论文标题
使用基于代理的模型探索COVID-19触点跟踪应用程序的有效性
Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
论文作者
论文摘要
在放松锁定措施后，必须采用接触追踪策略来控制共vid-19的传播。使用基于代理的模型，我们探索了提出的基于技术的策略之一，这是一种接触式智能手机应用程序。该模型模拟了Covid-19在城市规模上的众多代理商中的传播。代理商的特征是异质的，并且与代表社会结构的多层网络相连，包括家庭，友谊，就业和学校。我们探讨了接触追踪应用程序的各种采用率，不同水平的测试能力以及评估对流行病的影响的行为因素的相互作用。结果表明，当伴随着足够的测试能力或测试策略优先症状时，接触跟踪应用程序可以为降低人群的感染率降低。随着用户率的增加，感染的患病率会降低。因此，如果未优先考虑有症状的病例，则高度的应用程序用户可以产生大量测试需求增加，如果没有足够的供应，则可能会使应用程序适得其反。这表明有效的测试政策以及高档测试能力的必要性的关键作用。
A contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure - including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.
