Construction and validation of a COVID-19 pandemic trend forecast model based on Google Trends data for smell and taste loss

• 主要な著者: Jingguo Chen (著者), Hao Mi (著者), Jinyu Fu (著者), Haitian Zheng (著者), Hongyue Zhao (著者), Rui Yuan (著者), Hanwei Guo (著者), Kang Zhu (著者), Ya Zhang (著者), Hui Lyu (著者), Yitong Zhang (著者), Ningning She (著者), Xiaoyong Ren (著者)
• フォーマット: 図書
• 出版事項: Frontiers Media S.A., 2022-12-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.

AimTo explore the role of smell and taste changes in preventing and controlling the COVID-19 pandemic, we aimed to build a forecast model for trends in COVID-19 prediction based on Google Trends data for smell and taste loss.MethodsData on confirmed COVID-19 cases from 6 January 2020 to 26 December...