Corona virus (COVID-19) - a system dynamics simulation model using not just the bass diffusion

Kai Neumann

Simulationsergebnisse von Faktor Infected

PI

This is the initial model assuming that the rapid spread is just slowed down in order to be tackled by an abstract number of intensive care capacities. It uses a range function for different assumptions on how many days it takes social distancing to work, ranging from 1 to 10 days. However, the current efforts on social distancing and the actual figures on intensive care capacities required an enhanced model that is shown with the following slides:

Modell aus Perspektive des Faktors Casualties (dying)

PI

This is the current version of the model with pink factors showing levers, orange mostly parameters, red the bad factors and green and yellow what we hope for. You can run scenarios from any of these factors and add curves for comparison.

Simulationsergebnisse von Faktor Diffusion rate

PI

The diffusion rate as a crucial factor representing the effectiveness and possible delay of social distancing is shown in this table. It means that with a value of 0.05 every infected person will infect another every 20 days or in other words each day every 20th infected person will infect another one .... all slowed down by the decrease of likelihood to meet persons that are not infected yet (the so called bass diffusion).

Simulationsergebnisse von Faktor Total deaths

PI

This chart shows the effect of delayed action/social distancing, whether from government's action or people's discipline. The lowest death toll we get with immediate action and more than twice the number if we wait for 10 days.

Simulationsergebnisse von Faktor Proportion cured

PI

This table shows how quickly we run out of caring capacities even though it assumes that we manage to more than double them after 30 days. It assumes a proportion of 10 percent of people that go treated (50 percent the model assumes don't get diagnosed) that are potentially in need for intensive care. Hopefully this figure is lower.

Simulationsergebnisse von Faktor New infections

PI

This chart shows with the dark red line how after an initial exponential growth the number of new infections will oscillate, the deaths will stop after 400 days when the cure is available and after 500 days (quite unrealistic assumption) the social distancing will be abandoned so the rest will quickly become infected but not dying.

Simulationsergebnisse von Faktor Total deaths

PI

This chart has adopted latest theories on how many cases remain undetected and it also features a lower fatality rate. While the total deaths my be lower the pattern remains the same - without social distancing our medical capacities wouldn't match the severe cases and lead to preventable deaths.

Simulationsergebnisse von Faktor New infections

PI

Current scenario with 80 percent undetected and massive social distancing - more infected people out there with fewer new infections

Simulationsergebnisse von Faktor New infections

PI

Massive testing, less social distancing - fewer infected people out there but more infections because of less social distancing