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

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• The COVID-19 pandemic highlighted the importance of social determinants of health (SDH) in disease spread and impact.
• Mathematical models are crucial tools for understanding infectious disease dynamics and informing public health interventions.

Purpose of the Study:

• To systematically identify and analyze mathematical models of COVID-19 that incorporated social determinants of health (SDH).

Main Methods:

• A comprehensive literature search was conducted across multiple databases (MEDLINE, EMBASE, Cochrane Library, medRxiv, Web of Science) from December 2019 to August 2020.
• Included studies were mathematical modeling research on COVID-19 in humans that incorporated at least one SDH.
• Data abstracted included country, model type, SDH, and study quality was appraised.

Main Results:

• Eighty-three studies were included, with most focusing on multiple countries, the United States, or China.
• Compartmental and agent-based models were most common.
• Age was the most frequently included SDH, followed by gender, race/ethnicity, and location; few models incorporated other SDH.
• While most models captured disease dynamics, external validation was reported in less than 40% of studies.

Conclusions:

• Mathematical models developed early in the COVID-19 pandemic predominantly excluded social determinants of health (SDH) except for age.
• The limited inclusion of SDH in these models represents a missed opportunity to understand differential pandemic impacts and to evaluate targeted public health strategies.