Time Series Model For Forecasting the Number of Covid-19 Cases Worldwide - A Prospective Cohort Study
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 7,882,471
- 试验地点
- 1
- 主要终点
- Number of Confirmed cases of Covid-19
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Confirmed case of Covid-19
排除标准
- •Cases not reported
结局指标
主要结局
Number of Confirmed cases of Covid-19
时间窗: December 31, 2019 to June 15, 2020
次要结局
未报告次要终点
研究者
Serhat Akay
Principal Investigator
Turkish Ministry of Health Izmir Teaching Hospital