Analysis of the impact of the social justice index on the COVID-19 pandemic using artificial intelligence in EU and OECD countries

The COVID-19 disease has evolved into a pandemic that affects the world in multiple dimensions. While COVID-19 spread rapidly to several nations, distinct patterns of spread emerged in each nation. This spreading behavior is related to various characteristics of countries, including social, political, and economic factors. In this study, an analysis of the COVID-19 pandemic in EU and OECD countries was conducted, taking into account the social justice index for the first time. The impact and significance of the social justice index on the COVID-19 analysis results were attempted to be revealed. As a result, it is understood that the countries with high Social Justice Index scores and sub-dimension scores are more successful in combating the COVID-19 pandemic. In addition, a new LSTM-based model was developed to predict the number of cases and deaths in these countries. The designed LSTM approach was compared with some well-known deep learning and machine learning algorithms. As a result of the experimental studies, the LSTM model obtained the best prediction results. Finally, the similarities between these countries in terms of the characteristics of the COVID-19 pandemic, including death and case spread, were analyzed, and exciting results were disclosed.