Max Planck Institute for Dynamics and Self-Organization (MPIDS), Göttingen, Niedersachsen, Germany.
Institute for Dynamics of Complex Systems, University of Göttingen, Göttingen, Niedersachsen, Germany.
PLoS One. 2021 Apr 8;16(4):e0248004. doi: 10.1371/journal.pone.0248004. eCollection 2021.
In the case of airborne diseases, pathogen copies are transmitted by droplets of respiratory tract fluid that are exhaled by the infectious that stay suspended in the air for some time and, after partial or full drying, inhaled as aerosols by the susceptible. The risk of infection in indoor environments is typically modelled using the Wells-Riley model or a Wells-Riley-like formulation, usually assuming the pathogen dose follows a Poisson distribution (mono-pathogen assumption). Aerosols that hold more than one pathogen copy, i.e. poly-pathogen aerosols, break this assumption even if the aerosol dose itself follows a Poisson distribution. For the largest aerosols where the number of pathogen in each aerosol can sometimes be several hundred or several thousand, the effect is non-negligible, especially in diseases where the risk of infection per pathogen is high. Here we report on a generalization of the Wells-Riley model and dose-response models for poly-pathogen aerosols by separately modeling each number of pathogen copies per aerosol, while the aerosol dose itself follows a Poisson distribution. This results in a model for computational risk assessment suitable for mono-/poly-pathogen aerosols. We show that the mono-pathogen assumption significantly overestimates the risk of infection for high pathogen concentrations in the respiratory tract fluid. The model also includes the aerosol removal due to filtering by the individuals which becomes significant for poorly ventilated environments with a high density of individuals, and systematically includes the effects of facemasks in the infectious aerosol source and sink terms and dose calculations.
在空气传播疾病的情况下，病原体通过传染性呼吸道液滴传播，这些液滴由感染者呼出，在空气中停留一段时间，然后在部分或完全干燥后，被易感者作为气溶胶吸入。室内环境中的感染风险通常使用 Wells-Riley 模型或类似的 Wells-Riley 公式进行建模，通常假设病原体剂量遵循泊松分布（单病原体假设）。含有多个病原体副本的气溶胶，即多病原体气溶胶，即使气溶胶剂量本身遵循泊松分布，也会打破这一假设。对于最大的气溶胶，每个气溶胶中的病原体数量有时可能有数百或数千个，这种影响不可忽视，尤其是在感染风险每病原体都很高的疾病中。在这里，我们通过分别对每个气溶胶中的每个病原体副本进行建模，同时假设气溶胶剂量本身遵循泊松分布，对多病原体气溶胶的 Wells-Riley 模型和剂量反应模型进行了推广。这导致了一种适合单/多病原体气溶胶的计算风险评估模型。我们表明，单病原体假设会大大高估呼吸道液中高病原体浓度下的感染风险。该模型还包括由于个体过滤而导致的气溶胶去除，对于通风不良且个体密度高的环境，这会变得非常重要，并且系统地将口罩的影响纳入传染性气溶胶源和汇项以及剂量计算中。
