Bicher, M., Rippinger, C., Schneckenreither, G., Weibrecht, N., Urach, C., Zechmeister, M., Brunmeir, D., Huf, W., & Popper, N. (2022). Model based estimation of the SARS-CoV-2 immunization level in austria and consequences for herd immunity effects. Scientific Reports, 12(1), Article 2872. https://doi.org/10.1038/s41598-022-06771-x
Several systemic factors indicate that worldwide herd immunity against COVID-19 will probably not be achieved in 2021. On the one hand, vaccination programs are limited by availability of doses and on the other hand, the number of people already infected is still too low to have a disease preventing impact and new emerging variants of the virus seem to partially neglect developed antibodies from previous infections. Nevertheless, by February 2021 after one year of observing high numbers of reported COVID-19 cases in most European countries, we might expect that the immunization level should have an impact on the spread of SARS-CoV-2. Here we present an approach for estimating the immunization of the Austrian population and discuss potential consequences on herd immunity effects. To estimate immunization we use a calibrated agent-based simulation model that reproduces the actual COVID-19 pandemic in Austria. From the resulting synthetic individual-based data we can extract the number of immunized persons. We then extrapolate the progression of the epidemic by varying the obtained level of immunization in simulations of an hypothetical uncontrolled epidemic wave indicating potential effects on the effective reproduction number. We compared our theoretical findings with results derived from a classic differential equation SIR-model. As of February 2021, [Formula: see text] of the Austrian population has been affected by a SARS-CoV-2 infection which causes a [Formula: see text] reduction of the effective reproduction number and a [Formula: see text] reduction of the prevalence peak compared to a fully susceptible population. This estimation is now recomputed on a regular basis to publish model based analysis of immunization level in Austria also including the fast growing effects of vaccination programs. This provides substantial information for decision makers to evaluate the necessity of non pharmaceutical intervention measures based on the estimated impact of natural and vaccinated immunization.
Mathematical and Algorithmic Foundations: 20% Computer Science Foundations: 20% Modeling and Simulation: 60%