Predictions of COVID-19 Spread by Using Supervised Data Mining Techniques

Abstract

In the wake of the outbreak of the new coronavirus, the countries in the world have fought to combat the spread of infection and imposed preventive measures to compel the population to social distancing, which led to a global crisis. Important strategies must be studied and identified to prevent and control the spread of coronavirus COVID-19 disease 2019. In this paper, the effect of preventive strategies on COVID-19 spread was studied, a model based on supervised data mining algorithms was presented and the best algorithm was suggested on the basis of accuracy. In this model, three classifiers (Naive Bayes, Multilayer Perceptron and J48) depended on the questionnaires filled out by Basra City respondents. The questionnaires consisted of 25 questions that covered fields most related to and that affect the prevention of COVID-19 spread, including demographic, psychological, health management, cognitive, awareness and preventive factors. A total of 1017 respondents were collected. This model was developed using Weka 3.8 tool. Results showed that quarantine played an important role in controlling the spread of the disease. By comparing the accuracy of the algorithms used, the best algorithm was found to be J48.

Assessment of SQL and NoSQL Systems to Store and Mine COVID-19 Data

“…Different Data Mining algorithms have been used regarding different COVID-19 data prediction models. In the studies [5,[22][23][24] Decision Trees were the best algorithm in the prediction models with accuracies of 99.85%, 94.99%, 98.7%, and 99.98%, respectively. In [6,[25][26][27], different algorithms such as K-Nearest Neighbor, Logistic Regression, Bayesian Network, and Random Forest proved to be the best in prediction models with accuracies of 98%, 87%, 89.31%, and 90.83%, respectively.…”

“…worldwide. As a result, multiple papers have been published regarding this issue [5,6,[22][23][24][25][26][27]. In addition, a significant amount of research has been put forward using artificial intelligence on COVID-19 data.…”

“…Orange Data Mining provides a vast Data Mining algorithm's range. Naïve Bayes, Decision Tree, Random Forest, and Logistic Regression were used in this study as state-ofthe-art [5,6,[22][23][24][25][26][27]. The following subsections briefly describe each of these algorithms.…”

Improved autoregressive integrated moving average model for COVID-19 prediction by using statistical significance and clustering techniques

“…Multilayer perceptron, naive Bayes, and J48 were used in Ref. [ 27 ] to categorize responses to questionnaires distributed to Basra city residents. The effectiveness of COVID-19 preventive tactics was examined, and the most precise method was determined.…”

Hybrid information security system via combination of compression, cryptography, and image steganography

“…There are various lossy compression methods like transform coding [18], discrete cosine transform (DCT) [19], discrete wavelet transforms (DWT) [20], chroma subsampling [21], fractals lossless compression is generally used for medical imaging, drawings, comics. There are various methods for lossless compression like run-length coding, predictive coding, entropy coding, Huffman coding, Lempel Ziv Welch (LZW) [16], [22], [23]. So, DWT technique is applied for image compression.…”