| Name: |
Package for Respiratory Disease Open-source Forecasting (beta version) |
| Abbreviation: |
PSI-PROF_beta
|
| Owner: |
lshandross
|
| Team name: |
Predictive Science Inc. |
| Description: |
A beta-version of PROF, for testing new features in a prospective forecasting environment. This model adds compartments for vaccinated subjects to the existing PROF methodology. |
| Contributors: |
Michal Ben-Nun (Predictive Science Inc) <mbennun@predsci.com>, James Turtle (Predictive Science Inc) <jturtle@predsci.com>, Pete Riley (Predictive Science Inc) <pete@predsci.com> |
| License: |
Creative Commons Attribution 4.0 |
| Notes: |
NOT a designated model // Data inputs: "Daily and weekly incident flu hospitalizations from the HHS COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries. US Census population estimates. Previous Season Vaccination Time-Series from CDC/NCIRD" // Team funding: "CSTE/CDC: Development of Forecasts and/or Scenario Projections for Influenza to Inform Public Health Decision Making (Cooperative Agreement number NU38OT000297)." |
| Citation: |
https://doi.org/10.1371/journal.pcbi.1010375 |
| Methods: |
The PROF routines perform a deterministic fit of our compartmental SIR[H]2 model to daily hospitalization incidence profiles. The model includes a hospitalization compartment which is split into two sub-compartments. This split ensures that the model preserves the correct generation time (Tg) and that the ratio between cumulative recovered and hospitalized individuals is determined by the infection-hospitalization-ratio. The transmission-rate coefficient (Beta) is a time-dependent function of 2 or more arc-tangents. The model fit is inferred by an MCMC procedure. It is followed by stochastic simulations through the forecast time-window using the inferred parameter distributions and a daily cadence which is then aggregated to weekly incidence to produce the forecasts. Where there is little-to-no epi signal in the data, a baseline statistical model is substituted for the mechanistic model. This model is similar to our standard model 'PSI-PROF', but with the addition of vaccinated compartments for Susceptibles and Infectious, and with deterministic simulations through the forecast time window. //
Update 2023-10-10: Vaccine efficacy against severe disease set at 0.52 based on Southern Hemisphere results. |
| Home: |
https://www.predsci.com/usa-flu-hosp/
|
| Auxiliary data: |
(No URL)
|