期刊
JOURNAL OF MEDICAL VIROLOGY
卷 93, 期 10, 页码 5896-5907出版社
WILEY
DOI: 10.1002/jmv.27143
关键词
COVID-19 pandemic; machine learning; prediction model
类别
资金
- China Pharmaceutical University [3150120001]
This study predicted the development trend of the second wave of COVID-19 in five European countries, including peak times and numbers of cases and deaths. The results showed that the second wave of COVID-19 is expected to have more cases and deaths, last longer, but with a lower mortality rate.
The second wave of COVID-19 has caused a dramatic increase in COVID-19 cases and deaths globally. An accurate prediction of its development trend is significant. We predicted the development trend of the second wave of COVID-19 in five European countries, including France, Germany, Italy, Spain, and the UK. We first built models to predict daily numbers of COVID-19 cases and deaths based on the data of the first wave of COVID-19 in these countries. Based on these models, we built new models to predict the development trend of the second wave of COVID-19. We predicted that the second wave of COVID-19 would have peaked around on November 16, 2020, January 10, 2021, December 1, 2020, March 1, 2021, and January 10, 2021, in France, Germany, Italy, Spain, and the UK, respectively. It will be basically under control on April 26, 2021, September 20, 2021, August 1, 2021, September 15, 2021, and August 10, 2021, in these countries, respectively. Their total number of COVID-19 cases will reach around 4,745,000, 7,890,000, 6,852,000, 8,071,000, and 10,198,000, respectively, and total number of COVID-19 deaths will be around 262,000, 262,000, 231,000, 253,000, and 350,000 during the second wave of COVID-19. The COVID-19 mortality rate in the second wave of COVID-19 is predicted to be about 3.4%, 3.5%, 3.4%, 3.4%, and 3.1% in France, Spain, Germany, France, and the UK. The second wave of COVID-19 is expected to cause many more cases and deaths, last for a much longer time, and have a lower COVID-19 mortality rate than the first wave.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据