Work

Disaggregating Middle Eastern and North African Populations in Mortality Records to Better Understand COVID-19 Inequalities in Virginia

Year: 2025

Type: article

Abstract: Many ethno-racial minority populations had disproportionately high rates of COVID-19 infection and mortality during the initial years of the pandemic, but it is currently unclear whether Middle Eastern and North African populations in the USA experienced similar inequalities. This study disaggregates the MENA population in Virginia death records using a long short-term memory machine learning model that can probabilistically identify ethnically-unique names. The results suggest that MENA populations had higher overall excess mortality and a higher percentage of COVID-19 deaths among total deaths, when compared to the non-Hispanic White population of Virginia. The paper highlights the importance of disaggregating the MENA population in health inequalities research and offers a new method that improves upon previous name-based disaggregation methods.

Source: Journal of Racial and Ethnic Health Disparities

DOI: 10.1007/s40615-025-02589-1

Author: Elyas Bakhtiari

Institution: William & Mary

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDGs: Reduced inequalities, Good health and well-being

Open Access status: hybrid

Estimated APC paid: $5,190