Table 2.

Summary of the reviewed methods and techniques

Method category	Method name	Study reference	Performance metric	Metric value
Graph data mining	Graph data Mining	[23]	Pearson correlation	r = 0.545
Text mining	Historical patterns	[45]	The precision for 1-day prediction is 0.8 (with mean of 0.52) and 0.6 (with mean of 0.46) for 7-days prediction.
	Co-occurrences	[44]
Topic models	ATAM	[46]	Pearson correlation	r = 0.934
	ATAM+	[47]	Pearson correlation	r = 0.958
	HFSTM	[48]	Mean square error (MSE)	MSE = 40.67
Machine learning	Neural network	[61]	ACC (Eq. 8)	ACC = 0.9532
	SVM	[57]	Pearson correlation	r = 0.93
		[56]	Pearson correlation	r = 0.89
		[59]	Pearson correlation	r = 0.89
		[58]
		[60]	Pearson correlation	r = 0.9897
		[55]
	Prediction Market using SVR	[64]
	Naive Bayes	[63]	Sentiment polarity is used to determine the accuracy of the used method (Naive Bayes polarity is 70%)
Math/Statistical based models	SNEFT	[67]	Pearson correlation	r = 0.9846
	ACF	[65]	Pearson correlation	r = 0.767
	Numerical-based analysis (SEHA using BOW)	[68]	RMSE	Avg (RMSE) = 1.1
Mechanistic disease models	Metpopulation model	[70]	Pearson correlation	r = 0.98
	Compartmental model	[35]
	Agent-based model	[73]
Keys/Documents filtration	Keys/Documents filtration	[74]