Dismantling the Herd Immunity Threshold Orthodoxy: Heterogeneous Transmission Networks, Superspreading Dynamics, and the Recalibration of Population-Level Immunological Benchmarks in Post-Pandemic Epidemiology

Abstract

The classical herd immunity threshold (HIT) framework, rooted in homogeneous mixing assumptions derived from compartmental SIR models, has historically guided vaccination coverage targets across national immunization programs. Emerging epidemiological evidence from the post-COVID-19 era challenges the universal applicability of these deterministic benchmarks. This study synthesizes multi-country seroprevalence datasets, network-based transmission models, and individual-level contact matrices to interrogate whether fixed HIT values remain defensible under conditions of pronounced population heterogeneity. Employing a stratified meta-analytic framework across 27 national cohorts (2021–2024), we demonstrate that superspreading events and assortative social mixing systematically lower effective reproductive numbers below conventionally predicted thresholds. Our findings advocate for context-sensitive, dynamic immunological benchmarks that incorporate spatial clustering, age-structured susceptibility gradients, and waning immunity kinetics, with direct implications for adaptive vaccine policy design.