WSEAS Transactions on Environment and Development
Print ISSN: 1790-5079, E-ISSN: 2224-3496
Volume 18, 2022
Predicting the Dynamics of Covid-19 Propagation in Azerbaijan based on Time Series Models
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Abstract: The study is dedicated to developing an econometric model that can be used to make medium-term forecasts about the dynamics of the spread of the coronavirus in different countries, including Azerbaijan. We examine the number of COVID-19 cases and deaths worldwide to understand the data's intricacies better and make reliable predictions. Though it’s essential to quickly obtain an acceptable (although not perfect) prediction that shows the critical trends based on incomplete and inaccurate data, it is practically impossible to use standard SIR models of the epidemic spread. At the same time the similarity of the dynamics in different countries, including those which were several weeks ahead of Azerbaijan in the epidemic situation, and the possibility of including the heterogeneity factors into the model allowed as early as March 2020 to develop the extrapolation working relatively well on the medium-term horizon. The SARS-CoV-2 virus, which causes COVID-19, has affected societies worldwide, but the experiences have been vastly different. Countries' health-care and economic systems differ significantly, making policy responses such as testing, intermittent lockdowns, quarantine, contact tracing, mask-wearing, and social distancing. The study presented in this paper is based on the Exponential Growth Model method, which is used in statistical analysis, forecasting, and decision-making in public health and epidemiology. This model was created to forecast coronavirus spread dynamics under uncertainty over the medium term. The model predicts future values of the percentage increase in new cases for 1–2 months. Data from previous periods in the United States, Italy, Spain, France, Germany, and Azerbaijan were used. The simulation results confirmed that the proposed approach could be used to create medium-term forecasts of coronavirus spread dynamics. The main finding of this study is that using the proposed approach for Azerbaijan, the deviation of the predicted total number of confirmed cases from the actual number was within 3-10 percent. Based on March statistics on the spread of the coronavirus in the US, 4 European countries: Italy, Spain, France, Germany (most susceptible to the epidemic), and Azerbaijan, it was shown how the trajectory would deviate exponentially from a shape; a trial was carried out to identify and assess the key factors that characterize countries. One of the unexpected results was the impact of quarantine restrictions on the number of people infected. We also used the medium-term forecast set by the local government to assess the adequacy of health systems.
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Keywords: Coronavirus, epidemic spread, regression models, time series analysis, exponential growth model, prediction, applied econometrics
Pages: 1036-1048
DOI: 10.37394/232015.2022.18.99