Decoding Viral Transmission Dynamics in Structured Populations Using a Microfluidic Herd-Immunity-on-a-Chip Platform.

Understanding how population structure shapes viral transmission remains challenging because most in vitro models assume well-mixed conditions and lack spatial structure. We present a Herd-Immunity-on-a-Chip (HIC) platform-a 444-chamber microfluidic network that recreates structured populations-and apply it to human coronavirus 229E infecting MRC-5 fibroblasts. By varying initial inoculum (I0), susceptible density (S0), cell motility, and the fraction of non-susceptible cells (U0), we decode how seeding, density, immunity and movement reshape outbreak trajectories. Increasing S0 or I0 raised local contact rates, reduced effective intercellular spacing, and increased the reproduction number (R0), accelerating spread. In contrast, higher U0 suppressed transmission; with U0 ≥ 80% of the fixed uninfected population (S0 + U0), outbreaks collapsed (herd immunity). Independently, lowering S0 slowed early spread but did not, alone, prevent eventual transmission. We integrate the data with mathematical modelling of spatial, contact-structured transmission to quantify changes in R0 and apparent herd-immunity thresholds. HIC offers a generalizable, bench-top framework for outbreak forecasting and intervention testing.