Simulation of non-pharmaceutical interventions in an agent based epidemic model Petra Vidnerová 1,9 , Roman Neruda 1,9 , Gabriela Suchopárová 1,9 , Ludˇ ek Berec 3,9 , Tomáš Diviák 4,9 , Aleš Kubˇ ena 2,9 , René Levínský 5,9 , Josef Šlerka 6,9 , Martin Šmíd 2,9 , Jan Trnka 7,9 , Vít Tuˇ cek 8,9 , Karel Vrbenský 2,9 , and Milan Zajíˇ cek 2,9 1 The Czech Academy of Sciences, Institute of Computer Science petra@cs.cas.cz 2 The Czech Academy of Sciences, Institute of Information Theory and Automation 3 Institute of Mathematics, Faculty of Science, University of South Bohemia and The Czech Academy of Sciences, Biology Centre, Institute of Entomology 4 Department of Criminology and Mitchell Centre for Social Network Analysis, School of Social Sciences, University of Manchester 5 CERGE-EI 6 New Media Studies, Faculty of Arts, Charles University 7 Department of Biochemistry, Cell and Molecular Biology, Third Faculty of Medicine, Charles University 8 Department of Mathematics, University of Zagreb 9 Centre for Modelling of Biological and Social Processes WWW home page: http://bisop.eu Abstract: The standard SEIR equation-based models rep- resent the state-of-the-art approach in epidemiological modelling. Their drawbacks include unrealistic infection- related contact estimates and difficulties in modelling non- pharmaceutical interventions, such as contact reductions or partial closures. In this paper, we present our agent-based model that ad- dresses the above-mentioned issues. It works with a pop- ulation of individuals (agents) and their contacts are mod- elled as a multi-graph social network according to real data based on a Czech county. Custom algorithmic procedures simulating testing, quarantine and partial closures of vari- ous contact types are implemented. The model can serve as a tool for relative comparison of the efficacy of various policies. It was also used for a study comparing various interventions in Czech primary and secondary schools, using a graph based on real data from a selected Czech school. 1 Introduction Mathematical models play an important role in a variety of scientific fields, including epidemiology. Mathematical modelling has been an integral part of epidemiology for more than 100 years. Epidemiological models serve many different purposes, namely as a tool for hypothesis verifi- cation, explanation of observed data, understanding basic principles of infectious dynamics, prediction of the future development and understanding the current one, calcula- tion of fundamental epidemiological metrics. During the current world-wide pandemic the interest in epidemiological modelling significantly increased not only in the scientific community, but also in the general public. The ability to model and predict the development of the epidemic became important from day to day. There exists a variety of epidemic models, including well established S(E)IR models[14, 5]. Our focus is on modelling the impact of non-pharmaceutical interventions. The non-pharmaceutical interventions and epidemiologi- cal measures influence the development of the epidemic significantly. Therefore, a proper epidemic model should reflect these interventions and must be able to model them and their impact on epidemic. Such a model may then be- come an important tool in choosing most efficient policies. In this paper we present our agent based model that was designed for the purpose of comparing various interven- tions, measures and policies. We focus on the simulation of non-pharmaceutical interventions, such as partial clo- sures, contact restrictions and quarantines. More details on the model itself can be found in our preprint [6]. The interventions we simulate cover protective mea- sures and contact restrictions. By protective measures we understand masks, stronger hygiene, and general cau- tiousness. Protective measures decrease the probability of transmission of the disease when the infectious contact happens. On the other hand, the contact restrictions de- crease the probability that such contacts are realised. Con- tact restrictions can be either flat, i. e. whole public places are closed (school closures, shop closures, etc.), or indi- vidual. Individual contact restrictions cover isolation or quarantine of single individuals. The effective contact re- striction on individual level requires to actively search for individuals that were in contact with infectious ones. This process is known as contact tracing. All mentioned interventions play an important role in the epidemic and the model should be able to reflect them. Some of the available epidemiological models posses mechanisms for modelling some of the mentioned inter- ventions including contact tracing [17, 13, 12, 11, 8]. The paper is organised as follows. In the next section we briefly explain the framework of our model and its main properties. In Section 3 the principles of simulation of individual interventions are described. Section 4 brings discussion of the usage of the model, its capabilities and _____________________ Copyright ©2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).