The Safe Blues protocol and machine learning techniques have been developed together with an experimental minimal viable product, presented as an app on Android devices with a server back-end. Then using machine-learning techniques the Safe Blues system creates more accurate projections about the current and near-future state of the epidemic. Real time counts of multiple forms of the tokens are combined with delayed measurements of the actual epidemic. Safe Blues strands are safe virtual `virus-like' tokens that are spread using cellular devices and Bluetooth. Safe Blues fills this need, providing real time population-level estimates of the level of physical proximity and near-future projections of the epidemic. There is thus a pressing need for real time information on the level of physical proximity while respecting personal privacy. Consequently there can be a time lag of the order of several weeks between the initiation of a regulatory measure and its observed effect. However, with a pandemic such as COVID-19, the data is always lagging and biased since the time between a patient being infected with SARS-CoV-2 and being recorded as positive can be a week or more. It is this last element that governments can control through social-distancing directives. Viral spread is a complicated function of multiple elements including biological properties, preventative measures such as sanitation and masks, the environment, and the level of physical proximity. Safe Blues: A Method for Estimation and Control in the Fight Against COVID-19 Overview
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