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.

Latest population adjusted confirmed and death cases, sorted by country. Legend is sorted from worst to least. Population of Hubei used for China. (Johns Hopkins CSSEGISandData/COVID-19)

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

US-Italy comparison. (updated 4/14/2020) Our latest SIR is on track. Italy and US have a similar population adjusted responses. The US death plot (semi-log) is proportionally in-line as well. (Johns Hopkins CSSEGISandData/COVID-19)

COVID191 CoviD-19

Just wanted to give a last post peak update, from our original projection. Here is the latest attached plot, with an interesting update.

You will be able to notice a similar transition that both countries experienced, weeks apart. When we saw the correlation, it caught our attention. We were able to replicate this effect in our mathematical model/simulation.

What is occurring is that the initial upward slope occurs while the news of the virus has not yet started. Then, after about 25 days, the news cycle starts and everyone starts social distancing. We took our model and throttled it for social distancing. Modeling people shuttering themselves in (zero contacts) and then going out again (new contacts), and so forth. It looks like the repeatable perturbations are a result of social distancing.

(Note: These are plots of slope for the confirmed cases, adjusted for population size. We are using the data located in the Johns Hopkins CSSEGISandData/COVID-19 github repository.)

COVID191 Unite Against Covid-19 Covid-19 Pandemic Tracking

(4/9/2020) Our predicted date is here, and our plots are well aligned to our SIR model. (Suspected Infected Recovered mathematical projected curve)

The perturbations are very interesting, give that the two events occurred almost a month apart. We believe the behavior of the curves are related to social distancing. The first major drop is the delayed effect of when social distancing started.

We added a second plot, that shows Italy's recovered rate in comparison to the US. The units are on recovered persons per million.

Updated SIR model and collected data. The first major dip for the US, looks like this dip is the delayed effect of social distancing. Both countries experience a similar dip, about 25 days from their respective onset. The US recovered curve also tracks well with the SIR model.

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.

We 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. Making predictions is not easy, but assuming we follow Italy's lead in a relative scope, it is pretty close to what we should expect. We are currently comparing the two countries to a normalized distribution. but we will update the plot to reference the correct epidemiological curve.

Social distancing can be stressful. Here is a good article about how we can try to make it as positive as we can possibly can.

COVID-19 pandemic: Tips to remain ‘sane and safe’ during social distancing Muncie, IN — Maintaining a routine, helping others and taking time to focus on self-care are among the tips one Ball State University professor is sharing to help people stay “sane and safe” while practicing social distancing during the COVID-19 pandemic.

Attached is a list of EPA registered products claimed to be effective for use against SARS-CoV-2.

List N: Disinfectants for Use Against SARS-CoV-2 | US EPA List N includes products with an emerging viral pathogen claim and products with claims for human coronaviruses.