Author: Patrick Jenny; David F Jenny; Hossein Gorji; Markus Arnoldini; Wolf-Dietrich Hardt
                    Title: Dynamic Modeling to Identify Mitigation Strategies for Covid-19 Pandemic  Document date: 2020_3_30
                    ID: ngsstnpr_41
                    
                    Snippet: The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.27.20045237 doi: medRxiv preprint As a final mitigation strategy, we investigated a combination of social distancing and mass testing, i.e., from day 50 to 100 a 70% lower infection rate due to social distancing is considered, followed by a one year period with 1.7666 times higher detection rate. The corresponding plots are shown in Fig. .....
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.27.20045237 doi: medRxiv preprint As a final mitigation strategy, we investigated a combination of social distancing and mass testing, i.e., from day 50 to 100 a 70% lower infection rate due to social distancing is considered, followed by a one year period with 1.7666 times higher detection rate. The corresponding plots are shown in Fig. 7 . One can see that extreme social distancing brings the number of infections down and moderate testing keeps the values constant. Again, after the testing phase ends there is a delayed outbreak leading to the same end result as in the base case. In the bottom logarithmic plots of Fig. 7 the detected infected population (dotted lines) is shown together with the intensive care unit capacity (horizontal long dashed lines).
 
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