Journal
MATHEMATICS
Volume 9, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/math9060659
Keywords
COVID-19; Fourier fitting; curve fitting; optimization algorithm
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Funding
- RUDN University Strategic Academic Leadership Program: RUDN University Strategic Academic Leadership Program
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This paper models daily confirmed cases of COVID-19 in various countries using different mathematical regression models. Countries are classified into three categories based on virus spreading and average annual temperatures. Predictions of upcoming scenarios are compared with actual confirmed cases for validation.
In this paper, daily confirmed cases of COVID-19 in different countries are modelled using different mathematical regression models. The curve fitting is used as a prediction tool for modeling both past and upcoming coronavirus waves. According to virus spreading and average annual temperatures, countries under study are classified into three main categories. First category, the first wave of the coronavirus takes about two-year seasons (about 180 days) to complete a viral cycle. Second category, the first wave of the coronavirus takes about one-year season (about 90 days) to complete the first viral cycle with higher virus spreading rate. These countries take stopping periods with low virus spreading rate. Third category, countries that take the highest virus spreading rate and the viral cycle complete without stopping periods. Finally, predictions of different upcoming scenarios are made and compared with actual current smoothed daily confirmed cases in these countries.
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