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Nowcasting COVID‐19 deaths in England by age and region
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349735/ https://www.ncbi.nlm.nih.gov/pubmed/35942006 http://dx.doi.org/10.1111/rssc.12576 |
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author | Seaman, Shaun R. Samartsidis, Pantelis Kall, Meaghan De Angelis, Daniela |
author_facet | Seaman, Shaun R. Samartsidis, Pantelis Kall, Meaghan De Angelis, Daniela |
author_sort | Seaman, Shaun R. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9349735 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93497352022-08-04 Nowcasting COVID‐19 deaths in England by age and region Seaman, Shaun R. Samartsidis, Pantelis Kall, Meaghan De Angelis, Daniela J R Stat Soc Ser C Appl Stat Original Articles 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. John Wiley and Sons Inc. 2022-06-15 /pmc/articles/PMC9349735/ /pubmed/35942006 http://dx.doi.org/10.1111/rssc.12576 Text en © 2022 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Seaman, Shaun R. Samartsidis, Pantelis Kall, Meaghan De Angelis, Daniela Nowcasting COVID‐19 deaths in England by age and region |
title | Nowcasting COVID‐19 deaths in England by age and region |
title_full | Nowcasting COVID‐19 deaths in England by age and region |
title_fullStr | Nowcasting COVID‐19 deaths in England by age and region |
title_full_unstemmed | Nowcasting COVID‐19 deaths in England by age and region |
title_short | Nowcasting COVID‐19 deaths in England by age and region |
title_sort | nowcasting covid‐19 deaths in england by age and region |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9349735/ https://www.ncbi.nlm.nih.gov/pubmed/35942006 http://dx.doi.org/10.1111/rssc.12576 |
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