Effects of quarantine disobedience and mobility restrictions on COVID-19 pandemic waves in dynamical networks

Dorian Stipic; Mislav Bradac; Tomislav Lipic; Boris Podobnik

doi:10.1016/j.chaos.2021.111200

Effects of quarantine disobedience and mobility restrictions on COVID-19 pandemic waves in dynamical networks

Chaos Solitons Fractals. 2021 Sep:150:111200. doi: 10.1016/j.chaos.2021.111200. Epub 2021 Jun 23.

Authors

Dorian Stipic^{1

2}, Mislav Bradac¹, Tomislav Lipic³, Boris Podobnik^{2

4

5

6}

Affiliations

¹ University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.
² Zagreb School of Economics and Management, Zagreb, Croatia.
³ Laboratory for Machine Learning and Knowledge Representations, Rudjer Boskovic Institute, Zagreb, Croatia.
⁴ Luxembourg School of Business, Luxembourg, EU.
⁵ University of Rijeka, Faculty of Civil Engineering, Rijeka 51000, Croatia.
⁶ Faculty of Information Studies in Novo Mesto, Novo Mesto 8000, Slovenia, EU.

Abstract

For the global COVID-19 pandemic it is still not adequately understood how quarantine disobedience and change in mobility restrictions influence the pandemic spreading and waves. Here, we propose a new metapopulation epidemiological model as a network composed of equal clusters to predict the course of the epidemic based on the contiguous spreading between the neighbours, the probability of quarantine misbehaviour, and the probability of mobility, which control contacts outside the cluster. We exemplify the model by comparing simulation results with real data on COVID-19 pandemic in Croatia. Fitting the data over the first and second pandemic waves, when the probability of mobility is set by the stringency index, the probability of quarantine misbehaviour is found by a Bayesian optimization yielding a fascinating agreement between the daily COVID-19 deaths and model output and efficiently predicting the timing of pandemic bursts. A sudden increase in the probability of quarantine misbehaviour alongside the sudden increase in the probability of mobility generate the model third wave in good agreement with daily COVID-19 deaths.

Keywords: Bayesian optimisation; COVID-19; Data science; Modeling; Network theory; Pandemics.