按年龄和地区分列的英格兰COVID-19死亡人数

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY
Shaun R. Seaman, Pantelis Samartsidis, Meaghan Kall, Daniela De Angelis
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引用次数: 15

摘要

了解COVID-19每日死亡人数的轨迹对于决定如何应对大流行至关重要,但由于死亡发生和报告之间的延迟,估计这一轨迹变得复杂。在英国,延迟通常是几天,但也可能是几周。这给最近几天有多少人死亡造成了相当大的不确定性。在这里,我们使用贝叶斯模型估计了英国七个地区五个年龄层每天的死亡人数,该模型考虑了报告日效应和延迟分布的长期变化。我们展示了当延迟分布在多个地层中相同时,例如,在广泛的年龄范围内,该模型如何在计算上有效地拟合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Nowcasting COVID-19 deaths in England by age and region

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. 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.

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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
76
审稿时长
>12 weeks
期刊介绍: The Journal of the Royal Statistical Society, Series C (Applied Statistics) is a journal of international repute for statisticians both inside and outside the academic world. The journal is concerned with papers which deal with novel solutions to real life statistical problems by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to them. At their heart therefore the papers in the journal are motivated by examples and statistical data of all kinds. The subject-matter covers the whole range of inter-disciplinary fields, e.g. applications in agriculture, genetics, industry, medicine and the physical sciences, and papers on design issues (e.g. in relation to experiments, surveys or observational studies). A deep understanding of statistical methodology is not necessary to appreciate the content. Although papers describing developments in statistical computing driven by practical examples are within its scope, the journal is not concerned with simply numerical illustrations or simulation studies. The emphasis of Series C is on case-studies of statistical analyses in practice.
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