toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author (up) Andrew Arnette; Christopher W. Zobel; Duygu Pamukcu pdf  isbn
openurl 
  Title Post-Impact Analysis of Disaster Relief Resource Pre-Positioning After the 2013 Colorado Floods Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 237-243  
  Keywords Disaster Operations Management; Facility Location; Humanitarian Operations  
  Abstract Pre-positioning of supplies is important to facilitate disaster relief operations, however it is only after a disaster event occurs that the effectiveness of the pre-positioning strategy can be properly assessed. With this in mind, this paper analyzes a risk-based pre-positioning algorithm, developed for the American Red Cross, in the context of its actual performance in the 2013 Colorado Front Range floods. The paper assesses the relative effectiveness of the pre-positioning approach with respect to historical asset placements, and it discusses changes to the model that are necessary to support such comparisons and allow for further model extensions.  
  Address University of Wyoming; Virginia Tech; Virginia Tech  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-23 ISBN 2411-3409 Medium  
  Track Analytical Modeling and Simulation Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes aarnette@uwyo.edu Approved no  
  Call Number Serial 2224  
Share this record to Facebook
 

 
Author (up) Anmol Haque; Duygu Pamukcu; Ruixiang Xie; Mohsen Zaker Esteghamati; Margaret Cowell; Jennifer L. Irish pdf  openurl
  Title Cascading Effects of Mass Gatherings on COVID-19 Infections from a Multi-hazard Perspective: A Case Study of New York City Type Conference Article
  Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021  
  Volume Issue Pages 218-227  
  Keywords COVID-19 pandemic, Mass gatherings, Multi-hazard, Vulnerability  
  Abstract The devastating economic and societal impacts of COVID-19 can be substantially compounded by other secondary events that increase individuals' exposure through mass gatherings such as protests or sheltering due to a natural disaster. Based on the Crichton's Risk Triangle model, this paper proposes a Markov Chain Monte Carlo (MCMC) simulation framework to estimate the impact of mass gatherings on COVID-19 infections by adjusting levels of exposure and vulnerability. To this end, a case study of New York City is considered, at which the impact of mass gathering at public shelters due to a hypothetical hurricane will be studied. The simulation results will be discussed in the context of determining effective policies for reducing the impact of multi-hazard generalizability of our approach to other secondary events that can cause mass gatherings during a pandemic will also be discussed.  
  Address Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-61-5 ISBN Medium  
  Track Analytical Modeling and Simulation Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management  
  Notes anmol91@vt.edu Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2327  
Share this record to Facebook
 

 
Author (up) Ayda Kianmehr; Duygu Pamukcu pdf  isbn
openurl 
  Title Analyzing Citizens’ Needs during an Extreme Heat Event, based on 311 Service Requests: A Case Study of the 2021 Heatwave in Vancouver, British Columbia Type Conference Article
  Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022  
  Volume Issue Pages 174-182  
  Keywords Extreme heat; 311 calls; weather-related variables; time-series analysis; hazard preparedness  
  Abstract Heat waves are becoming more common and intense with global climate change, which requires deploying resilience strategies of governments to prepare for long-term trends of higher temperatures and carefully plan emergency responses for such extreme heat events. The British Columbia province of Canada is one of the regions severely affected by extreme climatic events in 2021, which resulted in several deaths and put hundreds of thousands of people scrambling for relief. This study examines the public reactions to one of these extreme climatic events, the 2021 Pacific Northwest heatwave, in a non-emergency service request platform to uncover the types of municipal service needs during severe climatic disasters. City of Vancouver 311 system data is used to identify the impact of the heatwave on the frequency and types of service needs and examine the significance of the relationship between climatic conditions and the non-emergency service volumes.  
  Address Virginia Tech; Virginia Tech  
  Corporate Author Thesis  
  Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium  
  Track Analytical Modeling and Simulation Expedition Conference  
  Notes Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2408  
Share this record to Facebook
 

 
Author (up) Derya Ipek Eroglu; Duygu Pamukcu; Laura Szczyrba; Yang Zhang pdf  isbn
openurl 
  Title Analyzing and Contextualizing Social Vulnerability to Natural Disasters in Puerto Rico Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 389-395  
  Keywords Data Analytics, Hurricane María, Principal Component Analysis, Social Vulnerability Index.  
  Abstract As the third hurricane the U.S. experienced in 2017, Hurricane María generated impacts that resulted in both short term and long term suffering in Puerto Rico. In this study, we aim to quantify the vulnerability of Puerto Ricans by taking region and society specific characteristics of the island into account. To do this, we follow Cutter et al.'s social vulnerability calculation, which is an inductive approach that aims to represent a society based on its characteristics. We adapted the Social Vulnerability Index (SoVI) for Puerto Rico by using data obtained from the U.S. Census Bureau. We analyzed the newly calculated SoVI for Puerto Rico and compared it with the existing deductive approach developed by the Center for Disease Control (CDC). Our findings show that the new index is able to capture some characteristics that the existing vulnerability index is unable to do.  
  Address Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-37 ISBN 2411-3423 Medium  
  Track Data and resilience: opportunities and challenges Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes deryaipek@vt.edu Approved no  
  Call Number Serial 2238  
Share this record to Facebook
 

