2026-10-14T04:40:05Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33961297 2026-09-22T04:10:43Z category_7 category_21 category_24 category_272 category_46 category_734 category_811 category_64 category_132 category_135 portal_63 item_type_3 month_year_09_2026

Influenza A (H1N1) and SARS-CoV‑2 Transmission in Airplanes: Quanta Profiles and Infection Control Ao Li (15375) Hui-Ling Yen (85577) Nancy H. L. Leung (9230269) Julian W. Tang (7742660) Yuguo Li (628076) Medicine Biotechnology Evolutionary Biology Environmental Sciences not elsewhere classified Immunology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Cancer Infectious Diseases Computational Biology poses critical challenges results reveal super effectively reducing close close time equivalents 40 airplane outbreaks variable close standardizing close mitigating super 23 outbreaks range transmission public transit poorly characterized occupancy spaces new metric institutional settings including aircraft emerging variants driven variability confined spaces confined high commercial boeing ancestral strain 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. 2026-09-22T00:00:00Z Dataset Dataset 10.1021/acs.est.6c09696.s002 https://figshare.com/articles/dataset/Influenza_A_H1N1_and_SARS-CoV_2_Transmission_in_Airplanes_Quanta_Profiles_and_Infection_Control/33961297 CC BY-NC 4.0