Moghadas, SeyedLiwag, Maria Geneva Roselle Marino2023-03-282023-03-282022-10-052023-03-28http://hdl.handle.net/10315/40979In epidemiology, herd immunity refers to the population level of immunity required to prevent or extinguish a large disease outbreak. In models with homogeneously mixing assumptions and without demographic structures, the herd immunity level may be different from that in heterogeneous models. With the COVID-19 pandemic in Ontario as a case study, a comprehensive deterministic mathematical model of disease spread with age and contact pattern variations was developed to examine the required herd immunity for different variants and compare with theoretical values obtained using homogeneous assumptions. The effects of non-pharmaceutical (testing/isolation of silent infections) interventions and vaccination on epidemic progression and herd immunity were investigated. With the inclusion of age and contact pattern structures, the resulting herd immunity level required to end an epidemic under the assumptions of long-term protection (without re-infection) is lower than theoretical values, even for more transmissible variants. While waning immunity and re-infection results in an oscillation in herd immunity levels in the population, subsequent epidemic peaks are less amplified, suggesting that even with increased variant transmissibility, infections of any variant allow for population immunity to rise, leading to an endemic state.Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.Applied mathematicsEpidemiologyElectronic Thesis or Dissertation2023-03-28Mathematical modellingDisease modellingCOVID-19Population heterogeneityHerd immunity