|
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.
|
|
|
Andrea H. Tapia, Nicolas LaLone, Elizabeth MacDonald, Reid Priedhorsky, & Hall Hall. (2014). Crowdsourcing rare events: Using curiosity to draw participants into science and early warning systems. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 135–144). University Park, PA: The Pennsylvania State University.
Abstract: This research presents a centralized boundary object website and mobile app focused on allowing participants to participate in developing an early warning system through space weather and the beauty of the aurora borealis. Because of the beauty and majesty of auroral activity, people will seek information about when and where these unpredictable events occur. This activity, commonly referred to as nowcasting, can be combined with scientific data collected from observatories and satellites and serve as an early warning system with potentially far greater accuracy and timeliness than the current state of the art. We believe that long-term engagement with a citizen science tool will help bridge the many social worlds surrounding the aurora borealis and lead to the development of an early warning system that may correlate the visibility of the northern lights to violent space weather. We hope this will lead to other real time crowdsourced early warning systems in the future.
|
|
|
Tina Comes, Brice Mayag, & Elsa Negre. (2015). Beyond Early: Decision Support for Improved Typhoon Warning Systems. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Warnings can help prevent damage and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks, or issue early warnings. In this paper we analyze the different systems in the light of the initial decisions that need to be made in the response to sudden onset disasters. We outline challenges of current practices and methods, and provide an agenda for future research.
To illustrate our approach, we present a case study of Typhoon Haiyan. Although meteorological services had issued warnings; relief goods were prepositioned; and responders predeployed, the delivery of aid was delayed in some of the worst hit regions. We argue for an integrated consideration of preparedness and response to provide adequate thresholds for early warning systems that focus on decision-makers needs.
|
|
|
Ana Rosa Trancoso, José Delgado Domingos, Maria João Telhado, & João Corte-Real. (2011). Early warning system for meteorological risk in Lisbon municipality: Description and quality evaluation. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The current work describes and evaluates an early warning system for meteorological risk in Lisbon that has been functioning in SMPC since February 2008. The system aims to integrate multiple sources of information and facilitate cross checking observations, forecasts and warnings, allowing for an efficient and timely evaluation of the alert level to issue. Currently, it comprises hourly weather and tide level forecasts and automated warnings for Lisbon city, given by MM5 and WRF models running at IST. Results show MM5 performing better than WRF except for warm weather. The overall skill of the warning system is 40% with some false alarm ratios, mainly for forecasts with more than 3 days in advance. This is a reasonable characteristic for early warning since a potentially problematic situation can be anticipated and checked avoiding unnecessary economic expenditures if the warnings do not persist.
|
|
|
Simone Wurster, & Ulrich Meissen. (2014). Towards an economic assessment approach for early warning systems: Improving cost-avoidance calculations with regard to private households. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 439–443). University Park, PA: The Pennsylvania State University.
Abstract: In recent years, Early Warning Systems (EWS) have proven their value by saving many lives. However, most in-vestments into EWS were motivated directly by experienced disaster events and rarely pro-actively by possible up-coming threats. In order to change that we think that besides ethical and humanitarian reasons also the positive economic effects should be analyzed. EWS also help to protect property, but their contribution is not as obvious in that field due to the lack of quantitative models. This paper presents a disaster-independent formula that shows the benefits of EWS. Additional value to existing approaches is based on its advanced focus on behavioral aspects and the benefits of EWS in comparison to warnings issued via social media. We consider this work as an important contribution for future investments into warning technologies. However, yet this model just provides a theoretical framework for necessary empirical studies that are subject of further research.
|
|
|
Andrea Zielinski, & Ulrich Bügel. (2012). Multilingual analysis of twitter news in support of mass emergency events. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Social media are increasingly becoming a source for event-based early warning systems in the sense that they can help to detect natural disasters and support crisis management during or after disasters. In this work-in-progress paper we study the problems of analyzing multilingual twitter feeds for emergency events. The present work focuses on English as “lingua franca” and on under-resourced Mediterranean languages in endangered zones, particularly Turkey, Greece, and Romania Generally, as local civil protection authorities and the population are likely to respond in their native language. We investigated ten earthquake events and defined four language-specific classifiers that can be used to detect earthquakes by filtering out irrelevant messages that do not relate to the event. The final goal is to extend this work to more Mediterranean languages and to classify and extract relevant information from tweets, translating the main keywords into English. Preliminary results indicate that such a filter has the potential to confirm forecast parameters of tsunami affecting coastal areas where no tide gauges exist and could be integrated into seismographic sensor networks. © 2012 ISCRAM.
|
|