Study: Partial lockdown on unvaccinated individuals promises breaking of fourth COVID-19 wave in Bavaria. Image Credit: Lightspring/Shutterstock
However, a considerable fraction of the German population was unwilling to get vaccinated despite the availability of the vaccines. These unvaccinated individuals are at a higher risk of developing serious disease, protecting them from infection has therefore become a priority of the public health strategy.
Computer simulations have been used by epidemiologists since the beginning of the pandemic to meet the demands of decision-makers for the scientific assessment of political options and also to forecast the development of the pandemic. Agent-based models were found to be able to represent the complexity of the pandemic in some detail.
A new study published in 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 partial lockdown on the unvaccinated population.
About the study
The study involved the creation of a synthetic population that statistically matched the real population of Germany concerning 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 up from a reduced sample.
Simulations were therefore carried out with 71,000 agents and all the absolute numbers were scaled by a factor of 185. Contact networks were set between agents for four typical environments that included school, home, work, and free time. The simulations calculated the probability of viral transmission from one agent to another given existing contacts.
Furthermore, non-pharmaceutical (public health) and pharmaceutical (vaccinations) interventions that were applied in Bavaria were integrated into the Covasim simulator and quantitatively modeled. Several aspects were accounted for in the model a few of which are base transmission probability was modeled, the crossover from the wild variant of COVID-19 to alpha and delta variants were modeled continuously, contact tracing by public health departments was modeled, working from home arrangement was simulated along with travel during summer vacations, the number of future vaccinations was assumed, and additional partial lockdown measures were simulated that affected different areas of the life of the unvaccinated people.
The free parameters of the model were fixed in such a way that the simulated curves that provided real data of the seven-day incidence and the critical cases from February 01, 2020, to November 24, 2021, matched well. Finally, the calibrated model of the pandemic was used as a starting point for simulating the future lockdown scenarios.
Study findings
The results of the study indicated that the simulation was able to capture the first three waves of COVID-19 along with the beginning of the fourth wave. The model projects that in absence of any intervention, a 7-day incidence of just under 1,000 in the second last week of 2021 along with a requirement of more than 2,600 intensive care units during January 2021 in Bavaria can take place. However, the simulations also show that interventions starting from December 2021 can mitigate the fourth wave effectively.
Working from home and restricting leisure contacts of unvaccinated people was found to be beneficial in preventing transmission of infection while the exclusion of unvaccinated students from classes in schools was found to be least effective. No additional restrictions are required to be imposed on vaccinated individuals for the mitigation of the third wave.
However, it is observed that even without further interventions the number of infections and critical cases decreases before the turn of the year. This can be due to the ever-increasing immunization of the population through vaccination as well as infection. Therefore, it can be concluded that the population’s immunization is progressing towards herd immunity which will make the infections less probable.
Limitations
The study had certain limitations. First, data from only Bavaria or Germany have been included. Second, data on the actual implementation of public health orders was limited. Third, the study involved several assumptions which might have some influence on the simulations. Finally, the study is considered uncertain due to actual human behavior.
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