EHS Integration and Engineering Solutions

Resistance is futile

The dotted line represents 0.1% death for a per million population. If the death rate is truly 0.1%, then all of the countries will eventually merge to that line (and it really does look like that is the asymptote). The clusters shown below, are not a measure of medical care, but should be considered a measure of isolation. Given that, this is beyond containment, resistance is futile, and you will be assimilated. Its a matter of time, but all countries will approach that line. How long it take is just a matter of how long people can hold out in their shelters, eventually, everyone will be exposed, and death will merge to the 0.1% line.

Belgium is in the lead of the death curves, as can be seen in our last post (semi-log plot). Here is a population adjusted, infected(solid) and death(dotted) slope curves for four countries, plus our SIR models. The models are for different social distancing start dates.

Given Sweden's different approach to attacking the corona virus, we decided to add Sweden's data to the analysis. They have a volatility and response that is very different from the social distancing approach. The death percentages noted in the death lines, is the current percentage for that country, and is not a positional value in the plot. It is calculated by the area under the death curve in proportion to the recorded confirmed total. All plots are adjusted for population, per million. Total infected and total deaths are represented by the area under each respective curve. The death plot , is a semi-log plot, also population adjusted per million.

Due to the volatility, it is hard to tell if Sweden has turned the infected corner, however gauging from their death plot, it looks like they may have. It also looks like their final death percentage may be between, US and Italy. Time will show us a clearer picture.

COVID191

Updated the Italy comparison plot, that compares our position in time relative to Italy, this one normalizes to population size. This normalization helps for a better comparison. Assuming we follow Italy's lead in a relative scope, it is pretty close to what we should expect. Updated the plot to include the projected epidemiological curve, from our SIR model.