Putting SARS-CoV-2 statistics in the right perspective
There are lots of websites publishing maps and statistics of SARS-CoV-2. But do they really give the right picture? We are trying to put things in the right perspective.
As for today (even with pumped up numbers, after 6 months of haunting for Covid victims) only 0,008% of World population has died with the new Coronavirus. This means 8 in 100’000! The average age of people dying is 82 years! 96% of them have other comorbidities!
The graphs and maps come from https://ourworldindata.org/coronavirus-data-explorer website. We do NOT change or modify in any way the data or the way it is visualised!
Please, remember that in many countries the official “Covid-19” statistics have been greatly exaggerated and are currently being reviewed (or so we hope). Our maps are based on currently available data.
What is different about our maps?
It’s very simple – all maps we publish show data per 1 million of inhabitants. This gives the right perspective to the numbers.
Why don’t we publish the number of cases?
Simple – because the number of cases is completely irrelevant! According to worldometers 99% of people who test positive have mild or “asymptomatic” flu. This is putting in question how much we can even trust the tests. Even if the tests were 100% reliable, the number of cases would be only a function of the number of tests performed and would NOT reflect epidemiological reality.
In this case the only factors that matter are the number of deaths (indicates how much a country has been hit), number of critical cases and new death (indicate current situation).
Tests per confirmed case & share of positive tests
The higher the value the more tests had to be done to find one positive case. Remember, that some countries reduce the testing of people without symptoms, while other countries increase it.
High values can mean that the percentage of infected people is lowering. Low values can mean higher percentage of infected people OR change in policy regarding testing of asymptomatic people.
Understanding policy changes is critical in interpreting the below graphs.