Data61, CSIRO, Sydney, Australia.
Research Centre for Integrated Transport Innovation,School of Civil and Environmental Engineering, University of New South Wales, Sydney, NSW, Australia.
BMC Infect Dis. 2022 Aug 17;22(1):694. doi: 10.1186/s12879-022-07664-0.
COVID-19 has had a substantial impact globally. It spreads readily, particularly in enclosed and crowded spaces, such as public transport carriages, yet there are limited studies on how this risk can be reduced. We developed a tool for exploring the potential impacts of mitigation strategies on public transport networks, called the Systems Analytics for Epidemiology in Transport (SAfE Transport). SAfE Transport combines an agent-based transit assignment model, a community-wide transmission model, and a transit disease spread model to support strategic and operational decision-making. For this simulated COVID-19 case study, the transit disease spread model incorporates both direct (person-to-person) and fomite (person-to-surface-to-person) transmission modes. We determine the probable impact of wearing face masks on trains over a seven day simulation horizon, showing substantial and statistically significant reductions in new cases when passenger mask wearing proportions are greater than 80%. The higher the level of mask coverage, the greater the reduction in the number of new infections. Also, the higher levels of mask coverage result in an earlier reduction in disease spread risk. These results can be used by decision makers to guide policy on face mask use for public transport networks.
COVID-19 在全球范围内产生了重大影响。它很容易传播,特别是在封闭和拥挤的空间,如公共交通工具车厢内,但关于如何降低这种风险的研究有限。我们开发了一种用于探索缓解策略对公共交通网络潜在影响的工具,称为交通流行病学系统分析(SAfE Transport)。SAfE Transport 将基于代理的交通分配模型、全社区传播模型和交通疾病传播模型结合在一起,以支持战略和运营决策。在这个模拟 COVID-19 的案例研究中,交通疾病传播模型结合了直接(人与人之间)和媒介(人到表面到人与人之间)传播模式。我们确定了在七天模拟期间戴口罩对火车的可能影响,当乘客戴口罩的比例大于 80%时,新病例的数量会大幅减少,且具有统计学意义。口罩覆盖程度越高,新感染人数的减少就越大。此外,较高水平的口罩覆盖度可更早地降低疾病传播风险。这些结果可供决策者用来指导公共交通网络上使用口罩的政策。