Sterl, S., Almalla, N., & Gerhold, L. (2023). Conceptualizing a Pandemic Early Warning System Using Various Data: An Integrative Approach. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 284–294). Omaha, USA: University of Nebraska at Omaha.
Abstract: Covid-19 demonstrated the vulnerability of various systems and showed, however, that digital tools and data can serve not only to stop infections but also to detect viruses before or immediately after a zoonosis has occurred, thus preventing a potential pandemic. Although several pandemic early warning systems (P-EWS) and German pandemic-related projects (G-PRP) exist, they often use a limited data range or rely on third-party data. Here, we present a concept of an integrative pandemic early warning system (IS-PAN) applied to Germany using various data such as health data (e.g., clinical/syndromic) or internet data (e.g., social media/apps). Based on a systematic literature research of P-EWS and G-PRP on scientific and public health platforms, we derived indicators that help to detect virus threats with a system consisting of modules monitored in parallel. By integrating various pre collected digital data, this approach can help to identify a potential health threat efficiently and effectively.
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Sterl, S., Billig, A., Taffo, F. W., & Gerhold, L. (2023). Visualizing the Psychosocial Situation in Crises and Disasters: Conceptualizing a Multi-Functional Crisis Information Platform (CIP-PS). In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 252–262). Omaha, USA: University of Nebraska at Omaha.
Abstract: Crises and disasters are becoming more frequent, long-lasting, complex, and interdependent. This can lead to negative psychosocial consequences in vulnerable population groups, increasing the need to (1) monitor psychosocial indicators and (2) make information on psychosocial topics available to decision-makers, the scientific community, and the public. In this WiPe paper, we present a way to systematically visualize, research, and document different types of psychosocial data in crises and disasters by developing a “Multi-Functional Crisis Information Platform for Psychosocial Situations”, called CIP-PS. The CIP-PS has three components, i.e., an information dashboard (CIP-DAB), a research platform (CIP-REP), and a documentation (CIP-DOC) component which together help visualize, research and document psychosocial topics, such as the psychosocial situation picture in Germany. The platform is a valuable tool for presenting relevant psychosocial information in the context of disaster public health. Its strength lies in an extensive connection between the three components related to healthcare informatics.
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Fiona Jennet McNeill, Diana Bental, Jeremy Bryans, Paolo Missier, & Jannetta Steyn. (2018). Informing decision makers: facilitating communication and trust for decision makers during crises. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1133–1135). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: This paper describes our approach to facilitating automated data sharing during a crisis management scenario. There are a number of reasons why this is difficult, of which we are addressing two of the main ones. Firstly, data in different organisations (and organisations) is mismatched in that different terminology, structure, specificity and data formats are used, so automated comprehension of data is problematic. Secondly, is that it is hard to assess the trustworthiness of data from other organisations. We have developed data-matching and provenance-based solutions to these problems individually. In this paper, we discuss how best these approaches can be integrated so that decision makers can quickly and automatically be presented with data to match, or approximately match, their data needs, together with the right information for them to understand the quality and meaning of this data, and introduce the CEM-DIT (Communication for Emergency Management through Data Integration and Trust) system.
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Efstratios Kontopoulos, Panagiotis Mitzias, Jürgen Moßgraber, Philipp Hertweck, Hylke van der Schaaf, Désirée Hilbring, et al. (2018). Ontology-based Representation of Crisis Management Procedures for Climate Events. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1064–1073). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: One of the most critical challenges faced by authorities during the management of a climate-related crisis is the overwhelming flow of heterogeneous information coming from humans and deployed sensors (e.g. cameras, temperature measurements, etc.), which has to be processed in order to filter meaningful items and provide crisis decision support. Towards addressing this challenge, ontologies can provide a semantically unified representation of the domain, along with superior capabilities in querying and information retrieval. Nevertheless, the recently proposed ontologies only cover subsets of the relevant concepts. This paper proposes a more “all-around” lightweight ontology for climate crisis management, which greatly facilitates decision support and merges several pertinent aspects: representation of a crisis, climate parameters that may cause climate crises, sensor analysis, crisis incidents and related impacts, first responder unit allocations. The ontology could constitute the backbone of the decision support systems for crisis management.
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Ivison C. Rubim, & Marcos R. S. Borges. (2017). The Resilience and Its Dimensions. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 457–463). Albi, France: Iscram.
Abstract: Resilience has become a concept extensively used by several areas of knowledge. However, there is no method, widely recognized capable of measuring resilient behavior. Therefore, this exploratory work aims to present a set of dimensions capable of delimiting metrics in order to measure a resilient attitude. For that, we analyzed some scientific papers considered relevant by the academic community. In this work we follow an analytical flow seeking to conceptualize resilience and situate it in the context of complex systems. This analysis allowed the discovery of some characteristics regarding resilience, fundamental for the proposition of the presented dimensions. Finally, we present a conceptual map that brings together the elicited dimensions.
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