Baquero, Carlos ; Casari, Paolo ; Fernandez Anta, Antonio ; García-García, Amanda ; Frey, Davide ; Garcia-Agundez, Augusto ; Georgiou, Chryssis ; Girault, Benjamin ; Ortega, Antonio ; Goessens, Mathieu ; Hernández-Roig, Harold A. ; Nicolaou, Nicolas ; Stavrakis, Efstathios ; Ojo, Oluwasegun ; Roberts, Julian C. ; Sanchez, Ignacio (2024)
The CoronaSurveys System for COVID-19 Incidence Data Collection and Processing.
In: Frontiers in Computer Science, 2021, 3
doi: 10.26083/tuprints-00022228
Artikel, Zweitveröffentlichung, Verlagsversion
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Kurzbeschreibung (Abstract)
CoronaSurveys is an ongoing interdisciplinary project developing a system to infer the incidence of COVID-19 around the world using anonymous open surveys. The surveys have been translated into 60 languages and are continuously collecting participant responses from any country in the world. The responses collected are pre-processed, organized, and stored in a version-controlled repository, which is publicly available to the scientific community. In addition, the CoronaSurveys team has devised several estimates computed on the basis of survey responses and other data, and makes them available on the project’s website in the form of tables, as well as interactive plots and maps. In this paper, we describe the computational system developed for the CoronaSurveys project. The system includes multiple components and processes, including the web survey, the mobile apps, the cleaning and aggregation process of the survey responses, the process of storage and publication of the data, the processing of the data and the computation of estimates, and the visualization of the results. In this paper we describe the system architecture and the major challenges we faced in designing and deploying it.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Baquero, Carlos ; Casari, Paolo ; Fernandez Anta, Antonio ; García-García, Amanda ; Frey, Davide ; Garcia-Agundez, Augusto ; Georgiou, Chryssis ; Girault, Benjamin ; Ortega, Antonio ; Goessens, Mathieu ; Hernández-Roig, Harold A. ; Nicolaou, Nicolas ; Stavrakis, Efstathios ; Ojo, Oluwasegun ; Roberts, Julian C. ; Sanchez, Ignacio |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | The CoronaSurveys System for COVID-19 Incidence Data Collection and Processing |
| Sprache: | Englisch |
| Publikationsjahr: | 19 Januar 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2021 |
| Ort der Erstveröffentlichung: | Lausanne |
| Verlag: | Frontiers Media S.A. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Frontiers in Computer Science |
| Jahrgang/Volume einer Zeitschrift: | 3 |
| Kollation: | 10 Seiten |
| DOI: | 10.26083/tuprints-00022228 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/22228 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| Kurzbeschreibung (Abstract): | CoronaSurveys is an ongoing interdisciplinary project developing a system to infer the incidence of COVID-19 around the world using anonymous open surveys. The surveys have been translated into 60 languages and are continuously collecting participant responses from any country in the world. The responses collected are pre-processed, organized, and stored in a version-controlled repository, which is publicly available to the scientific community. In addition, the CoronaSurveys team has devised several estimates computed on the basis of survey responses and other data, and makes them available on the project’s website in the form of tables, as well as interactive plots and maps. In this paper, we describe the computational system developed for the CoronaSurveys project. The system includes multiple components and processes, including the web survey, the mobile apps, the cleaning and aggregation process of the survey responses, the process of storage and publication of the data, the processing of the data and the computation of estimates, and the visualization of the results. In this paper we describe the system architecture and the major challenges we faced in designing and deploying it. |
| Freie Schlagworte: | COVID-19, monitoring, survey, indirect reporting, visualization, network scale-up method, mobile app |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-222286 |
| Zusätzliche Informationen: | This article is part of the Research Topic Compelling COVID-19 Graphical Simulations This article was submitted to Human-Media Interaction, a section of the journal Frontiers in Computer Science |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik 600 Technik, Medizin, angewandte Wissenschaften > 621.3 Elektrotechnik, Elektronik |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Multimedia Kommunikation |
| Hinterlegungsdatum: | 19 Jan 2024 14:13 |
| Letzte Änderung: | 12 Mär 2024 09:59 |
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| Suche nach Titel in: | TUfind oder in Google |
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