ABSTRACT
Globally, there is massive uptake and explosion of data, and the challenge is to address issues like scale, pace, velocity, variety, volume, and complexity of this big data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This chapter presents medical perspective of COVID-19 toward epidemiological triad and the study of state of the art. The main aim of this chapter is to present different predictive analytics techniques available for trend analysis, different models and algorithms, and their comparison. Finally, this chapter concludes with the prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time. © 2020, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.