If the political goal should be to push R below 1 again, it should be noted that this will become more and more difficult as infection rates increase. As the proportion of contact tracing becomes smaller and smaller with their overload, it will need to be supplemented by more and more additional measures.

In the following, we list possible measures that we have calculated. For the quantitative effects of the measures, see the [Measure Calculator](/r-calcs/2020-10-23).

- Our calculations show that only **significant restrictions** in the leisure sector would have sufficient effect to push R below the critical value of 1.

- Ideally, this would be combined with a very significant increase in contact tracing capacity. This increase would have to follow the exponential curve of new infections, i.e. the necessary capacities would have to double (!) again every week. According to our calculations today (23.10) a tripling would be necessary; in one week it would be a sixfold increase.

- Closing hours or curfews in the leisure sector have an effect, but show a clear effect only with closing times well before 11:00 PM. This is because, except on Fridays and Saturdays in the evening, most leisure activities end before 11:00 PM anyway.

- Regarding work, we still recommend home office, single room or continuous mask requirements at the workplace. According to our calculations, this would make a significant contribution to reducing R, but would not be sufficient to push R back below 1.

- Regarding school, we recommend masks also at the desk or seat, and/or halved class sizes with alternating school days. Overall, according to our simulations, schools are not strong drivers of infection.

Our models allow the calculation of individual infection probabilities, e.g. about 30% at a typical dinner party when an infectious person is present.

We were able to estimate the parameters of our mathematical model with high fidelity, based on simulation results of the agent-based model. This allows us to quickly estimate the effects of different combinations of measures with the mathematical model without the need to use the agent-based model with its long computing times.
