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Modeling the impact of racial and ethnic disparities on COVID-19 epidemic dynamics.
Ma, Kevin C; Menkir, Tigist F; Kissler, Stephen; Grad, Yonatan H; Lipsitch, Marc.
  • Ma KC; Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States.
  • Menkir TF; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, United States.
  • Kissler S; Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States.
  • Grad YH; Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States.
  • Lipsitch M; Division of Infectious Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, United States.
Elife ; 102021 05 18.
Article in English | MEDLINE | ID: covidwho-1232679
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ABSTRACT

Background:

The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown.

Methods:

Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk change across groups.

Results:

A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites.

Conclusions:

Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection.

Funding:

K.C.M. was supported by National Science Foundation GRFP grant DGE1745303. Y.H.G. and M.L. were funded by the Morris-Singer Foundation. M.L. was supported by SeroNet cooperative agreement U01 CA261277.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / Health Status Disparities / Pandemics / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Country/Region as subject: North America Language: English Year: 2021 Document Type: Article Affiliation country: ELife.66601

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / Health Status Disparities / Pandemics / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Country/Region as subject: North America Language: English Year: 2021 Document Type: Article Affiliation country: ELife.66601