InfectionSourceSink 201902091713 For the safety of those who may be sensitive and susceptible to a disease, it is useful for both the susceptible, and for carriers, to have information about the danger of a disease at any particular moment at a particular location. We can model this problem by using the language of sources and sinks. For a particular disease, sources and sinks form a network of connectivity, which we model as a directed graph. Such graphs are formed as entropy networks encoded in Finite State Machine format. Source and sink nodes maintain a connection via wireless internet to an exchange at gravitylover.com/p/14090/1/ which stores and publishes node states and positions. A locally positioned node in real space can then predict source and sink interaction by downloading nearby node positions. The spatial vectors of nodes can be used to predict source-sink interaction. Linking the vectors to a spatial context database of the built environment can help predict the probability of a source reaching a sink. 20220212121212WA earwiggler pandemic project 202002081022WA Monitors: 2019-nCoV Dingxiang Yuan 2019-nCoV Boston Children's Hospital 2019-nCoV Johns Hopkins CSSE