An improved numerical model for epidemic transmission and infection risks assessment in indoor environment.
An improved numerical model for epidemic transmission and infection risks assessment in indoor environment.
复制标题
室内环境中流行病传播和感染风险评估的改进数值模型
DOI:
10.1016/j.jaerosci.2021.105943
复制
发表时间:
2022-05
影响因子:
4.5
通讯作者:
Tu J
中科院分区:
文献类型:
--
作者:
Shang Y;Dong J;Tian L;He F;Tu J
Social distance will remain the key measure to contain COVID-19 before the global widespread vaccination coverage expected in 2024. Containing the virus outbreak in the office is prioritised to relieve socio-economic burdens caused by COVID-19 and potential pandemics in the future. However, “what is the transmissible distance of SARS-CoV-2” and “what are the appropriate ventilation rates in the office” have been under debate. Without quantitative evaluation of the infection risk, some studies challenged the current social distance policies of 1–2 m adopted by most countries and suggested that longer social distance rule is required as the maximum transmission distance of cough ejected droplets could reach 3–10 m. With the emergence of virus variants such as the Delta variant, the applicability of previous social distance rules are also in doubt. To address the above problem, this study conducted transient Computational Fluid Dynamics (CFD) simulations to evaluate the infection risks under calm and wind scenarios. The calculated Social Distance Index (SDI) indicates that lower humidity leads to a higher infection risk due to weaker evaporation. The infection risk in office was found more sensitive to social distance than ventilation rate. In standard ventilation conditions, social distance of 1.7 m–1.8 m is sufficient distances to reach low probability of infection (PI) target in a calm scenario when coughing is the dominant transmission route. However in the wind scenario (0.25 m/s indoor wind), distance of 2.8 m is required to contain the wild virus type and 3 m is insufficient to contain the spread of the Delta variant. The numerical methods developed in this study provide a framework to evaluate the COVID-19 infection risk in indoor environment. The predicted PI will be beneficial for governments and regulators to make appropriate social-distance and ventilation rules in the office.
登录
查看更多内容
影响因子:
4.9
作者:
Miller SL;Clements N;Elliott SA;Subhash SS;Eagan A;Radonovich LJ
通讯作者:
Radonovich LJ
影响因子:
7.4
作者:
Li, Xiangdong;Shang, Yidan;Tu, Jiyuan
通讯作者:
Tu, Jiyuan
影响因子:
3.7
作者:
Bourouiba, Lydia;Dehandschoewercker, Eline;Bush, John W. M.
通讯作者:
Bush, John W. M.
影响因子:
--
作者:
Baldwin, PEJ;Maynard, AD
通讯作者:
Maynard, AD
影响因子:
6.8
作者:
Baron, Rita Christiane;Risch, Lorenz;Risch, Martin
通讯作者:
Risch, Martin