 To derive future ICU load from reported infections, we suggest a simple statistical model that (1) accounts for time lags and (2) allows for making predictions depending on different future growth rates. We evaluate our model for public data from Berlin, Germany, by first estimating the model parameters (i.e., time lag and average stay in ICU)for March 2020 and then using an exponential model to predict the future ICU load for April and May 2020.
<clarity>  To derive future ICU load from reported infections, we suggest a simple statistical model that (1) accounts for time lags and (2) allows for making predictions depending on different future growth rates. We evaluate our model for public data from Berlin, Germany, by first estimating the model parameters (i.e., time lag and average stay in ICU)for March 2020 and then using an exponential model to predict the future ICU load for April and May 2020.
 To derive future ICU load from reported infections, we suggest a simple statistical model that (1) accounts for time lags and (2) allows for making predictions depending on different future growth of infections. We have evaluated our model for public data from Berlin, Germany, by first estimating the model parameters (i.e., time lag and average stay in ICU)for March 2020 and then using an exponential model to predict the future ICU load for April and May 2020.