论文标题
使用基于代理的模型在超市中建模Covid-19在超市中进行建模
Modelling COVID-19 transmission in supermarkets using an agent-based model
论文作者
论文摘要
自2020年3月上旬Covid-19爆发以来，英国超市已经实施了不同的政策，以减少商店中的病毒传播，以保护客户和员工，例如限制商店中的最大客户数量，商店布局的更改或执行强制性的面部涵盖政策。为了定量评估这些缓解方法，我们根据客户在客户与感染性客户的近距离花费的时间基于一个简单的病毒传输模型制定了一个基于代理的客户运动模型（由网络代表）。我们将模型应用于合成商店和购物数据，以显示如何使用我们的模型来估计商店中人与人类接触引起的感染数量以及如何建模不同的商店干预措施。源代码可在https://github.com/fabianying/covid19-supermarket-abm上公开获得。我们鼓励零售商使用该模型来找到最有效的商店政策，以减少商店中的病毒传播，从而保护客户和员工。
Since the outbreak of COVID-19 in early March 2020, UK supermarkets have implemented different policies to reduce the virus transmission in stores to protect both customers and staff, such as restricting the maximum number of customers in a store, changes to the store layout, or enforcing a mandatory face covering policy. To quantitatively assess these mitigation methods, we formulate an agent-based model of customer movement in a supermarket (which we represent by a network) with a simple virus transmission model based on the amount of time a customer spends in close proximity to infectious customers. We apply our model to synthetic store and shopping data to show how one can use our model to estimate the number of infections due to human-to-human contact in stores and how to model different store interventions. The source code is openly available at https://github.com/fabianying/covid19-supermarket-abm. We encourage retailers to use the model to find the most effective store policies that reduce virus transmission in stores and thereby protect both customers and staff.
