论文标题

计算风险增加以在流行病期间做出决定

Counting Risk Increments to Make Decisions During an Epidemic

论文作者

Hardy, Lucien

论文摘要

我提出了一个智能手机应用程序,该应用程序将使人们能够在流行病或大流行期间(例如Covid-19)参与自己的安全管理,使他们能够提前查看,如果他们访问某个给定的场地(一个咖啡馆,健身房,工作场所,公园,公园,...),以及在任何一周或一周的时间内都会累积此类风险,他们将承担的风险。这个想法可以作为计数点显示给应用程序的用户。一个点表示感染的$ p_ \ text {point} $。然后,该应用程序将以与卡路里计数应用程序相似的方式工作(而不是计数卡路里,我们计算被感染的概率增加)。政府可以根据其目标设定最多建议的每日(或每周)点数(或每周)的积分(使疾病受到控制,使必不可少的工人能够工作,保护脆弱的人...)。有人认为,这以及其他提议的“杠杆”将使政府能够逐步过渡到正常状态。我讨论了一个电路框架,其中的电线在盒子之间运行。在此框架中,电线代表了可能的感染来源,即个人和场地本身(通过剩下的病原体沉积)。盒子代表这些来源的互动(当个人访问场地时)。该电路框架允许(i)计算访问场所的点成本和(ii)概率接触跟踪。这里提出的积分可以通过添加功能以允许用户参与决策来补充现有的联系跟踪应用程序。

I propose a smartphone app that will allow people to participate in the management of their own safety during an epidemic or pandemic such as COVID-19 by enabling them to view, in advance, the risks they would take if they visit some given venue (a cafe, the gym, the workplace, the park,...) and, furthermore, track the accumulation of such risks during the course of any given day or week. This idea can be presented to users of the app as counting points. One point represents some constant probability, $p_\text{point}$, of infection. Then the app would work in a similar way to a calorie counting app (instead of counting calories we count probability increments of being infected). Government could set a maximum recommended number of daily (or weekly) points available to each user in accord with its objectives (bringing the disease under control, allowing essential workers to work, protecting vulnerable individuals, ...). It is posited that this, along with other proposed "levers" would allow government to manage a gradual transition to normalcy. I discuss a circuit framework with wires running between boxes. In this framework the wires represent possible sources of infection, namely individuals and the venues themselves (through deposits of pathogens left at the venue). The boxes represent interactions of these sources (when individuals visit a venue). This circuit framework allows (i) calculation of points cost for visiting venues and (ii) probabilistic contact tracing. The points systems proposed here could complement existing contact tracing apps by adding functionality to permit users to participate in decision making up front.

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