Using System Dynamics approach as decision support tool in fighting against pandemic

  • Tomasz Zawadzki ,
  • Halina Świeboda,
  • Tomasz Wałęcki
  • a,b,c War Studies University, Aleja Generała Antoniego Chruściela „Montera” 103, Warsaw, 00-910, Poland
Cite as
Zawadzki T, Świeboda H., Wałęcki T. (2021). Using System Dynamics approach as decision support tool in fighting against pandemic. Proceedings of the 11th International Defence and Homeland Security Simulation Worskhop (DHSS 2021), pp. 48-53. DOI:
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The COVID-19 outbreak hit all countries and all mankind with unexpected initial force. This forced decision-makers at all levels, both among the rulers and managers of the private sector, to make decisions that had been atypical so far. As a last resort, in order to minimize the number of cases and ultimately the number of victims, the rulers were forced to introduce further lockdowns. Unfortunately, such activities have severely limited economic activity,
contributing to the economic slowdown. Thus, the rulers are forced to make difficult decisions on how much to protect health and how much to protect the economy. In this paper, using the method of systems dynamics and epidemic development models, we present how to predict its course and how to support decision-makers in assessing the current and future situation. The paper describes how to use well known epidemic spread model called SIR (Susceptible-Infected-Recovered) together with System Dynamics methodology and simulation tool JOptisim. The methodology that was choosen, allows modelers to easily extend basic SIR model by new variables depending on modeler needs. In presented example the cost of hospitalization was the variable which was added to the basic model. Using the proprietary JOptisim tool, which has implemented RADU5 numerical procedure, allows authors to validate developed model and achieve accurate simulation results. The paper consists of three sections. The first one is the general introduction to possibilities of predicting epidemic spread and the second one describes briefly the System Dynamics methodology. In the last section it is explained how to choose equations for some of the variables of the model using nonlinear regression methods implemented in R language when real data is available.


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