论文标题
移动智能手机跟踪几乎可以检测到所有SARS-COV-2感染
Mobile smartphone tracing can detect almost all SARS-CoV-2 infections
论文作者
论文摘要
当前，许多国家正在考虑在移动智能手机上引入跟踪软件，其主要目的是为移动应用程序用户提供信息和警告。在这里，我们证明，除了令人震惊和通知外，移动跟踪还可以检测几乎所有被SARS-COV-2感染的用户。我们的算法BETIS（贝叶斯对追踪感染状态的估计）利用了用户健康状况的自我报告。然后，Betis保证可以检测到几乎所有SARS-COV-2感染。此外，贝蒂斯（Betis）估计了整个人群中的病毒患病率，包括用户和非用户。贝蒂斯基于隐藏的马尔可夫流行模型和递归贝叶斯过滤。除了医学测试和隔离外，移动追踪应用程序的潜力还可以消除Covid-19，这可能会说服公民对公共卫生进行权衡隐私。
Currently, many countries are considering the introduction of tracing software on mobile smartphones with the main purpose to inform and alarm the mobile app user. Here, we demonstrate that, in addition to alarming and informing, mobile tracing can detect nearly all users that are infected by SARS-CoV-2. Our algorithm BETIS (Bayesian Estimation for Tracing Infection States) makes use of self-reports of the user's health status. Then, BETIS guarantees that almost all SARS-CoV-2 infections of the group of users can be detected. Furthermore, BETIS estimates the virus prevalence in the whole population, consisting of users and non-users. BETIS is based on a hidden Markov epidemic model and recursive Bayesian filtering. The potential that mobile tracing apps, in addition to medical testing and quarantining, can eradicate COVID-19 may persuade citizens to trade-off privacy against public health.
