Coronavirus disease-19 (Covid-19) had an unprecedented effect on both nations and health systems. Time series modeling using Auto-Regressive Integrated Moving Averages (ARIMA) models have been used to forecast variables extensively mainly in statistics and econometrics. The investigators aimed to predict the total number of cases for Covid-19 using ARIMA models of time-series analysis.

Coronavirus Disease 19 (Covid-19) is an infectious disease initially defined in December 2019 before becoming pandemic. Respiratory disease is the main form of disease causing acute respiratory distress as the main cause of death.

Increased number of cases worldwide had put an enormous load on public health resulting lockdowns, quarantines and curfews. Predicting number of cases is hard as the increment of cases between communities differ.

Time series had been used in different fields of science to predict, such as signal processing, mathematical finance, weather prediction. In medicine, time series analysis were used in number of admitted patients to hospitals. Aim of this study is to predict the total number of Covid-19 cases worldwide using time series anaylsis.

Inclusion Criteria:

• Confirmed case of Covid-19

Exclusion Criteria:

• Cases not reported

Population consists all confirmed cases of Covid-19 reported from Situation Dashboard of the European Center for Disease Prevention and Control website Coronavirus 19 Situation Report