Germany’s current COVID-19 crisis is mainly driven by the unvaccinated

Abstract

Vaccines are the most powerful pharmaceutical tool to combat the COVID-19 pandemic. While the majority (about 65%) of the German population were fully vaccinated, incidence started growing exponentially in October 2021 with about 41% of recorded new cases aged twelve or above being symptomatic breakthrough infections, presumably also contributing to the dynamics. At the time, it (i) remains elusive how significant this contribution is and (ii) whether targeted non-pharmaceutical interventions (NPIs) may stop the amplification of the ongoing crisis. Here, we estimate that about 67%–76% of all new infections are caused by unvaccinated individuals, implying that only 24%–33% are caused by the vaccinated. Furthermore, we estimate 38%–51% of new infections to be caused by unvaccinated individuals infecting other unvaccinated individuals. In total, unvaccinated individuals are expected to be involved in 8–9 of 10 new infections. We further show that decreasing the transmissibility of the unvaccinated by, e. g. targeted NPIs, causes a steeper decrease in the effective reproduction number ℛ than decreasing the transmissibility of vaccinated individuals, potentially leading to temporary epidemic control. Furthermore, reducing contacts between vaccinated and unvaccinated individuals serves to decrease ℛ in a similar manner as increasing vaccine uptake. Taken together, our results contribute to the public discourse regarding policy changes in pandemic response and highlight the importance of combined measures, such as vaccination campaigns and contact reduction, to achieve epidemic control and preventing an overload of public health systems.

Neural parameter calibration for large-scale multiagent models

“…A line of great current interest in the mathematical sciences is to calibrate parameters of mathematical models using data, thereby creating computationally efficient, theoretically grounded, and socially beneficial predictive tools. For instance, models of the spread of contagion continue to inform much government policy during the ongoing COVID-19 pandemic ( 1 – 5 ): predictions are generated, subsequently compared to live data, and the underlying model revised accordingly. Computational models have also been used to understand the dynamics of crime and urban violence ( 6 , 7 ), pedestrian dynamics ( 8 ), synchronized oscillations ( 9 ), social network dynamics ( 10 – 12 ), chemotaxis and flocking ( 13 – 15 ), population dynamics ( 16 , 17 ), systemic risk ( 18 ), and the dynamics of economic systems ( 19 , 20 ).…”

Strategietreffen: Virushepatitis in Deutschland eliminieren – Was ist zu tun?

“…Diese wird seit 1995 durch die ständige Impfkommission (STIKO) für Säuglinge und Kleinkinder empfohlen, nicht zuletzt, da eine Infektion in diesem Alter mit einer hohen Chronifizierungsrate assoziiert ist. Leider belief sich die Inanspruchnahme der Impfung im Jahre 2019 zum Zeitpunkt der Schuleingangsuntersuchung mit großen Schwankungen zwischen den Bundesländern zwischen 78,9 % und 94,5 % 21 . Eine Förderung von Impfkampagnen sowie Aufklärungsarbeit können hier die Impfbereitschaft erhöhen.…”

Is vaccination against COVID-19 a Christian duty? A risk-analytic approach

“…26 The reason is-most likely-that while the peak viral load between vaccinated and non-vaccinated might be similar, the overall viral load of vaccinated is lower as vaccinated people clear the virus more quickly, i.e., "within days of infection, the viral load in vaccinated people drops much more rapidly and therefore makes them much less likely to transmit [COVID-19]." 27 Consequently, Maier et al found that "67%-76% of all new infections are caused by unvaccinated individuals" in Germany (autumn 2021,) 28 although merely some 30 % of the population were unvaccinated. Thus, we can conclude that vaccination reduces the risk of infecting others, i.e., 0 < Pinf/V < Pinf/𝑉𝑉 � .…”