The art of “DIVI-nation” – predicting tomorrow’s ICU capacities from today’s infection numbers

Preventing the health system from collapse has been repeatedly stated as one of the main objectives for the German containment policy for SARS COV 2. The exact relation between infections recorded in the public surveillance system maintained by the German center for disease control (RKI) and data on hospital occupation published by the German association for intensive care an emergency medicine (DIVI) has not been analyzed to date. Using a stepwise approach as described in the paper a linear regression model based on recorded infections with known disease onset was found to be the most suitable predictor for the number of ICU patients with a positive test for SARS COV 2 one month later. The model showed an excellent model fit with nearly 90% explained variance and reliable prediction of the maximum when applied to data beyond the construction dataset. Still, the number of additional patients with a diagnosis of COVID 19 does not necessarily mean a reduction of ICU capacities in the same dimension. Based on a examination of interrelations between parameters published in the DIVI registry it is concluded that a temporary reorganization of hospital care for SARS COV 2 positive patients would probably help to mitigate the risks coming with increasing infection rates.