Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study
BackgroundGiven the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19’s disease dynamics seemed difficult to predict. External factors, such as internet search da...
Main Authors: | Atina Husnayain, Eunha Shim, Anis Fuad, Emily Chia-Yu Su |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2021-12-01
|
Series: | Journal of Medical Internet Research |
Online Access: | https://www.jmir.org/2021/12/e34178 |
Similar Items
-
Estimating the Risk of COVID-19 Death during the Course of the Outbreak in Korea, February–May 2020
by: Eunha Shim, et al.
Published: (2020-05-01) -
Optimal Allocation of the Limited COVID-19 Vaccine Supply in South Korea
by: Eunha Shim
Published: (2021-02-01) -
Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology Study
by: Jesus Trevino, et al.
Published: (2022-04-01) -
Measuring Public Concern About COVID-19 in Japanese Internet Users Through Search Queries: Infodemiological Study
by: Zhiwei Gao, et al.
Published: (2021-07-01) -
The Effects of Online Health Information–Seeking Behavior on Sexually Transmitted Disease in China: Infodemiology Study of the Internet Search Queries
by: Xuan Li, et al.
Published: (2023-05-01)