Numbers are the ultimate object through which we see and quantify different phenomena, through them we understand our environment and also project events that will occur in the immediate future – with the help of computers we can sometimes look at the distant future. It is however, charts and visualizations that allow us to immediately grasp a larger view of quantified events – the following are visualizations of the covid-19 impact on our world.
The data used for the statistics and visualizations shown in this website are collected from various sources including from the Johns Hopkins University & Medicine Coronavirus Resource Center, the Government of Canada Coronavirus disease (covid-19), the World Health Organization Coronavirus disease (covid-19) Situation Dashboard and the Government of Quebec Situation of the coronavirus (covid-19) in Quebec. The data are collected, analyzed and formatted daily by the Responsa team.
Canadian confirmed cases of covid-19
Canadian deaths from covid-19
Deaths per 1 Million People
The ambiguous definition of what constitute a “Confirmed Case” of covid-19 has made it difficult to analyze the data that is collected by the international health agencies. An element that skews the data is the exclusion of the so-called asymptomatic cases – those who are identified only after they have been tested. Notwithstanding, the number of confirmed cases in the data set used in the next geo chart are those published by the Johns Hopkins Coronavirus Center – by far the most reliable.
According to the World Health Organization, the common flu causes 84 deaths per 1 million people in the world annually – covid-19 has already killed over 230 persons per 1 million people in Italy in less than 2 months. The argument that the common flu kills more people per million has by April 2nd, 2020 been debunked by the realities in: Spain – 221, Belgium – 87, France 85 and by tiny San Marino – 884 persons by 1 million people. The following Geo chart shows graphically the virulence of covid-19.
* The maximum range in the chart is intentionally set to 84 – the annual rates of the common flu for comparison.
The bubble chart shows the number of covid-19 deaths per 1 million population versus the number of confirmed cases. This number is sadly extremely high both in Spain and Italy which has already 4 times the number of the common flu attributed deaths per million people.
The potential devastation of a pandemic lies in its ability to spread rapidly and forcefully. The calculation for its rate of transmissibility is quite simple, it involves calculating the average reproduction number of secondary cases generated per a typical infectious case. In other words, simply dividing the current total number of infected cases by the number of the previous period – as an example: dividing the number of confirmed covid-19 cases of March 26th, 2020 – 525,364 by the number of cases on March 25th, 2020 – 458,224 would give us 1.15 meaning that each case generates 0.15 new cases, a higher result means a rapid spread probably through crowding, conversely, a number close to 1 means a certain degree of control. The next geo chart shows the situation in each country – the ones in red are sadly in for a rude awakening.
So what do all these numbers mean?
Can any meaningful projections be made based on the data?
Yes, straight-line projections based on historical data can be made. In fact, linear projections made over the last several days have accurately predicted the outcome of the following days – these projections however, do not take into account any other variables that might occur as a result of a conscious intervention. The following projections show a probable outcome should the conditions remain as they are now.