ABSTRACT

The recent Covid-19 outbreak has had a tremendous impact on the world, and many countries are struggling to help incoming patients and at the same time, rapidly enact new public health measures such as lock downs. Many of these decisions are guided by the outcomes of so-called Susceptible-Exposed-Infectious-Recovered (SEIR) models that operate on a national level. Here we introduce the Flu And Coronavirus Simulator (FACS), a simulation tool that models the viral spread at the sub-national level, incorporating geospatial data sources to extract buildings and residential areas in a region. Using FACS, we can model Covid-19 spread at the local level, and provide estimates of the spread of infections and hospital arrivals for different scenarios. We validate the simulation results with the ICU admissions obtained from the local hospitals in the UK. Such validated models can be used to support local decision-making for an effective health care capability response to the epidemic.

摘要

最近爆​​发的 Covid-19 疫情对世界产生了巨大影响，许多国家都在努力帮助新来的患者，同时迅速实施封锁等新的公共卫生措施。其中许多决定是由在国家层面运行的所谓的易感暴露感染恢复 (SEIR) 模型的结果指导的。在这里，我们介绍流感和冠状病毒模拟器 (FACS)，这是一种模拟工具，用于模拟次国家层面的病毒传播，并结合地理空间数据源来提取一个地区的建筑物和住宅区。使用 FACS，我们可以对 Covid-19 在当地的传播进行建模，并提供不同情况下感染传播和住院人数的估计值。我们使用从英国当地医院获得的 ICU 入院来验证模拟结果。