ABSTRACT
Multiple journal editorials and letters to the editor have referenced the many SARS-CoV-2 (novel coronavirus or COVID-19) forecasting models, sometimes with wildly diverging predictions. The use of open source models (OSMs), those for which all data and programming associated with the model are made openly available to enhance transparency and, perhaps, facilitate replication and ongoing modifications of the model, have the potential to allow for faster access to critical knowledge. Use of OSMs, perhaps in an easily accessible database, could allow for the aforementioned “crowdsourced” model review and more accurate/timely models, at least as far as the existing data allow. A preliminary cost-effectiveness analysis of remdesivir, an agent that has shown promise in reducing the length of hospitalization for patients with advanced COVID-19 illness and lung involvement, used a short-term decision tree with a long-term Markov model, the health system perspective and a lifetime time horizon to calculate a reasonable price for remdesivir.
