Airborne transmission of influenza A(H1N1)pdm09 and SARS-CoV-2 (ancestral strain) poses critical challenges in confined high-occupancy spaces, including aircraft, public transit, and institutional settings. Population-level quanta generation rate profiles, quantifying infectious particle emissions, are vital for assessing airborne infection risk but are poorly characterized. Short-range transmission complicates risk assessment due to variable close-contact scenarios. We estimated these profiles from 40 airplane outbreaks (14 influenza A(H1N1)pdm09, 26 SARS-CoV-2) using a novel heterogeneity matching method and an integrated Wells–Riley model combining short- and long-range transmission, calibrated via Monte Carlo simulations. Results reveal super-emitter-driven variability. A new metric, close time equivalents for standardizing close-contact exposure, was calculated for 23 outbreaks (6 influenza A(H1N1)pdm09, 17 SARS-CoV-2). Outbreak-derived quanta rates align with viral-load-based estimates, though the latter show greater variability. The population-level ventilation distribution compiled from commercial Boeing and Airbus cabin studies supports the robustness of the estimates. Impractical clean air equivalents for mitigating super-emitter transmission necessitate mask-wearing, effectively reducing close-contact and long-range transmission. These findings inform public health strategies for confined spaces and emerging variants.
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