论文标题
基于代理的模型使用GPS分析用于感染扩散和SARS-COV-2在东京的抑制机制
Agent-based model using GPS analysis for infection spread and inhibition mechanism of SARS-CoV-2 in Tokyo
论文作者
论文摘要
根据实际数据分析SARS-COV-2大流行爆发，同时反映真实城市的特征为将来采取合理的感染控制措施提供了有益的信息。我们根据GPS信息和官方国家统计数据展示了基于代理的建模，并对东京感染情况进行时空分析。由于使用真实的GPS数据在东京的第一波SARS-COV-2浪潮中进行了模拟，该感染发生在服务行业，例如餐馆，市中心，然后被感染的人们将病毒带回了住宅区；感染在东京的每个地区蔓延。这种现象阐明了感染的传播可以通过抑制出去或加强服务设施中的感染预防措施来遏制。结果表明，东京的大流行措施不仅可以通过强大的控制（例如城市的封锁）来实现，而且还可以通过在服务设施中的彻底感染预防措施来实现，这解释了真正东京的遏制现象。
Analyzing the SARS-CoV-2 pandemic outbreak based on actual data while reflecting the characteristics of the real city provides beneficial information for taking reasonable infection control measures in the future. We demonstrate agent-based modeling for Tokyo based on GPS information and official national statistics and perform a spatiotemporal analysis of the infection situation in Tokyo. As a result of the simulation during the first wave of SARS-CoV-2 in Tokyo using real GPS data, the infection occurred in the service industry, such as restaurants, in the city center, and then the infected people brought back the virus to the residential area; the infection spread in each area in Tokyo. This phenomenon clarifies that the spread of infection can be curbed by suppressing going out or strengthening infection prevention measures in service facilities. It was shown that pandemic measures in Tokyo could be achieved not only by strong control, such as the lockdown of cities, but also by thorough infection prevention measures in service facilities, which explains the curb phenomena in real Tokyo.
