A probabilistic graphical model for COVID-19 infection spread through a population based on mutual contacts between pairs of individuals across time as well as test outcomes The C++/Python implementation enables full inference at the scale of millions of contacts between thousands of individuals.
MIT License
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Infection status computed with forward smoothing (no Gibbs sampling) #2
The proposed approach may be wrong! I'm closing the PR