COVID-19 Outbreak: Application of Multi-gene Genetic Programming to Country-based Prediction Models

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is a novel coronavirus that has infected more than 2,900,000 individuals worldwide. The widespread of coronavirus 2019 (COVID-19) brings about the need for a prediction model to adopt appropriate evidence-based strategies. In this study, multi-gene genetic programming (MGGP), as one of the artificial intelligence models, has been proposed for the first time for predicting the COVID-19 outbreak. Although this is a challenging task due to significant fluctuations of daily confirmed cases, the results achieved by MGGP are promising. To be more specific, the predicted confirmed cases are acceptably close to the observed values for seven countries considered in this study. Thus, MGGP is suggested for developing estimation models of COVID-19. Furthermore, similarities and differences between the proposed prediction models are presented. Finally, it is discussed why a country-based prediction model is recommended.

Application of artificial neural networks to predict the COVID-19 outbreak

“…Therefore, an investigation similar to the one conducted in this study is suggested in favor of finding the best ANN-based model for a specific country, while the 14th model is found to be adequate in the absence of such analysis. The need for the quest for a country-based prediction model is in agreement with the previous studies [ 5 , 13 ].…”

“…Despite numerous advantages of prediction models, they have inevitable limitations. Since these predictions are based on the reported data, they underestimate the confirmed cases either due to the neglecting asymptomatic patients or limited sources of case findings in some countries [ 13 ]. Moreover, developing an ANN-based prediction model, which considers previous fourteen days, reduces fourteen-day records from ANN train data.…”

“…However, the longer a country has experienced COVID-19, the more number of data is available for the country. This obviously provides more data to train AI models, such as ANN, which may yield to more accurate prediction results [ 13 ].…”

“…Fu et al [ 12 ] utilized a Boltzmann function-based approach for estimation of cumulative confirmed cases in China [ 12 ]. Niazkar and Niazkar [ 13 ] exploited multi-gen genetic programming, which is one of AI models, to develop mathematical models with the exponential function for predicting the COVID-19 pandemic in seven countries including China, Republic of Korea, Japan, Italy, Singapore, Iran and United States of America. They suggested country-based prediction models.…”

Applications of artificial intelligence in battling against covid-19: A literature review

“…In [495] , a genetic algorithm is used with a cross-validation method to generate a model of the epidemic in Algeria. A multi-gene genetic programming algorithm is proposed in [496] , as a model to predict covid-19 outbreak. In [497] , a combination of virus optimization algorithm with ANFIS is proposed to investigate the effect of various climate-related factors and population density on the spread of the virus.…”