Records |
Author |
Andrew Arnette; Christopher W. Zobel; Duygu Pamukcu |
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 |
Anmol Haque; Duygu Pamukcu; Ruixiang Xie; Mohsen Zaker Esteghamati; Margaret Cowell; Jennifer L. Irish |
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 |
Ayda Kianmehr; Duygu Pamukcu |
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 |
Derya Ipek Eroglu; Duygu Pamukcu; Laura Szczyrba; Yang Zhang |
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 |
Duygu Pamukcu; Christopher W. Zobel; Andrew Arnette |
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 |
Duygu Pamukcu; Christopher Zobel; Yue Ge |
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 |
Duygu Pamukcu; Christopher Zobel; Yue Ge |
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 |
Laura Szczyrba; Yang Zhang; Duygu Pamukcu; Derya Ipek Eroglu |
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 |