Do COVID-19 Infectious Disease Models Incorporate the Social Determinants of Health? A Systematic Review.

IF 3.5 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH PUBLIC HEALTH REVIEWS Pub Date : 2024-10-10 eCollection Date: 2024-01-01 DOI:10.3389/phrs.2024.1607057

Ava A John-Baptiste, Marc Moulin, Zhe Li, Darren Hamilton, Gabrielle Crichlow, Daniel Eisenkraft Klein, Feben W Alemu, Lina Ghattas, Kathryn McDonald, Miqdad Asaria, Cameron Sharpe, Ekta Pandya, Nasheed Moqueet, David Champredon, Seyed M Moghadas, Lisa A Cooper, Andrew Pinto, Saverio Stranges, Margaret J Haworth-Brockman, Alison Galvani, Shehzad Ali

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Abstract

Objectives: To identify COVID-19 infectious disease models that accounted for social determinants of health (SDH).

Methods: We searched MEDLINE, EMBASE, Cochrane Library, medRxiv, and the Web of Science from December 2019 to August 2020. We included mathematical modelling studies focused on humans investigating COVID-19 impact and including at least one SDH. We abstracted study characteristics (e.g., country, model type, social determinants of health) and appraised study quality using best practices guidelines.

Results: 83 studies were included. Most pertained to multiple countries (n = 15), the United States (n = 12), or China (n = 7). Most models were compartmental (n = 45) and agent-based (n = 7). Age was the most incorporated SDH (n = 74), followed by gender (n = 15), race/ethnicity (n = 7) and remote/rural location (n = 6). Most models reflected the dynamic nature of infectious disease spread (n = 51, 61%) but few reported on internal (n = 10, 12%) or external (n = 31, 37%) model validation.

Conclusion: Few models published early in the pandemic accounted for SDH other than age. Neglect of SDH in mathematical models of disease spread may result in foregone opportunities to understand differential impacts of the pandemic and to assess targeted interventions.

Systematic review registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020207706], PROSPERO, CRD42020207706.

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COVID-19 传染病模型是否纳入了健康的社会决定因素？系统回顾。

目的确定考虑了健康的社会决定因素（SDH）的 COVID-19 传染病模型：我们检索了 2019 年 12 月至 2020 年 8 月期间的 MEDLINE、EMBASE、Cochrane Library、medRxiv 和 Web of Science。我们纳入了以人类为研究对象、调查 COVID-19 影响并包含至少一种 SDH 的数学建模研究。我们摘录了研究特征（如国家、模型类型、健康的社会决定因素），并使用最佳实践指南评估了研究质量：结果：共纳入 83 项研究。大多数研究涉及多个国家（15 项）、美国（12 项）或中国（7 项）。大多数模型是分区模型（n = 45）和基于代理的模型（n = 7）。年龄是纳入最多的 SDH（n = 74），其次是性别（n = 15）、种族/民族（n = 7）和偏远/农村地区（n = 6）。大多数模型反映了传染病传播的动态性质（n = 51，61%），但很少有报告对模型进行内部（n = 10，12%）或外部（n = 31，37%）验证：结论：大流行早期发布的模型中，除年龄外，很少有模型考虑到 SDH。在疾病传播的数学模型中忽略 SDH 可能会导致失去了解大流行的不同影响和评估有针对性的干预措施的机会：[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020207706], prospero, crd42020207706.

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