Viral Respiratory Epidemic Modeling of Societal Segregation Based on Vaccination Status

Abstract

Background: Societal segregation of unvaccinated people from public spaces has been a novel and controversial coronavirus disease 2019 (COVID-19)-era public health practice in many countries. Models exploring potential consequences of vaccination-status-based segregation have not considered how segregation influences the contact frequencies in the segregated groups. We systematically investigate implementing effects of segregation on population-specific contact frequencies and show this critically determines the predicted epidemiological outcomes, focusing on the attack rates in the vaccinated and unvaccinated populations and the share of infections among vaccinated people that were due to contacts with infectious unvaccinated people. Methods: We describe a susceptible-infectious-recovered (SIR) two-population model for vaccinated and unvaccinated groups of individuals that transmit an infectious disease by person-to-person contact. The degree of segregation of the two groups, ranging from zero to complete segregation, is implemented using the like-to-like mixing approach developed for sexually transmitted diseases, adapted for presumed severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) transmission. We allow the contact frequencies for individuals in the two groups to be different and depend, with variable strength, on the degree of segregation. Results: Segregation can either increase or decrease the attack rate among the vaccinated, depending on the type of segregation (isolating or compounding), and the contagiousness of the disease. For diseases with low contagiousness, segregation can cause an attack rate in the vaccinated, which does not occur without segregation. Interpretation: There is no predicted blanket epidemiological advantage to segregation, either for the vaccinated or the unvaccinated. Negative epidemiological consequences can occur for both groups.