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

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

doi:10.3389/phrs.2024.1607057

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

Public Health Rev. 2024 Oct 10:45:1607057. doi: 10.3389/phrs.2024.1607057. eCollection 2024.

Authors

Ava A John-Baptiste^{1

2

3

4

5}, Marc Moulin^{3

6}, Zhe Li^{1

2

3

5

7}, Darren Hamilton⁶, Gabrielle Crichlow^{1

5

8}, Daniel Eisenkraft Klein^{1

9}, Feben W Alemu¹, Lina Ghattas¹, Kathryn McDonald¹⁰, Miqdad Asaria¹¹, Cameron Sharpe^{1

5}, Ekta Pandya¹, Nasheed Moqueet^{1

12}, David Champredon¹², Seyed M Moghadas¹³, Lisa A Cooper¹⁰, Andrew Pinto^{9

14

15

16

17}, Saverio Stranges^{1

18}, Margaret J Haworth-Brockman¹⁹, Alison Galvani²⁰, Shehzad Ali^{1

2

3

5

6

21

22

23}

Affiliations

¹ Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
² Department of Anesthesia and Perioperative Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
³ Centre for Medical Evidence, Decision Integrity and Clinical Impact, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
⁴ Lawson Health Research Institute, London, ON, Canada.
⁵ Schulich Interfaculty Program in Public Health, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
⁶ Health Sciences Library, London Health Sciences Centre, London, ON, Canada.
⁷ University of Ottawa Heart Institute, Ottawa, ON, Canada.
⁸ School of Health Studies, Faculty of Health Sciences, Western University, London, ON, Canada.
⁹ Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
¹⁰ Johns Hopkins Center for Health Equity, Johns Hopkins University, Baltimore, MD, United States.
¹¹ Department of Health Policy, London School of Economics and Political Science, London, United Kingdom.
¹² Public Health Agency of Canada (PHAC), Ottawa, ON, Canada.
¹³ Department of Mathematics and Statistics, Faculty of Science, York University, Toronto, ON, Canada.
¹⁴ Department of Family and Community Medicine, St. Michael's Hospital, Toronto, ON, Canada.
¹⁵ Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
¹⁶ Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada.
¹⁷ Institute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
¹⁸ Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy.
¹⁹ National Collaborating Centre for Infectious Diseases, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
²⁰ School of Public Health, Yale University, New Haven, CT, United States.
²¹ Department of Health Sciences, University of York, University of Manitoba, York, United Kingdom.
²² World Health Organization Collaborating Centre for Knowledge Translation and Health Technology Assessment in Health Equity, Ottawa, ON, Canada.
²³ Department of Psychology, Macquarie University, Sydney, NSW, Australia.

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.

Keywords: COVID-19; infectious disease models; model validity; public health; social determinants of health.

Copyright © 2024 John-Baptiste, Moulin, Li, Hamilton, Crichlow, Klein, Alemu, Ghattas, McDonald, Asaria, Sharpe, Pandya, Moqueet, Champredon, Moghadas, Cooper, Pinto, Stranges, Haworth-Brockman, Galvani and Ali.

Publication types

Systematic Review

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This project is funded by the Gordon and Betty Moore Foundation through Grant GBMF9634 to Johns Hopkins University to support the work of the Society for Medical Decision Making (SMDM) COVID-19 Decision Modeling Initiative (CDMI).