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dc.contributor.authorSeaman, Shaun R
dc.contributor.authorSamartsidis, Pantelis
dc.contributor.authorKall, Meaghan
dc.contributor.authorDe Angelis, Daniela
dc.date.accessioned2022-06-16T08:00:53Z
dc.date.available2022-06-16T08:00:53Z
dc.date.issued2022-06-15
dc.date.submitted2020-11-30
dc.identifier.issn0035-9254
dc.identifier.otherrssc12576
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/338148
dc.description.abstractAbstract: Understanding the trajectory of the daily number of COVID‐19 deaths is essential to decisions on how to respond to the pandemic, but estimating this trajectory is complicated by the delay between deaths occurring and being reported. In England the delay is typically several days, but it can be weeks. This causes considerable uncertainty about how many deaths occurred in recent days. Here we estimate the deaths per day in five age strata within seven English regions, using a Bayesian model that accounts for reporting‐day effects and longer‐term changes in the delay distribution. We show how the model can be computationally efficiently fitted when the delay distribution is the same in multiple strata, for example, over a wide range of ages.
dc.languageen
dc.publisherWiley
dc.subjectORIGINAL ARTICLE
dc.subjectORIGINAL ARTICLES
dc.subjectepidemic monitoring
dc.subjectgeneralised Dirichlet
dc.subjectreporting delay
dc.subjectright‐truncation
dc.titleNowcasting COVID‐19 deaths in England by age and region
dc.typeArticle
dc.date.updated2022-06-16T08:00:53Z
prism.publicationNameJournal of the Royal Statistical Society: Series C (Applied Statistics)
dc.identifier.doi10.17863/CAM.85557
dcterms.dateAccepted2022-05-11
rioxxterms.versionofrecord10.1111/rssc.12576
rioxxterms.versionAO
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.identifier.eissn1467-9876
cam.issuedOnline2022-06-15


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