CodeForPhilly / CodeForPhilly/chime
["model"] Check impact of latent period delay from infectious to hospitalized on model dynamics and forecasts
- Lingua principale
- Python
- Stelle
- 210
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- 153
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Descrizione
### Summary
There's no a priori reason to assume that transition of a person from the Susceptible to Infectious states corresponds with immediate development of symptoms requiring hospitalization. If there's a separation in time, then the model may be mis-predicting spread in the region by initializing `I` based on present-day hospitalizations.
We need to check whether accounting for this affects relevant forecast outputs.
### Additional details
### Suggested fix
Shift the initialization from current hospitalizations to community infection rate back in time by a configurable `latent_period`, and then shift forecast admissions of newly-infected individuals forward in time by that same `latent_period`
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