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WIP: Exogenous rates #128

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WIP: Exogenous rates #128

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@odunbar odunbar commented Jun 16, 2020

To Resolve #84
This PR is to introduce exogenous rates. Currently 3 features in mind

  • Homogeneous rates, set uniformly on all 'user nodes'.
  • Heterogeneous nodal rates, varied depending on the ratio of user and 'non-user nodes'.
  • a data assimilator which can learn a constant factor of the exogenous rates.

Currently we set a user_connectivity score as a node attribute on the user nodes of the network. This is either 1 for all users (in the homogeneous case) or between [0,1) in the heterogeneous case. The score for a user is given by

({total_user_edges} - {user_edges_that_are_users}) / {total_user_edges}

Here, a score of 0 represents a node whose neighbors are completely contained within the user_base. and scores near 1 represent a node with many connections not within the user base.

This score is used to prefactor a (learned) exogenous_transmission_rate to produce the exogenous rate in the master equations, we call this eta.

eta = connectivity_score * exogenous_transmission_rate

@odunbar odunbar closed this Sep 11, 2020
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Exogenous infections
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