientific literature published between 1997 and 2022. The dataset contains information excerpted through a custom template on the employed training methods and technology, study information, participants, and contents of the discussion of the 73 sources of evidence that were identified in the systematic review process.</p>
Dataset of traffic dynamics during the 2020 Glass Wildfire Evacuation
<p>This dataset contains the </p> <p>This dataset has been sourced from the Performance Measurement System of the California Department of Transportation. The data has been processed, analysed, presented and summarized in the paper: <em>Rohaert et al., ‘T</em>he analysis of traffic data of wildfire evacuation: the case study of the 2020 Glass Fire<em>’, [Submitted for peer-review to an international journal.], 2023.</em></p> <p><strong>Acknowledgements</strong></p> <p>This work has been funded under award 60NANB21D118 from the National Institute of Standards and Technology (NIST), U.S. Department of Commerce.</p>
Data Set on the Literature Screening for a Scoping Review of Evacuation Training Methods in Buildings
<p>This data set contains all retrieved literature records of a scoping review on fire evacuation training methods in buildings together with the reasoning for their in- or exclusion in the review.</p>
Self-administered Lidocaine Gel for Pain-control During Cervical Preparation for Dilation and Evacuation
ClinicalTrials.gov study NCT02852434. IPD Sharing: NO. Countries: 1. Publications: 1.
Minimally Invasive Surgery and rtPA for Intracerebral Hemorrhage Evacuation
ClinicalTrials.gov study NCT00224770. IPD Sharing: Not stated. Countries: 4. Publications: 5.
Transcutaneous Electrical Nerve Stimulation (TENS) for Pain Control During Cervical Dilator Placement Prior to Dilation and Evacuation
ClinicalTrials.gov study NCT03868787. IPD Sharing: NO. Countries: 1. Publications: 12.
Minimally Invasive Surgery Plus Rt-PA for ICH Evacuation Phase III
ClinicalTrials.gov study NCT01827046. IPD Sharing: Not stated. Countries: 9. Publications: 5.
Sevoflurane as an Anesthetic During Dilation and Evacuation Procedures
ClinicalTrials.gov study NCT01048658. IPD Sharing: Not stated. Countries: 1. Publications: 19.
Transcranial Ultrasound Via Sonolucent Cranioplasty After Minimally Invasive Intracerebral Hemorrhage Evacuation
ClinicalTrials.gov study NCT05538286. IPD Sharing: NO. Countries: 1. Publications: 10.
Effects of Oxytocin on Bleeding Outcomes During Dilation and Evacuation
ClinicalTrials.gov study NCT02083809. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Cervical Preparation Before Dilation and Evacuation
ClinicalTrials.gov study NCT01751087. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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