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Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm

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Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia
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Clinical Hospital Centre, Rijeka, Krešimirova ul. 42, 51000 Rijeka, Croatia
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Faculty of Engineering, University of Kragujevac, Sestre Janjić, 34000 Kragujevac, Serbia
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Bioengineering Research and Development Centre (BioIRC), Prvoslava Stojanovića 6, 34000 Kragujevac, Serbia
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Faculty of Medicine, University of Rijeka, Ul. Braće Branchetta 20/1, 51000, Rijeka, Croatia
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Faculty of Dental Medicine, University of Rijeka, Kresimirova 40/42, 51000 Rijeka, Croatia
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(3), 959; https://doi.org/10.3390/ijerph18030959
Received: 14 December 2020 / Revised: 19 January 2021 / Accepted: 20 January 2021 / Published: 22 January 2021
Estimation of the epidemiology curve for the COVID-19 pandemic can be a very computationally challenging task. Thus far, there have been some implementations of artificial intelligence (AI) methods applied to develop epidemiology curve for a specific country. However, most applied AI methods generated models that are almost impossible to translate into a mathematical equation. In this paper, the AI method called genetic programming (GP) algorithm is utilized to develop a symbolic expression (mathematical equation) which can be used for the estimation of the epidemiology curve for the entire U.S. with high accuracy. The GP algorithm is utilized on the publicly available dataset that contains the number of confirmed, deceased and recovered patients for each U.S. state to obtain the symbolic expression for the estimation of the number of the aforementioned patient groups. The dataset consists of the latitude and longitude of the central location for each state and the number of patients in each of the goal groups for each day in the period of 22 January 2020–3 December 2020. The obtained symbolic expressions for each state are summed up to obtain symbolic expressions for estimation of each of the patient groups (confirmed, deceased and recovered). These symbolic expressions are combined to obtain the symbolic expression for the estimation of the epidemiology curve for the entire U.S. The obtained symbolic expressions for the estimation of the number of confirmed, deceased and recovered patients for each state achieved R2 score in the ranges 0.9406–0.9992, 0.9404–0.9998 and 0.9797–0.99955, respectively. These equations are summed up to formulate symbolic expressions for the estimation of the number of confirmed, deceased and recovered patients for the entire U.S. with achieved R2 score of 0.9992, 0.9997 and 0.9996, respectively. Using these symbolic expressions, the equation for the estimation of the epidemiology curve for the entire U.S. is formulated which achieved R2 score of 0.9933. Investigation showed that GP algorithm can produce symbolic expressions for the estimation of the number of confirmed, recovered and deceased patients as well as the epidemiology curve not only for the states but for the entire U.S. with very high accuracy. View Full-Text
Keywords: artificial intelligence; COVID-19; epidemiology curve; genetic programming algorithm; regression modeling artificial intelligence; COVID-19; epidemiology curve; genetic programming algorithm; regression modeling
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MDPI and ACS Style

Anđelić, N.; Šegota, S.B.; Lorencin, I.; Jurilj, Z.; Šušteršič, T.; Blagojević, A.; Protić, A.; Ćabov, T.; Filipović, N.; Car, Z. Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm. Int. J. Environ. Res. Public Health 2021, 18, 959. https://doi.org/10.3390/ijerph18030959

AMA Style

Anđelić N, Šegota SB, Lorencin I, Jurilj Z, Šušteršič T, Blagojević A, Protić A, Ćabov T, Filipović N, Car Z. Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm. International Journal of Environmental Research and Public Health. 2021; 18(3):959. https://doi.org/10.3390/ijerph18030959

Chicago/Turabian Style

Anđelić, Nikola; Šegota, Sandi B.; Lorencin, Ivan; Jurilj, Zdravko; Šušteršič, Tijana; Blagojević, Anđela; Protić, Alen; Ćabov, Tomislav; Filipović, Nenad; Car, Zlatan. 2021. "Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm" Int. J. Environ. Res. Public Health 18, no. 3: 959. https://doi.org/10.3390/ijerph18030959

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