Joint spatial modelling of COVID-19 severity among seniors: A Bayesian shared component approach using health administrative data from Ontario, Canada

IF 3 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Annals of Epidemiology Pub Date : 2025-10-08 DOI:10.1016/j.annepidem.2025.10.004

Nushrat Nazia, Charmaine Dean

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引用次数: 0

Abstract

Purpose

Jointly monitoring adverse COVID-19 outcomes among seniors is critical for assessing outbreak severity. These outcomes are often influenced by socioeconomic and demographic conditions and may co-occur in space, indicating shared structural risks that inform targeted responses.

Methods

We analyzed severe COVID-19 outcomes among adults aged 65 + in Ontario (January 2020–March 2022) using data from the Ontario Health Data Platform supported by ICES. A Bayesian shared component model with Integrated Nested Laplace Approximation at the forward sortation area level included socioeconomic and demographic covariates.

Results

The shared component explained ∼75 % of the total modeled spatial variability. High risks clustered in southern Ontario, while lower risks occurred in central and northern regions. Material deprivation was positively associated with death (RR 1.12, 95 % CrI: 1.04–1.21) and multiple hospitalizations (RR 1.20, 95 % CrI: 1.13–1.29). Racialized/newcomer population concentration was positively associated with death (RR 1.25, 95 % CrI: 1.14–1.38) and with single hospitalizations (RR 1.18, 95 % CrI: 1.11–1.24). The percentage of seniors was inversely associated with hospitalization (RR 0.98, 95 % CrI: 0.96–0.99) but not death.

Conclusions

Findings highlight structural inequities in pandemic severity and suggest targeted, equity-oriented strategies in guiding pandemic preparedness and response.

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老年人COVID-19严重程度的联合空间建模：使用加拿大安大略省卫生行政数据的贝叶斯共享成分方法

目的：联合监测老年人COVID-19不良结局对评估疫情严重程度至关重要。这些结果往往受到社会经济和人口条件的影响，并可能在空间中同时发生，表明共同的结构性风险为有针对性的对策提供了信息。方法：我们使用由ICES支持的安大略省健康数据平台的数据，分析安大略省65岁以上成年人（2020年1月至2022年3月）的严重COVID-19结局。在前向分类区域水平上，采用集成嵌套拉普拉斯近似的贝叶斯共享分量模型包含社会经济和人口统计协变量。结果：共享分量解释了75%的空间变异性。高风险集中在安大略省南部，而风险较低的地区发生在中部和北部地区。物质剥夺与死亡（RR 1.12, 95% CrI: 1.04-1.21）和多次住院（RR 1.20, 95% CrI: 1.13-1.29）呈正相关。种族化/新移民人口集中与死亡呈正相关（RR 1.25, 95% CrI: 1.14-1.38），与单次住院呈正相关（RR 1.18, 95% CrI: 1.11-1.24）。老年人比例与住院率呈负相关（RR 0.98, 95% CrI: 0.96-0.99），但与死亡无关。结论：研究结果突出了大流行严重程度的结构性不平等，并建议在指导大流行防范和应对方面采取有针对性的、以公平为导向的战略。

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

Annals of Epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

7.40

自引率

1.80%

发文量

207

审稿时长

59 days

期刊介绍： The journal emphasizes the application of epidemiologic methods to issues that affect the distribution and determinants of human illness in diverse contexts. Its primary focus is on chronic and acute conditions of diverse etiologies and of major importance to clinical medicine, public health, and health care delivery.