The epidemic spread model of infectious diseases is a traditional epidemiological and mathematical problem with crucial practical value. The first transmission of coronavirus to humans started in Wuhan city of China and took the shape of a pandemic called Corona Virus Disease 2019 (COVID-19). Many papers and studies have been written from 2019 until today. The aim of this paper is to present and short-analyse hybrid AI techniques which have been applied: k-nearest neighbours algorithm, Support Vector Machine, Naive Bayes, Random Forest, k-means clustering, hierarchical clustering, fuzzy logic, Logistic Regression, Decision Tree, Artificial Neural Networks, Deep Learning, Convolutional Neural Network to extract significant features and classify various health conditions, detection and diagnoses of COVID-19 patients. The hybrid algorithm overcomes the lack of exploiting individual AI techniques and algorithms; and simultaneously, the obtained statistical results prove the efficiency and robustness compared over other state-of-the-art approaches.