Every pandemic affects life and actions of people, which in turn controls the course of the pandemic. Until now, the factors that determine our social, political, and psychological sphere could not be described by mathematical models, making it difficult to venture forecasts for the COVID-19 pandemic.
The new study will improve the situation. Researcher Professor Kai Wirtz of the Hereon Institution for Coastal Systems – Analysis and Modeling quantitatively describes the social phenomena hinted at above. ‘As a scientist, social modeling has been driving me for a while. It has also reached coastal research in the meantime. The greatest challenge in this development was integrating human agency into conventional epidemiological models,’ says Wirtz.
How COVID-19 changes people
Due to the problems in the predictability of social dynamics, Wirtz uses the uniqueness of the global COVID-19 pandemic for the new study. This comes along with unprecedented data availability, as he emphasizes. The study uses a part of these data sets – primarily presented by Apple, John Hopkins CSSE und YouGov – to quantitatively test a novel model based on the different pandemic course patterns in 20 affected regions. The regions include 11 EU countries such as Germany, Italy, Sweden, Iran, and eight states in the US.
Societies affected by the pandemic at the beginning of 2020, mostly Western industrialised countries, succeeded in curtailing infection rates through measures such as social distancing. After the societies began to lift the imposed lockdowns in May 2020, some of them achieved deficient case figures while others were affected by an enduring high mortality rate. Later during the fall and winter seasons of 2020–2021, all these regions were hit by a massive second and third wave despite their experiences made during the first lockdown.
The model of the study combines classic equations for viral spreading with simple rules for social dynamics. As a basis, it is assumed that societies act rationally to keep the cumulative damage resulting from COVID-19 caused mortality and the direct socio-economic cost of social distancing as low as possible. ‘However, the simulation results show that another mechanism is crucial to describe the dynamics in the 20 regions: the erosion of so-called social cohesion with a reduced willingness for and efficacy of social distancing,’ says Wirtz.
The simulation of this erosion process results in curves of regional mortality rates and mobility and behavioural changes that are almost identical to the empirical data. Thus, the study presents the first model, which increases forecasting from a few weeks to one year. In addition, the model can potentially be used to describe the impact of new SARS-CoV-2 mutants.
Based on this study, the regionally diverse second and third waves of the pandemic can be explained as the consequence of differences in social cohesion and climatological factors. The model calculations show that a zero COVID-19 strategy would have been possible in many countries in many countries in many countries in the summer of 2020. ‘But only if the social fatigue would have been halted and strict travel bans applied,’ says Kai Wirtz.
Due to the successful validation, the model can guide medium-term strategic planning, for example, more efficient vaccine distribution. At the beginning of 2021, the model predicted for Germany that each delayed day of the mass vaccination causes 178 further Corona deaths on average. With this piece of research, the human approach in dealing with the virus has become better predictable.