PROGNOSIS

The COVID-19 pandemic has shown that healthcare capacities can be overburdened even in highly developed countries, leading not only to inadequate care for COVID-19 patients, but also having an impact on the efficiency of the healthcare system as a whole, such as reduced prevention and screening programs and delayed surgeries. In the PROGNOSIS consortium, partners from five institutions with complementary expertise in biostatistics, bioinformatics, epidemiology, health research, infectious diseases and economics have joined forces to tackle this pressing problem with a principled and holistic approach. Data-driven short-term and mechanistic long-term prediction models of the hospital burden at different levels of care (standard, intensive care, ventilation, extracorporeal membrane oxygenation / ECMO) for three important respiratory infections: COVID-19, influenza and pneumococcal pneumonia. Different episodes of the epidemic and different geographical levels (Germany, federal states, districts) are also considered in order to enable local predictions. The models are parameterized with the help of extensive and constantly growing data sets from the ongoing collaboration with several German institutions and competence networks. Based on this, the impact on hospitals’ supply chains and human resources will also be modeled to derive concrete short-term countermeasures to cope with the expected burden on hospitals and to assess the effectiveness of long-term measures such as vaccination programs and non-pharmaceutical interventions. The modeling approach is structured in such a way that it is transferable to other pan- and epidemic situations.