| Autor: |
Ligui Wang, Mengxuan Lin, Jiaojiao Wang, Hui Chen, Mingjuan Yang, Shaofu Qiu, Tao Zheng, Zhenjun Li, Hongbin Song |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Infectious Disease Modelling, Vol 7, Iss 2, Pp 117-126 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2468-0427 |
| DOI: |
10.1016/j.idm.2022.04.003 |
| Popis: |
Numerous studies have proposed search engine-based estimation of COVID-19 prevalence during the COVID-19 pandemic; however, their estimation models do not consider the impact of various urban socioeconomic indicators (USIs). This study quantitatively analysed the impact of various USIs on search engine-based estimation of COVID-19 prevalence using 15 USIs (including total population, gross regional product (GRP), and population density) from 369 cities in China. The results suggested that 13 USIs affected either the correlation (SC-corr) or time lag (SC-lag) between search engine query volume and new COVID-19 cases (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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