Coronervirus Statistics: What can we believe, and what should we ignore?

In recent weeks we have seen an unstoppable epidemic of statistics. Vala threatens to snatch us all, but what do all these numbers mean? Here are eight statistics you can see, with some warnings of how much we can trust them.

1. The number of new cases every day. This could be a very poor reflection of the number of people who have actually been infected, as it depends substantially on the regime of tests conducted until April 9th, 1.3 million tests were conducted in Germany, against 317,000 in the United Kingdom.

2. The number of new deaths every day. The range of resources is surprising. Day-to-day reports should be carefully addressed, as they include only hospital deaths of those tested positive for coronarys, and there is usually a delay in reporting deaths for several days or longer.

3. The total death toll. Acumulating death graphs are shown in the daily government press conferences, but they are a hopeless tool for detection trends: we need daily counting to see if we have reached a “culm”. But day-to-day calculations are unstable, and so it's possible to extract basic trends: The world in the data uses a three-day average mobile.

4. Numbers Recorded on a Logical Scale. This will have a vertical axis labeled 1, 10, 100, 1,000. These are useful in comparing tendencies but useless in creating an impression of the size of the problem.

5. Forecasts from computer programs. Computer models try to shape the epidemic itself by making simplified assumptions about the mechanism with which a virus spreads through a community. The main amounts, such as how many people may infect an average case, are highly insecure at the beginning of an epidemic but become much more accurate after more data is collected. Such models have formed the basis for predicting the consequences of policy decisions in the United Kingdom.

6. “extra death” The number of additional deaths to be recorded in this period, due to Avid-19 or the impasse, has been sharply opposed. Life will be lost because of sickness, reduced medical care for all, domestic violence and the effects of unemployment and poverty; and life will be saved through fewer accidents and, especially, improved air quality.

7. Deadly risks from infection. These vary dramatically with age and how weak the person is physically, or so-called <x0-> abnormal risks”. In fact, the current assessments of the general public seem extremely similar to the risks we face each year, but all of these have gathered within weeks.

8. “The accuracy of a test. Even seemingly accurate tests can lead us to false conclusions, thinking we have immunity. But a less accurate test can be better if we test a representative sample to assess the proportion of an immunity population.