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Author |
Zeno Franco; Syed Ahmed; Craig E. Kuziemsky; Paul A. Biedrzycki; Anne Kissack |
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Title |
Using social network analysis to explore issues of latency, connectivity, interoperability & sustainability in community disaster response |
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Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Pages |
896-900 |
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Keywords |
Data fusion; Disasters; Information systems; Mergers and acquisitions; Social networking (online); Boundary spanning; Community engagement; Community resources; Community vulnerability; Crisis response; Disaster recovery; Disaster response; Social network analysis approaches; Emergency services |
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Abstract |
Community-based disaster response is gaining attention in the United States because of major problems with domestic disaster recovery over the last decade. A social network analysis approach is used to illustrate how community-academic partnerships offer one way to leverage information about existing, mediated relationships with the community through trusted actors. These partnerships offer a platform that can be used to provide entré into communities that are often closed to outsiders, while also allowing greater access to community embedded physical assets and human resources, thus facilitated more culturally appropriate crisis response. Using existing, publically available information about funded community-academic partnerships in Wisconsin, USA, we show how social network analysis of these meta-organizations may provide critical information about both community vulnerabilities in disaster and assist in rapidly identifying these community resources in the aftermath of a crisis event that may provide utility for boundary spanning crisis information systems. |
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Address |
Medical College of Wisconsin, United States; U. Ottawa, Canada; City of Milwaukee Public Health Department, United Kingdom |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
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Track |
Social Media |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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no |
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Call Number |
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Serial |
504 |
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Author |
Savannah Thais; Shaine Leibowitz; Allie Saizan; Ashay Singh |
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Title |
Understanding Historical, Socio-Economic, and Policy Contributions to COVID-19 Health Inequities |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
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Issue |
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Pages |
481-494 |
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Keywords |
Public Health; COVID-19; Economic Impact; Mobile Health; Unsupervised Learning; Longitudinal Analysis; Community Vulnerability Index; Proxy Outcomes; Health Policy; Social Determinants of Health; Equity |
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Abstract |
The COVID-19 pandemic has generated unprecedented, devastating impacts across the United States. However, some communities have disproportionately endured adverse health outcomes and socioeconomic injuries. Ascertaining the factors driving these inequities is crucial to determining how policy could mitigate the impacts of future public health crises. We have established research-driven metrics, aggregated as the Community Vulnerability Index (CVI), that quantify vulnerability to public health and economic impacts of COVID-19. We performed two analyses to better understand similarities between communities in terms of the vulnerabilities represented by the metrics. We performed an unsupervised k-means clustering analysis to understand whether communities can be grouped together based on their levels of negative social and health indicators. Our goal for this analysis is to determine whether attributes of the constructed clusters reveal areas of opportunity for potential policy impacts and future disaster response efforts. We also analyzed similarities between communities across time using time-sensitive clustering analysis to discover whether historical community vulnerabilities were persistent in the years preceding the pandemic and to better understand the historical factors associated with disparate COVID-19 impacts. In particular, we highlight where communities should invest based on their historical health and socioeconomic patterns and related COVID impacts. Through extensive interpretation of our findings, we uncover how health policy can advance equity and improve community resilience. |
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Address |
Princeton University; Community Insight and Impact; Community Insight and Impact; Community Insight and Impact |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
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Track |
Data and Resilience: Opportunities and Challenges |
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Conference |
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Notes |
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no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2434 |
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Author |
Sofia Kostakonti; Ramona Velea; Vassilis Papataxiarhis; Daniele Del Bianco; Uberto Delprato; Stathes Hadjiefthymiades |
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Title |
A semantic approach for modeling vulnerability of communities |
Type |
Conference Article |
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Year |
2021 |
Publication |
ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2021 |
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Volume |
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Issue |
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Pages |
305-318 |
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Keywords |
Community vulnerability, semantic modeling, community resilience, knowledge representation and reasoning |
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Abstract |
In this paper, we propose the use of semantic technologies for the representation of concepts and relationships required for the modeling of vulnerability data for local communities. First, we discuss the concepts of vulnerability and resilience and we try to identify the relationship between the two. We provide some background knowledge and we present basic characteristics of the two concepts. Next, we discuss the motivation behind the use of semantic technologies, and we show how the proposed framework can address existing challenges in terms of vulnerability assessment. The core part of this paper focuses on the semantic representation of community vulnerability aspects. We give an overview of the layered semantic framework consisting of interconnected ontological models and we provide a set of use-cases where the use of semantic-based modeling and query answering can prove beneficial in terms of assessing vulnerability. |
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Address |
National and Kapodistrian University of Athens; Institute of International Sociology of Gorizia; National and Kapodistrian University of Athens; Institute of International Sociology of Gorizia; Intelligence for Environment and Security; National and Kapod |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Edition |
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ISSN |
978-1-949373-61-5 |
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Track |
Data and Resilience: Opportunities and Challenges |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
sofkost@di.uoa.gr |
Approved |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2335 |
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