A joint Bayesian spatiotemporal risk prediction model of COVID-19 incidence, IC admission, and death with application to Sweden.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2022-11-28 DOI:10.1007/s00168-022-01191-1

I Gede Nyoman Mindra Jaya, Henk Folmer, Johan Lundberg

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引用次数: 0

Abstract

The three closely related COVID-19 outcomes of incidence, intensive care (IC) admission and death, are commonly modelled separately leading to biased estimation of the parameters and relatively poor forecasts. This paper presents a joint spatiotemporal model of the three outcomes based on weekly data that is used for risk prediction and identification of hotspots. The paper applies a pure spatiotemporal model consisting of structured and unstructured spatial and temporal effects and their interaction capturing the effects of the unobserved covariates. The pure spatiotemporal model limits the data requirements to the three outcomes and the population at risk per spatiotemporal unit. The empirical study for the 21 Swedish regions for the period 1 January 2020-4 May 2021 confirms that the joint model predictions outperform the separate model predictions. The fifteen-week-ahead spatiotemporal forecasts (5 May-11 August 2021) show a significant decline in the relative risk of COVID-19 incidence, IC admission, death and number of hotspots.

Supplementary information: The online version contains supplementary material available at 10.1007/s00168-022-01191-1.

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COVID-19发病、入院和死亡的贝叶斯时空联合风险预测模型在瑞典的应用。

COVID-19 的三个密切相关的结果，即发病、重症监护（IC）入院和死亡，通常是单独建模的，导致参数估计有偏差，预测效果相对较差。本文提出了一个基于周数据的三种结果的联合时空模型，用于风险预测和热点识别。本文采用的纯时空模型由结构化和非结构化时空效应及其交互作用组成，捕捉了未观测协变量的影响。纯时空模型将数据要求限制在三个结果和每个时空单位的风险人口。对瑞典 21 个地区 2020 年 1 月 1 日至 2021 年 5 月 4 日期间的实证研究证实，联合模型的预测结果优于单独模型的预测结果。提前15周的时空预测（2021年5月5日至8月11日）显示，COVID-19发病率、IC入院率、死亡人数和热点数量的相对风险显著下降：在线版本包含补充材料，可查阅 10.1007/s00168-022-01191-1。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.