Viral loads of different-sized droplets are fundamental for accurately assessing transmission risks of respiratory infectious diseases in indoor environments. However, current sampling techniques lack experimental data on exhaled droplets larger than 10 μm, posing a significant challenge in identifying the dominant transmission routes and preparing for the potential emergence of ‘Disease X’. This study developed a novel sampler based on the aerodynamic characteristics of respiratory droplets, including gravitational deposition and inertial impaction, to characterize viral loads in full-size-range respiratory droplets. The sampler components were designed and optimized through the computational fluid dynamics (CFD) simulations, and their performance was evaluated using inert particle aerosols, demonstrating effective collection of respiratory droplets across five size ranges: 1–2.5 μm, 2.5–5 μm, 5–10 μm, 10–50 μm, and >50 μm. The sampler achieved over 84% collection efficiency for droplets larger than 50 μm, with minimal loss (<15%) for droplets smaller than 10 μm, and consistent performance (fluctuations <15%) across various respiratory conditions. In clinical validation, SARS-CoV-2 RNA was detected in respiratory droplets from 4 out of 5 COVID-19 patients, ranging from nondetectable to 9.11 (>50 μm), 8.17 (10–50 μm), 4.95 (5–10 μm) and 5.91 (1–5 μm) log10 RNA copies per 15-min sampling, respectively. These findings offer a systematic quantification of SARS-CoV-2 viral distribution at the source, across the full-size-range of respiratory droplets, providing previously lacking data. This novel sampler enables comprehensive source characterization and supports effective non-pharmaceutical intervention strategies for infection control.
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