Author: Wolfgang Bock; Barbara Adamik; Marek Bawiec; Viktor Bezborodov; Marcin Bodych; Jan Pablo Burgard; Thomas Goetz; Tyll Krueger; Agata Migalska; Barbara Pabjan; Tomasz Ozanski; Ewaryst Rafajlowicz; Wojciech Rafajlowicz,; Ewa Skubalska-Rafajlowicz; Sara Ryfczynska; Ewa Szczurek; Piotr Szymanski
Title: Mitigation and herd immunity strategy for COVID-19 is likely to fail Document date: 2020_3_30
ID: 48stbn6k_47
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . In contrast to R* there is no data we can align the simulation to for obtaining the R min and R max values. We defined R max as the smallest R* value for which 10 sample paths surpassed the ICU threshold within D days. For cities D was chosen to be 200 days and for countries 700 days. The critical value R min was defined as the largest R * < R max for which the daily in.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . In contrast to R* there is no data we can align the simulation to for obtaining the R min and R max values. We defined R max as the smallest R* value for which 10 sample paths surpassed the ICU threshold within D days. For cities D was chosen to be 200 days and for countries 700 days. The critical value R min was defined as the largest R * < R max for which the daily incidence at day 200 was below 50% of the initial number N o of infected. That is, it represents the R* that will most probably not threaten the health-care system. To find these values we started fitting a sparse grid of plausible R*. By bisection we gradually made the grid finer to approach both R min and R max as described above.
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