Health insurance doctors develop early warning system for second corona wave

Photo: Uwe Anspach / dpa

Politicians and doctors worry about a possible second corona wave before the overload of the hospitals and the overload of the resident doctors.

The Central Institute for Statutory Health Insurance in Germany (Zi) has developed an early warning system: It shows how much time remains with an increase in infections in order to react in good time.

The early warning system is based on six indicators and enables epidemiological monitoring – and thus a return to normality with simultaneous safety.

Politicians are very afraid of the second or even third corona wave: Even though the number of infections has been falling continuously for weeks and the risk of infection has decreased, Federal Chancellor Angela Merkel (CDU) warned on Wednesday of a second wave – and that planned loosening actually only reluctantly supported: “We can afford a bit of courage, but we have to remain careful”.

The President of the Robert Koch Institute (RKI) Lothar Wieler also warned at the press conference on Tuesday about an upcoming second wave in the corona pandemic. The virus will keep us busy until 60 or 70 percent of the population is infected with it. “That is why we know that there is almost certainly a second wave,” said Wieler.

The concern about a new wave of infection concerns above all a possible overload of the hospitals. Around 40 percent of intensive care beds in Germany are currently free, so the situation is at least currently relaxed. But what if the situation suddenly worsens again? There are also concerns about an overload of the resident doctors should the numbers rise again.

Early warning signals help manage the pandemic

The so-called Central Institute for Statutory Health Insurance in Germany (Zi), the research institution of German statutory health insurance physicians, has now developed an early warning system that allows the federal and state governments to recognize how much time they have to take appropriate measures in the event of a new corona wave to avoid overwhelming the healthcare system.

This early warning system is intended to help replace a general lockdown with epidemiological monitoring. Measures and their effects do not have to be introduced and relaxed again in blind flight – instead, the effects of the measures can be monitored on a daily basis. According to the Zi, this enables a return to a safe normal state, both in medical care and in business life.

The limit values ​​defined by the early warning system could therefore give politicians the security of being able to react to a possible second wave in good time – and to slow them down before it is too late.

Six indicators were combined for the early warning system

The leading indicator is based on six indicators that the researchers derived from the known numbers and combined in part.

1. The load limit of inpatient care: Here it was calculated how many infections per day would lead to an overload or overload of the healthcare system. It was taken into account how high the proportion of all patients who come to the hospital is and how long they stay there on average. According to the doctors, the intensive medical stress limit would have been reached at a rate of 16,340 new infections daily.

2. The load limit of the contract medical care: These considerations include the number of physicians in practice in Germany, their time capacity, the proportion of Covid 19 patients who receive exclusively outpatient care and the proportion of these who require intensive care from a doctor.

3. The exposure limit in the German healthcare system: By comparing the first two points, the analysis shows that the intensive care capacities are more important because they exhaust more quickly. “The decisive factor is the intensive medical treatment capacity for setting the exposure limit. It is 163,340 actively infected or 16,340 new infections every day, ”write the doctors.

Also read: RKI boss: “We know that there is almost certainly a second wave”

4. The number of reproductions and the number of new infections: R indicates how many other people are infected. An increase in the number of reproductions above 1 would quickly lead to significant new infections with exponential growth. “That is why their development and the change in the reported daily case numbers must be closely monitored.” The doctors here recommend sticking to mean values ​​so as not to overestimate fluctuations caused by weekdays.

5.Warning time: The doctors derive the advance warning time from the two previous values. To do this, they project how the number of new infections would change depending on R. In doing so, they assume the relationship between the two values, which is known to researchers up to now. R is thus changed fictitiously (“What if R had risen to 1.3?”). This modeling can be used to derive the period in which the health system’s exposure limit would be reached. This period could then be used to counteract this. The higher the R value, the shorter the warning time for the same initial conditions. With an R-value of 1.5 or higher, less than two months remain until measures have to be effective so as not to overload the healthcare system.

6. Effective warning time: The doctors deduct a few more days from the calculated anticipation period, which can be caused, for example, by the fact that those affected can usually only be tested after about five days, there is a delay in reporting by the health authorities that the politicians need about six days to Decide on measures and put them into effect – and that the measures in turn take about a week to show results. These delays add up to approximately 21 days and are deducted. The effective warning time remains.

There was at least 90 days left to respond to an increase

“Based on the current number of cases, it follows that the politicians would have between 90 and 150 days to react (…) if the number of reproductions today would have been between R = 1.2 and R = 1.3”, says in a Zi statement. In fact, the R-value is currently (as of May 6, 2020) just over half, at R = 0.65.

“The leading indicator only becomes relevant with increasing new infections and shows the period of time until there is a potential overwhelming burden on the healthcare system. This makes it clear that not every increase has to be critically evaluated immediately, ”said the Zi.


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