Study: Partial ban for unvaccinated people promises the breakthrough of the fourth wave of COVID-19 in Bavaria. Image source: Lightspring / Shutterstock
However, despite the availability of vaccines, a considerable part of the German population was not ready to be vaccinated. These unvaccinated people are at higher risk of developing serious illnesses, which is why protecting against infection has become a priority of public health strategy.
Computer simulations have been used by epidemiologists since the beginning of the pandemic to meet the requirements of decision-makers for the scientific evaluation of political options and also to forecast the development of the pandemic. It turned out that agent-based models can depict the complexity of the pandemic in some detail.
A new study published on the pre-print server medRxiv * used an agent-based epidemiological simulator, Covasim, to determine the historical course of COVID-19 in Bavaria and to analyze the effectiveness of the partial lockdown on the unvaccinated population.
About the study
As part of the study, a synthetic population was created that statistically corresponds to the real population of Germany in terms of essential aspects such as household composition or age structure. Since simulations for the entire population of Bavaria would take a long time, the researchers decided to scale from a reduced sample.
Therefore simulations were carried out with 71,000 agents and all absolute numbers were scaled by a factor of 185. Contact networks between agents were established for four typical environments, which included school, home, work and leisure. The simulations calculated the likelihood of virus transmission from one agent to another with existing contacts.
In addition, non-pharmaceutical (public health) and pharmaceutical (vaccinations) interventions that were used in Bavaria were integrated into the Covasim simulator and modeled quantitatively. Several aspects were taken into account in the model, including the base probability of transmission, the transition from the wild variant of COVID-19 to the alpha and delta variants was continuously modeled, the contact tracing by health authorities was modeled, work from home in addition to travel during the summer vacation the arrangement was simulated, the number of future vaccinations was assumed and additional partial blocking measures were simulated, which affected different areas of life of the unvaccinated persons.
The free parameters of the model were set in such a way that the simulated curves, which provided real data for the seven-day incidence and the critical cases from 02/01/2020 to 11/24/2021, agreed well. Finally, the calibrated model of the pandemic was used as a starting point for simulating future lockdown scenarios.
Study results
The results of the study showed that the simulation was able to capture the first three waves of COVID-19 along with the start of the fourth wave. The model projects that, without intervention, a 7-day incidence of almost 1,000 in the penultimate week of 2021 and a need for more than 2,600 intensive care units in January 2021 can take place in Bavaria. However, the simulations also show that interventions from December 2021 can effectively mitigate the fourth wave.
Working from home and restricting recreational contacts of unvaccinated people were found to be beneficial in preventing the transmission of infection, while excluding unvaccinated students from teaching in schools was found to be the least effective. No additional vaccination restrictions are required for third wave attenuation.
However, it can be observed that even without further intervention, the number of infections and critical cases declines before the turn of the year. This may be due to the increasing coverage of the population through vaccinations and infections. It can therefore be concluded that population immunization is progressing towards herd immunity, reducing the likelihood of infection.
limitations
The study had certain limitations. Initially, only data from Bavaria or Germany were taken into account. Second, data on the actual implementation of public health orders have been limited. Third, the study made several assumptions that could have some impact on the simulations. Finally, based on actual human behavior, the study is considered unsafe.
*Important NOTE
medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, that guide clinical practice / health-related behavior or are treated as established information.