Time Series Model For Forecasting the Number of Covid-19 Cases Worldwide - A Prospective Cohort Study
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Covid-19
- Sponsor
- Turkish Ministry of Health Izmir Teaching Hospital
- Enrollment
- 7882471
- Locations
- 1
- Primary Endpoint
- Number of Confirmed cases of Covid-19
- Status
- Completed
- Last Updated
- 5 years ago
Overview
Brief Summary
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.
Detailed Description
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.
Investigators
Serhat Akay
Principal Investigator
Turkish Ministry of Health Izmir Teaching Hospital
Eligibility Criteria
Inclusion Criteria
- •Confirmed case of Covid-19
Exclusion Criteria
- •Cases not reported
Outcomes
Primary Outcomes
Number of Confirmed cases of Covid-19
Time Frame: December 31, 2019 to June 15, 2020