RESUMEN
AO_SCPLOWBSTRACTC_SCPLOWRt plays a key role in the development of the COVID-19 pandemic. The methods used for building an interactive website for the visualization of the time-varying reproduction number Rt and a novel way to visualize the time delay from infection to estimation overlayed with the Rt estimate are described and analyzed with regards to the influence of parameters chosen and compared to published estimates for Austria. Visualizing the time delays enables the interactive exploration of suspected changes in transmission and their effect on the Rt estimate.
RESUMEN
As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly modelled the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We used changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. Nationally, we estimated 3.7% [3.4%-4.0%] of the population had been infected by 1st June 2020, with wide variation between states, and approximately 0.01% of the population was infectious. We also demonstrated that good model forecasts of deaths for the next 3 weeks with low error and good coverage of our credible intervals.