Non-csv text files are no longer supported. Improved data input allows more flexible specification of how to read data from csv or Excel data files.In preparation for switching from case counts based on the date lab result were received, to the earliest known date of infection (now reported on the Santa Cruz County dashboard) to fit the model, case count and death data are no longer required to use the same dates and can be specified in separate files.For the time being, the last entries are not added to the case count file when running the Santa Cruz County model to minimize the impact of this bias. Existing daily case counts from the week prior are often updated with new data each day. Due to laboratory reporting delays and the transition to episode date, the latest entries in a case count file are likely to be underestimates. The model is now using the earliest known date of infection for the case data (also known as episode date).Updating this repository with the latest version of the SCZ COVID-19 Model, the previous version has been moved to v9.The model does not account for spatial or network patterns.However, they likely will shed live virus longer, especially if immuno-compromised. Hospitalized COVID-19 patients have a shorter duration of their infectious period because they are less likely to expose others.COVID-19 cases only die within the hospital.Not everyone who tests positive for COVID-19 goes to the hospital.COVID-19 hospitalization, ICU, and death rates are calculated based on the overall age demographics of Santa Cruz County.COVID-19 cases can be infectious 2 to 3 days prior to symptom onset.COVID-19 cases who recover gain short-term immunity.A fraction of vaccinated individuals gain immunity. The model's contact rate adjusts every 5 days using spline interpolation.The current model is started on May 1 2021, with initial conditions estimated from a previous model simulation.Additional Assumptions of the SCZ COVID-19 Model Note: If you have issues, questions or find a bug please create an issue in GitHub (above). The Jupyter template notebook can be found here. The model contains 11 compartments to divide COVID-19 cases into the asymptomatic, mild, and moderate to severe illness, which better informs hospitalization and death projections (see diagram below). The model projects a range of different scenarios that fit the inputs provided and are displayed in the exported plots. The model is set to run 4,000 simulations and fine-tune the inputted parameters using the local data (confirmed COVID-19 hospitalizations, confirmed COVID-19 cases, and deaths). The model requires a set of parameters, equations, and local data to help inform its simulations. The Santa Cruz County (SCZ) COVID-19 model is a time-discrete, stochastic SEIR model that uses Bayesian statistical methods, such as Hamiltonian Markov Chain Monte Carlo (MCMC) simulations, to forecast the COVID-19 pandemic in Santa Cruz County, California. For the most recent projections, see the Santa Cruz County dashboard. However, to ensure HIPAA compliance, we are not adding the data files to this repository. We have added recent versions of the model here with updated code. Note: The latest versions of the model have been fit to age-structured data, part of which are not publicly available.
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