Every day the news announces the current status of the new infections – but this value alone is not enough to be able to assess the situation with certainty. It does not show how much the clinics are working to the limit, how many people die of their Covid 19 disease, how many infections are not discovered at all and are therefore even more easily passed on to other people. There are indicators that help to better shed light on the development of the pandemic. Many of these values are chronically underestimated – an overview.
Positive tests: on the trail of the dark field
Chronically neglected, for example, the number of carried out and the proportion of positive PCR tests: To get at least an idea of how many people become infected undetected, it helps to look at this number. The problem: If people experience only mild symptoms of the disease, they rarely take a test – and are therefore missing from the statistics. In the summer, at times only half a million PCR test smears were taken per week. An overview of the rapid tests, which were massively expanded in parallel, is missing. In the fourth wave, the need increased enormously to up to two million tests per week – a fourfold increase.
However, the test centers cannot keep up with the exponential growth of the pandemic. The incidence has increased by a factor of 16 since then. This is also reflected in the positive rate: In the summer, far less than five percent of all smears showed a corona infection in many weeks, by the end of November this proportion rose to a good 20 percent.
Such a high positive rate suggests that many more people than officially known are infected with the coronavirus. Because: If the proportion of positive tests increases with the test rules remaining the same, this indicates a large number of unrecognized infections. For the assessment of the situation of the pandemic, the positive PCR value is therefore an important parameter for illuminating the dark field.
R-value: transmissions from person to person
The new infections curve has one more weakness: the power of exponential growth is difficult for many people to understand. A similar dynamic can be concealed behind a low, almost flat-looking curve as behind a steeply rising curve.
The example with the grains of rice helps here. If you double two grains of rice on a chessboard to four, it seems like little. If you double 1000 grains of rice to 2000, it looks immense. But the dynamics are the same, i.e. in the example of Corona the rate of transmission of infection.
To make this more tangible, the reproduction number, or R value for short, helps. It says how many other people an infected person will infect. If the value is above one, the incidence increases; if it is lower, the number of new infections every day also decreases.
The R value shows at an early stage whether the pandemic is worsening and a new wave is rolling off. At the beginning of July it rose above one, marking the beginning of the fourth wave. At that time the incidence was less than ten. If infections had been prevented more consistently at this point, the fourth wave might never have piled up as high as in the past few weeks – with all the dead.
Doubling time: dynamic pandemic
A similar leading indicator is the growth rate. It shows how the number of cases is developing compared to the previous week. The higher the value, the shorter the time it takes for cases to double. Values below zero, on the other hand, show that the dynamic has broken and the incidence is falling again.
This curve also shows a fundamental problem: for every doubling step in the number of cases that society accepts, it also needs a halving step. It is easy to see from the curve that a doubling every two weeks was achieved much more often than a halving in the comparable period of time.
Age groups: Old people become more ill
In order to control measures in a targeted manner and save human lives, it is helpful to look at data that is as differentiated as possible – such as the positive rate broken down into age groups or the number of new infections. In the past few months, children and adolescents became infected much more frequently than older people.
Deaths: Only an issue for milestones
January 2021: two million deaths worldwide. November 2021: 100,000 dead in Germany. Apart from the milestones, the number of Covid deaths is hardly present in public. Few people realize that in the past week, an average of 400 people did not survive their Covid 19 disease every day. That means: as many deaths every week as in the attack on the World Trade Center on September 11, 2001.
The people who died of Covid-19 also represent those who survived their illness after a long struggle in the intensive care unit. About every fourth corona death died despite treatment in an intensive care unit, two thirds of corona intensive care patients survived. Those who survive invasive treatment need time and medical care to get back to life. Many other corona patients do not come to the intensive care units, but still have to be treated in the hospital. In 2020, according to the figures from the Federal Statistical Office, three out of four Covid deaths died in the hospital.
Statistically, every dead person not only stands for an overburdened health system, but also for many infected people, their sense of smell and weaknesses that have been lost for weeks, for many people in quarantine and often for excessive demands in the health authorities.
All numbers have weaknesses
Whether new infections, deaths or a positive rate: each indicator has only limited informative value, the context decides. Even the raw number of cases depends on political decisions: If there is no testing, fewer cases will be found and fewer corona deaths will be reported. A country can do well in a naive international comparison, at least until an inexplicable excess mortality is determined. This is a readily comparable indicator – but unsuitable for deciding on measures, as it only becomes meaningful in retrospect.
Even if each individual number alone cannot reveal much, there is an enormous amount of knowledge in the interplay of many indicators. Short-term developments can be predicted and long-term scenarios can be modeled. As early as July, the RKI described possible scenarios for an upcoming fourth wave in autumn and winter. Reality caught up with the models almost exactly a few weeks later.