Cargando…
The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19
Internet search data was a useful tool in the pre-warning of COVID-19. However, the lead time and indicators may change over time and space with the new variants appear and massive nucleic acid testing. Since Omicron appeared in late 2021, we collected the daily number of cases and Baidu Search Inde...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484897/ https://www.ncbi.nlm.nih.gov/pubmed/37679512 http://dx.doi.org/10.1038/s41598-023-41939-z |
_version_ | 1785102672063365120 |
---|---|
author | Ruan, Yuhua Huang, Tengda Zhou, Wanwan Zhu, Jinhui Liang, Qiuyu Zhong, Lixian Tang, Xiaofen Liu, Lu Chen, Shiwen Xie, Yihong |
author_facet | Ruan, Yuhua Huang, Tengda Zhou, Wanwan Zhu, Jinhui Liang, Qiuyu Zhong, Lixian Tang, Xiaofen Liu, Lu Chen, Shiwen Xie, Yihong |
author_sort | Ruan, Yuhua |
collection | PubMed |
description | Internet search data was a useful tool in the pre-warning of COVID-19. However, the lead time and indicators may change over time and space with the new variants appear and massive nucleic acid testing. Since Omicron appeared in late 2021, we collected the daily number of cases and Baidu Search Index (BSI) of seven search terms from 1 January to 30 April, 2022 in 12 provinces/prefectures to explore the variation in China. Two search peaks of “COVID-19 epidemic”, “Novel Coronavirus” and “COVID-19” can be observed. One in January, which showed 3 days lead time in Henan and Tianjin. Another on early March, which occurred 0–28 days ahead of the local epidemic but the lead time had spatial variation. It was 4 weeks in Shanghai, 2 weeks in Henan and 5–8 days in Jilin Province, Jilin and Changchun Prefecture. But it was only 1–3 days in Tianjin, Quanzhou Prefecture, Fujian Province and 0 day in Shenzhen, Shandong Province, Qingdao and Yanbian Prefecture. The BSI was high correlated (r(s):0.70–0.93) to the number of cases with consistent epidemiological change trend. The lead time of BSI had spatial and temporal variation and was close related to the strength of nucleic acid testing. The case detection ability should be strengthened when perceiving BSI increase. |
format | Online Article Text |
id | pubmed-10484897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104848972023-09-09 The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 Ruan, Yuhua Huang, Tengda Zhou, Wanwan Zhu, Jinhui Liang, Qiuyu Zhong, Lixian Tang, Xiaofen Liu, Lu Chen, Shiwen Xie, Yihong Sci Rep Article Internet search data was a useful tool in the pre-warning of COVID-19. However, the lead time and indicators may change over time and space with the new variants appear and massive nucleic acid testing. Since Omicron appeared in late 2021, we collected the daily number of cases and Baidu Search Index (BSI) of seven search terms from 1 January to 30 April, 2022 in 12 provinces/prefectures to explore the variation in China. Two search peaks of “COVID-19 epidemic”, “Novel Coronavirus” and “COVID-19” can be observed. One in January, which showed 3 days lead time in Henan and Tianjin. Another on early March, which occurred 0–28 days ahead of the local epidemic but the lead time had spatial variation. It was 4 weeks in Shanghai, 2 weeks in Henan and 5–8 days in Jilin Province, Jilin and Changchun Prefecture. But it was only 1–3 days in Tianjin, Quanzhou Prefecture, Fujian Province and 0 day in Shenzhen, Shandong Province, Qingdao and Yanbian Prefecture. The BSI was high correlated (r(s):0.70–0.93) to the number of cases with consistent epidemiological change trend. The lead time of BSI had spatial and temporal variation and was close related to the strength of nucleic acid testing. The case detection ability should be strengthened when perceiving BSI increase. Nature Publishing Group UK 2023-09-07 /pmc/articles/PMC10484897/ /pubmed/37679512 http://dx.doi.org/10.1038/s41598-023-41939-z Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Ruan, Yuhua Huang, Tengda Zhou, Wanwan Zhu, Jinhui Liang, Qiuyu Zhong, Lixian Tang, Xiaofen Liu, Lu Chen, Shiwen Xie, Yihong The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 |
title | The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 |
title_full | The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 |
title_fullStr | The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 |
title_full_unstemmed | The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 |
title_short | The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19 |
title_sort | lead time and geographical variations of baidu search index in the early warning of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484897/ https://www.ncbi.nlm.nih.gov/pubmed/37679512 http://dx.doi.org/10.1038/s41598-023-41939-z |
work_keys_str_mv | AT ruanyuhua theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT huangtengda theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT zhouwanwan theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT zhujinhui theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT liangqiuyu theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT zhonglixian theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT tangxiaofen theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT liulu theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT chenshiwen theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT xieyihong theleadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT ruanyuhua leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT huangtengda leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT zhouwanwan leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT zhujinhui leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT liangqiuyu leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT zhonglixian leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT tangxiaofen leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT liulu leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT chenshiwen leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 AT xieyihong leadtimeandgeographicalvariationsofbaidusearchindexintheearlywarningofcovid19 |