Bayesian nowcasting during the STEC O104:H4 outbreak in Germany, 2011

DOI10.1111/biom.12194zbMath1393.62067OpenAlexW1924589045WikidataQ33415924 ScholiaQ33415924MaRDI QIDQ3465382

Matthias an der Heiden, Michael Höhle

Publication date: 21 January 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-113230

zbMATH Keywords

predictiontruncationinfectious disease epidemiologyreporting delayreal-time surveillance

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (4)

Modeling the occurrence of events subject to a reporting delay via an EM algorithm ⋮ Nowcasting fatal COVID‐19 infections on a regional level in Germany ⋮ Nowcasting the COVID‐19 pandemic in Bavaria ⋮ Bayesian outbreak detection in the presence of reporting delays

Uses Software

• R
• Surveillance
• gamair

Cites Work

• Unnamed Item
• Unnamed Item
• Surveillance: An R package for the monitoring of infectious diseases
• Generalized Dirichlet distribution in Bayesian analysis
• Nonparametric analysis of truncated survival data, with application to AIDS
• Regression
• Modeling Reporting Delays and Reporting Corrections in Cancer Registry Data
• Predictive Model Assessment for Count Data

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