Air purifier and ventilation fan effects on SARS-CoV-2 airborne transmission in vehicle: Infection risk analysis with zonal and CFD models

Predictive epidemiological models help design effective strategies against airborne disease transmission. To this end, this study compares zonal and computational fluid dynamics (CFD) models for simulating airflow, aerosol dispersion, and infection risk in a private vehicle. Three scenarios were assessed: no mitigation, ventilation fan only, and air purifier only, with airflow rates set to 8.33 × 10⁻³ m³ /s (500 L/min or 5 ACH), consistent with EPA and CDC recommendations. Both models captured similar qualitative trends, but significant quantitative discrepancies arose. In the no-mitigation case, CFD predicted infection risks up to 100 × higher than the zonal model due to better resolution of stagnation and turbulent dispersion. With the ventilation fan active, the zonal model predicted higher risks for downstream passengers, while CFD revealed more realistic dilution via recirculation and directional flow. CFD results showed that ventilation reduced average infection risk by 81.99 %, and the purifier by 76.88 %, relative to no mitigation. For rear passengers, the purifier achieved a greater reduction (89.98 %) than ventilation (73.67 %), highlighting spatial trade-offs between flow-driven and localized interventions. Taken together, the zonal model offers computational efficiency and reliable trend prediction, particularly in purifier-dominated or well-mixed environments. CFD, with its ability to resolve flow direction and turbulence, excels in capturing spatial variability. Together, these models form a complementary toolkit for infection risk assessment, adaptable to both rapid evaluations and detailed flow-sensitive analyses.