How data became one of the most powerful tools to fight an epidemic is a question that a recent (10 June 2020) The New York Times article poses in its title. Indeed, the spread of COVID-19 involves dynamically evolving hidden data (for example, the number of infected people, the number of asymptomatic people) that must be deduced from noisy and partially observed data (for example, the number of daily deaths, the number of daily hospitalizations, and the number of daily positive tests). The underlying mathematics for posing and solving this and several other partially observed dynamic problems is familiar to control theorists.

中文翻译：

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非线性滤波中的最优传输方法


《纽约时报》最近（2020 年 6 月 10 日）发表的一篇文章在标题中提出了一个问题：数据如何成为抗击流行病最有力的工具之一。事实上，COVID-19 的传播涉及动态演变的隐藏数据（例如，感染人数、无症状人数），这些数据必须从嘈杂和部分观察到的数据（例如，每日死亡人数、每日住院人数和每日阳性检测次数）。控制理论学家熟悉提出和解决这个问题以及其他几个部分观察到的动态问题的基础数学。