KIT | KIT-Bibliothek | Impressum | Datenschutz

Collaborative nowcasting of COVID-19 hospitalization incidences in Germany

Wolffram, Daniel 1; Abbott, Sam; an der Heiden, Matthias; Funk, Sebastian; Günther, Felix; Hailer, Davide 1; Heyder, Stefan; Hotz, Thomas; van de Kassteele, Jan; Küchenhoff, Helmut; Müller-Hansen, Sören; Syliqi, Diellë; Ullrich, Alexander; Weigert, Maximilian E.; Schienle, Melanie ORCID iD icon 1; Bracher, Johannes E. 1
1 Institut für Volkswirtschaftslehre (ECON), Karlsruher Institut für Technologie (KIT)

Abstract:

Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000161954
Veröffentlicht am 14.09.2023
Originalveröffentlichung
DOI: 10.1371/journal.pcbi.1011394
Scopus
Zitationen: 1
Web of Science
Zitationen: 1
Dimensions
Zitationen: 6
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Volkswirtschaftslehre (ECON)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 08.2023
Sprache Englisch
Identifikator ISSN: 1553-7358, 1553-734X
KITopen-ID: 1000161954
Erschienen in PLOS Computational Biology
Verlag Public Library of Science (PLoS)
Band 19
Heft 8
Seiten Art.-Nr.: e1011394
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 11.08.2023
Nachgewiesen in Web of Science
Dimensions
Scopus
Globale Ziele für nachhaltige Entwicklung Ziel 3 – Gesundheit und Wohlergehen
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page