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This is a predictive modeling tool to predict infections, fatalities, hospitalizations, critical cases, and ventilator usage for COVID-19 in the greater NY region.

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Model and Model Development

The SEIR model and application were developed by the University at Buffalo's Biomedical Informatics Department with special help from Matthew Bonner in the Department of Epidemiology and Environmental Health, Greg Wilding in the Department of Biostatistics, and Great Lakes Healthcare with Peter Winkelstein.

Building off of the core application from the CHIME model, our model adds compartments for Exposed and Death and fine-tunes the model for Erie County and hospital specific estimates.

Documentation of parameter choices and model choices can be found in the github Wiki. For questions, please email Gabe Anaya or Sarah Mullin.

As a note, these models are constantly being changed and updated as more information about COVID-19 surfaces. The deterministic models presented here are highly reliant on assumptions and parameter choice.

Acknowledgements

This work has been supported in part by grants from NIH NLM T15LM012495, NIAA R21AA026954, and NCATS UL1TR001412.

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This is a predictive modeling tool to predict infections, fatalities, hospitalizations, critical cases, and ventilator usage for COVID-19 in the greater NY region.

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