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1000 Titel
  • Digitale Epidemiologie
1000 Titelzusatz
  • Digital epidemiology
1000 Autor/in
  1. Brockmann, Dirk |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-01-23
1000 Erschienen in
1000 Quellenangabe
  • 63(2):166-175
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s00103-019-03080-z |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Digital epidemiology is a new and rapidly growing field. The technological revolution we have been witnessing during the last decade, the global rise of the Internet, the emergence of social media and social networks that connect individuals worldwide for information exchange and social interactions, and the almost complete social penetration of mobile devices such as smartphones provide access to data on individual behavior with unprecedented resolution and precision. In digital epidemiology, this type of high-resolution behavioral data is analyzed to advance our understanding of, for example, infectious disease dynamics and improve our abilities to forecast epidemic outbreaks and related phenomena.This article provides an overview on the topic. Different aspects of digital epidemiology are alluded to. Based on examples, I will explain how epidemiological data is integrated on new comprehensive and interactive websites, how the analysis of interactions and activities on social media platforms can yield answers to epidemiological questions, and finally how individual-based data collected by smartphones or wearable sensors in natural experiments can be used to reconstruct contact and physical proximity networks the knowledge of which substantially improves the predictive power of computational models for transmissible infectious diseases.The challenges posed in terms of privacy protection and data security will be discussed. Concepts and solutions will be explained that may help to improve public health by leveraging the new data while at the same time protecting the individual's data sovereignty and personal dignity.
1000 Sacherschließung
lokal Big data
lokal Communicable Diseases [MeSH]
lokal Machine learning
lokal Leitthema
lokal Humans [MeSH]
lokal Maschinelles Lernen
lokal Artificial intelligence
lokal Computational Epidemiology
lokal Künstliche Intelligenz
lokal Complex networks
lokal Computational epidemiology
lokal Komplexe Netzwerke
lokal Public Health [MeSH]
lokal Social Media [MeSH]
lokal Big Data
lokal Germany [MeSH]
lokal Data Collection [MeSH]
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/QnJvY2ttYW5uLCBEaXJr
1000 Hinweis
  • DeepGreen-ID: b6419942ad4346d185d713ce77b7dfc8 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Dateien
  1. Digitale Epidemiologie
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6443094.rdf
1000 Erstellt am 2023-04-26T17:08:54.957+0200
1000 Erstellt von 322
1000 beschreibt frl:6443094
1000 Zuletzt bearbeitet Thu Oct 19 13:59:19 CEST 2023
1000 Objekt bearb. Thu Oct 19 13:59:19 CEST 2023
1000 Vgl. frl:6443094
1000 Oai Id
  1. oai:frl.publisso.de:frl:6443094 |
1000 Sichtbarkeit Metadaten public
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