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An Agent-Based Modeling of COVID-19: Validation, Analysis, and Recommendations
Cognitive Computation ( IF 4.3 ) Pub Date : 2021-02-19 , DOI: 10.1007/s12559-020-09801-w
Md Salman Shamil 1 , Farhanaz Farheen 1 , Nabil Ibtehaz 1 , Irtesam Mahmud Khan 1 , M Sohel Rahman 1
Affiliation  

The coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted non-pharmaceutical interventions (NPI) to slow down the spread. This study proposes an agent-based model that simulates the spread of COVID-19 among the inhabitants of a city. The agent-based model can be accommodated for any location by integrating parameters specific to the city. The simulation gives the number of total COVID-19 cases. Considering each person as an agent susceptible to COVID-19, the model causes infected individuals to transmit the disease via various actions performed every hour. The model is validated by comparing the simulation to the real data of Ford County, KS, USA. Different interventions, including contact tracing, are applied on a scaled-down version of New York City, USA, and the parameters that lead to a controlled epidemic are determined. Our experiments suggest that contact tracing via smartphones with more than 60% of the population owning a smartphone combined with city-wide lockdown results in the effective reproduction number (Rt) to fall below 1 within 3 weeks of intervention. For 75% or more smartphone users, new infections are eliminated, and the spread is contained within 3 months of intervention. Contact tracing accompanied with early lockdown can suppress the epidemic growth of COVID-19 completely with sufficient smartphone owners. In places where it is difficult to ensure a high percentage of smartphone ownership, tracing only emergency service providers during a lockdown can go a long way to contain the spread.



中文翻译:


基于代理的 COVID-19 建模:验证、分析和建议



2019 年冠状病毒病 (COVID-19) 已导致全球范围内持续流行。各国已采取非药物干预措施(NPI)来减缓传播。本研究提出了一种基于代理的模型,可以模拟 COVID-19 在城市居民中的传播。通过集成特定于城市的参数,基于代理的模型可以适应任何位置。模拟给出了 COVID-19 病例总数。考虑到每个人都是 COVID-19 的易感者,该模型会导致受感染的个体通过每小时执行的各种操作来传播疾病。通过将模拟与美国堪萨斯州福特县的真实数据进行比较,对该模型进行了验证。在美国纽约市的缩小版上应用了包括接触者追踪在内的不同干预措施,并确定了控制流行病的参数。我们的实验表明,通过智能手机进行接触者追踪(超过 60% 的人口拥有智能手机),再加上全市封锁可导致有效传染数 ( Rt ) 在干预后 3 周内降至 1 以下。对于 75% 或更多的智能手机用户来说,新感染被消除,并且传播在干预后 3 个月内得到遏制。如果有足够的智能手机用户,接触者追踪和早期封锁可以完全抑制 COVID-19 的流行增长。在难以确保智能手机拥有率较高的地方,在封锁期间仅追踪紧急服务提供商可以在很大程度上遏制病毒传播。

更新日期:2021-02-19
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