Prediction of Epidemic of Infectious Disease by Statistical Modeling, and Scientific Policy Making

像东京一样，我们在电脑上构建了包含5个区域的虚拟城市，其中有120万居民居住在那里，这些居民分为公司员工、学生和非工作人员三种属性。建立了基于智能体的传染病模拟模型，对学校、公司和商店的传染病进行了模拟。我们调整了模拟模型中的参数，使传染率达到30%，并执行了三种类型的疫苗衍生策略；优先考虑公司员工，内部人员或随机派生。因此，优先考虑公司员工是最有效的。

Like Tokyo, we constructed virtual city including five areas on computer and 1.2 million residents, which are categorized into three attributes, company employees, students and non-workers, lives there. An agent-based simulation model was established to simulate epidemic at schools, companies or stores. We tuned the parameters in the simulation model so that the infectious rate becomes 30% and performed three types of vaccine deriver strategies; priority to company workers, people in house or random deriver. As the result, priority to company workers is the most effective.