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