Modelling of Regional Economic Management in Conditions of Mass Diseases
DOI:
https://doi.org/10.17059/ekon.reg.2023-2-1Keywords:
regional economy, mathematical model, economic dynamics model, pandemic, mass disease, COVID-19, regional management strategy, simulation, numerical analysis, assessment of management decisionsAbstract
Economic globalisation, logistics intensification, world population growth and increasing mobility lead to the emergence of mass diseases, determining the behaviour of various economic agents. The article offers a new tool for analysing regional economic management in conditions of mass diseases, which combines both socio-biological and economic factors in one economic and mathematical model. The proposed model is based on the description of disease dynamics among various population groups (SIR or SIER compartmental models) and corresponding socio-economic changes. Investments in the improvement of hospital beds, in the construction of new hospitals, and in information campaigns to combat the disease are considered as control actions on the economic system. Thus, the regional management system can apply this tool to quantify and compare possible management decisions, taking into account the mutual influence of biological and socio-economic factors. Mathematical models in population biology and epidemiology were analysed in order to construct the tool and assess its parameters by the methods of regression correlation analysis, simulation modelling, and numerical analysis of the differential equation system. In particular, statistical information on the COVID-19 pandemic in Russia and Ulyanovsk oblast for 2020 was examined during the research. The developed software package was utilised to model the presence or absence of restrictive measures during the reviewed period; then, a comparative analysis of these strategies was conducted. The described tool can be adapted to assess the management strategies of various economic agents. It can be further supplemented with quality criteria and appropriate algorithms for selecting optimal strategies to manage regional economy in conditions of mass diseases.
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