Author: Joshua A Salomon
Title: Defining high-value information for COVID-19 decision-making Document date: 2020_4_8
ID: iymhykq8_7
Snippet: Basic Using a Bayesian calibration approach, 11 we fit model parameters to approximate the pooled population and rise in confirmed COVID-19 cases through March 15 across six counties in the San Francisco Bay Area. These counties collectively comprise an early epicenter of spread in the US and were also early adopters of NPIs. We projected two scenarios from March 16 through June 30: a 'no intervention' counterfactual scenario and an 'NPI scenario.....
Document: Basic Using a Bayesian calibration approach, 11 we fit model parameters to approximate the pooled population and rise in confirmed COVID-19 cases through March 15 across six counties in the San Francisco Bay Area. These counties collectively comprise an early epicenter of spread in the US and were also early adopters of NPIs. We projected two scenarios from March 16 through June 30: a 'no intervention' counterfactual scenario and an 'NPI scenario' in which we assumed that all contact rates would be reduced by 10% to 60% after March 15.
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