 
Author (up) Duygu Pamukcu; Christopher W. Zobel; Andrew Arnette pdf  isbn
openurl 
  Title Characterizing Social Community Structures in Emergency Shelter Planning Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 228-236  
  Keywords Evacuation Planning; Sheltering; Simulation; Social Network; Group Behavior  
  Abstract During emergencies, it is often necessary to evacuate vulnerable people to safer places to reduce loss of lives and cope with human suffering. Shelters are publically available places to evacuate, especially for people who do not have any other choices. This paper overviews emergency shelter planning in disaster mitigation and preparation and discusses the need for better responding to people who need to evacuate during emergencies. Recent evacuation studies pay attention to integrating social factors into evacuation modeling for better prediction of evacuation decisions. Our goal is to address the impact of social behavior on the sheltering choices of evacuees and to explore the potential contributions of including social network characteristics in the decision-making process of authorities. We present the shelter utilization problem in South Carolina during Hurricane Florence and discuss an agent-based modeling approach that considers social community structures in modeling the shelter choice behavior of socially connected individuals.  
  Address Virginia Tech; Virginia Tech; University of Wyoming  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-22 ISBN 2411-3408 Medium  
  Track Analytical Modeling and Simulation Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes duygu@vt.edu Approved no  
  Call Number Serial 2223  
Share this record to Facebook
 

 
Author (up) Duygu Pamukcu; Christopher Zobel; Yue Ge pdf  isbn
openurl 
  Title A Data Envelopment Analysis-based Approach for Managing Performance of Public Service Systems During a Disaster Type Conference Article
  Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022  
  Volume Issue Pages 144-153  
  Keywords Performance measurement; Efficiency; Data Envelopment Analysis; 311; Public Service  
  Abstract In addition to their normal task of supporting community participation, engagement, and improved information access, information technology-based public service systems are also essential for maintaining critical services and providing effective communication with citizens before, during, and after emergencies. This study focuses on the impacts of disaster events on the operational performance of such service systems and discusses opportunities for managing service efficiency by rearranging and reallocating resources during emergencies. To the best of our knowledge, this is the first attempt to provide a practical method for improving the relative efficiency of public service systems in such a context. We suggest a Data Envelopment Analysis (DEA) approach for quantifying the relative efficiencies associated with service requests from an input-output-based standpoint, and discuss the Orange County (Florida) 311 non-emergency service system, in the context of the COVID-19 pandemic, as an example of how such operational efficiency can be managed during a disruption.  
  Address Virginia Tech; Virginia Tech; University of Central Florida  
  Corporate Author Thesis  
  Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium  
  Track Analytical Modeling and Simulation Expedition Conference  
  Notes Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2405  
Share this record to Facebook
 

 
Author (up) Duygu Pamukcu; Christopher Zobel; Yue Ge pdf  openurl
  Title Analysis of Orange County, Florida 311 System Service Requests During the COVID-19 Pandemic Type Conference Article
  Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021  
  Volume Issue Pages 208-217  
  Keywords Disaster management, COVID-19, 311 system, Orlando  
  Abstract The Orlando metropolitan area in Florida, where Walt Disney World is located, is intimately familiar with impacts of natural disasters because of the yearly threat of hurricanes in the southeastern United States. One of the tools that has aided them in their efforts to monitor and manage such disasters is their 311 non-emergency call system, through which local residents can issue requests to the municipality for disaster-related information or other services. This paper provides a preliminary examination of the potential for the Orange County 311 system to provide actionable information to them in support of their efforts to manage a different type of disaster: the COVID-19 pandemic. The potential of the system to support the County in this context is illustrated through several preliminary analyses of the complete set of service requests that were registered in the first ten months of 2020.  
  Address Virginia Tech; Virginia Tech; University of Central Florida  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-61-5 ISBN Medium  
  Track Analytical Modeling and Simulation Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management  
  Notes duygu@vt.edu Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2326  
Share this record to Facebook
 

 
Author (up) Laura Szczyrba; Yang Zhang; Duygu Pamukcu; Derya Ipek Eroglu pdf  isbn
openurl 
  Title A Machine Learning Method to Quantify the Role of Vulnerability in Hurricane Damage Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 179-187  
  Keywords Vulnerability, Impact, Damage, Machine Learning, Hurricane María.  
  Abstract Accurate pre-disaster damage predictions and post-disaster damage assessments are challenging because of the complicated interrelationships between multiple damage drivers, including various natural hazards, as well as antecedent infrastructure quality and demographic characteristics. Ensemble decision trees, a family of machine learning algorithms, are well suited to quantify the role of social vulnerability in disaster impacts because they provide interpretable measures of variable importance for predictions. Our research explores the utility of an ensemble decision tree algorithm, Random Forest Regression, for quantifying the role of vulnerability with a case study of Hurricane Mar\'ia. The contributing predictive power of eight drivers of structural damage was calculated as the decrease in model mean squared error. A measure of social vulnerability was found to be the model's leading predictor of damage patterns. An additional algorithm, other methods of quantifying variable importance, and future work are discussed.  
  Address Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-17 ISBN 2411-3403 Medium  
  Track Analytical Modeling and Simulation Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes lszczyrba@vt.edu Approved no  
  Call Number Serial 2218  
Share this record to Facebook
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: