Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index
Abstract Background New coronavirus disease 2019 (COVID-19) has posed a severe threat to human life and caused a global pandemic. The current research aimed to explore whether the search-engine query patterns could serve as a potential tool for monitoring the outbreak of COVID-19. Methods We collect...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-01-01
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| Series: | BMC Infectious Diseases |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12879-020-05740-x |
| _version_ | 1831693504904953856 |
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| author | Bizhi Tu Laifu Wei Yaya Jia Jun Qian |
| author_facet | Bizhi Tu Laifu Wei Yaya Jia Jun Qian |
| author_sort | Bizhi Tu |
| collection | DOAJ |
| description | Abstract Background New coronavirus disease 2019 (COVID-19) has posed a severe threat to human life and caused a global pandemic. The current research aimed to explore whether the search-engine query patterns could serve as a potential tool for monitoring the outbreak of COVID-19. Methods We collected the number of COVID-19 confirmed cases between January 11, 2020, and April 22, 2020, from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). The search index values of the most common symptoms of COVID-19 (e.g., fever, cough, fatigue) were retrieved from the Baidu Index. Spearman’s correlation analysis was used to analyze the association between the Baidu index values for each COVID-19-related symptom and the number of confirmed cases. Regional distributions among 34 provinces/ regions in China were also analyzed. Results Daily growth of confirmed cases and Baidu index values for each COVID-19-related symptom presented robust positive correlations during the outbreak (fever: r s=0.705, p=9.623× 10− 6; cough: r s=0.592, p=4.485× 10− 4; fatigue: r s=0.629, p=1.494× 10− 4; sputum production: r s=0.648, p=8.206× 10− 5; shortness of breath: r s=0.656, p=6.182× 10–5). The average search-to-confirmed interval (STCI) was 19.8 days in China. The daily Baidu Index value’s optimal time lags were the 4 days for cough, 2 days for fatigue, 3 days for sputum production, 1 day for shortness of breath, and 0 days for fever. Conclusion The searches of COVID-19-related symptoms on the Baidu search engine were significantly correlated to the number of confirmed cases. Since the Baidu search engine could reflect the public’s attention to the pandemic and the regional epidemics of viruses, relevant departments need to pay more attention to areas with high searches of COVID-19-related symptoms and take precautionary measures to prevent these potentially infected persons from further spreading. |
| first_indexed | 2024-12-20T12:14:47Z |
| format | Article |
| id | doaj.art-4095cfd6fda742d38cd9e99da73d550b |
| institution | Directory Open Access Journal |
| issn | 1471-2334 |
| language | English |
| last_indexed | 2024-12-20T12:14:47Z |
| publishDate | 2021-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Infectious Diseases |
| spelling | doaj.art-4095cfd6fda742d38cd9e99da73d550b2022-12-21T19:41:09ZengBMCBMC Infectious Diseases1471-23342021-01-0121111210.1186/s12879-020-05740-xUsing Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu indexBizhi Tu0Laifu Wei1Yaya Jia2Jun Qian3Department of Orthopedics, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Orthopedics, The First Affiliated Hospital of Anhui Medical UniversityDepartment of Pediatrics, The Shanxi Medical UniversityDepartment of Orthopedics, The First Affiliated Hospital of Anhui Medical UniversityAbstract Background New coronavirus disease 2019 (COVID-19) has posed a severe threat to human life and caused a global pandemic. The current research aimed to explore whether the search-engine query patterns could serve as a potential tool for monitoring the outbreak of COVID-19. Methods We collected the number of COVID-19 confirmed cases between January 11, 2020, and April 22, 2020, from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). The search index values of the most common symptoms of COVID-19 (e.g., fever, cough, fatigue) were retrieved from the Baidu Index. Spearman’s correlation analysis was used to analyze the association between the Baidu index values for each COVID-19-related symptom and the number of confirmed cases. Regional distributions among 34 provinces/ regions in China were also analyzed. Results Daily growth of confirmed cases and Baidu index values for each COVID-19-related symptom presented robust positive correlations during the outbreak (fever: r s=0.705, p=9.623× 10− 6; cough: r s=0.592, p=4.485× 10− 4; fatigue: r s=0.629, p=1.494× 10− 4; sputum production: r s=0.648, p=8.206× 10− 5; shortness of breath: r s=0.656, p=6.182× 10–5). The average search-to-confirmed interval (STCI) was 19.8 days in China. The daily Baidu Index value’s optimal time lags were the 4 days for cough, 2 days for fatigue, 3 days for sputum production, 1 day for shortness of breath, and 0 days for fever. Conclusion The searches of COVID-19-related symptoms on the Baidu search engine were significantly correlated to the number of confirmed cases. Since the Baidu search engine could reflect the public’s attention to the pandemic and the regional epidemics of viruses, relevant departments need to pay more attention to areas with high searches of COVID-19-related symptoms and take precautionary measures to prevent these potentially infected persons from further spreading.https://doi.org/10.1186/s12879-020-05740-xCOVID-19Web-based dataInternet searchingBaidu index |
| spellingShingle | Bizhi Tu Laifu Wei Yaya Jia Jun Qian Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index BMC Infectious Diseases COVID-19 Web-based data Internet searching Baidu index |
| title | Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index |
| title_full | Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index |
| title_fullStr | Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index |
| title_full_unstemmed | Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index |
| title_short | Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: – evidence from Baidu index |
| title_sort | using baidu search values to monitor and predict the confirmed cases of covid 19 in china evidence from baidu index |
| topic | COVID-19 Web-based data Internet searching Baidu index |
| url | https://doi.org/10.1186/s12879-020-05740-x |
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