Cargando…
Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data
BACKGROUND: From the beginning of 2020, the world was plunged into a pandemic caused by the novel coronavirus disease-19 (COVID-19). People increasingly searched for information related to COVID-19 on internet websites. The Baidu Index is a data sharing platform. The main data provided is the search...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511189/ https://www.ncbi.nlm.nih.gov/pubmed/36172094 http://dx.doi.org/10.21037/atm-22-3465 |
_version_ | 1784797609046573056 |
---|---|
author | Luo, Jianchen Ma, Jing Xu, Liangliang Zhang, Shuqi Zhang, Ming Xu, Mingqing |
author_facet | Luo, Jianchen Ma, Jing Xu, Liangliang Zhang, Shuqi Zhang, Ming Xu, Mingqing |
author_sort | Luo, Jianchen |
collection | PubMed |
description | BACKGROUND: From the beginning of 2020, the world was plunged into a pandemic caused by the novel coronavirus disease-19 (COVID-19). People increasingly searched for information related to COVID-19 on internet websites. The Baidu Index is a data sharing platform. The main data provided is the search index (SI), which represents the frequency that keywords are used in searches. METHODS: January 9, 2020 is an important date for the outbreak of COVID-19 in China. We compared the changes of SI before and after for 7 keywords, including “fever”, “cough”, “nausea”, “vomiting”, “abdominal pain”, “diarrhea”, “constipation”. The slope and peak values of SI change curves are compared. Ten provinces in China were selected for a separate analysis, including Beijing, Gansu, Guangdong, Guangxi, Heilongjiang, Hubei, Sichuan, Shanghai, Xinjiang, Tibet. The change of SI was analyzed separately, and the correlation between SI and demographic and economic data was analyzed. RESULTS: During period I, from January 9 to January 25, 2020, the average daily increase (ADI) of the SI for “diarrhea” was lower than that for “cough” (889.47 vs. 1,799.12, F=11.43, P=0.002). In period II, from January 25 to April 8, 2020, the average daily decrease (ADD) of the SI for “diarrhea” was significantly lower than that for “cough”, with statistical significance (cough, 191.40 vs. 441.44, F=68.66, P<0.001). The mean SI after January 9, 2020 (pre-SI) was lower than that before January 9, 2020 (post-SI) (fever, 2,616.41±116.92 vs. 3,724.51±867.81, P<0.001; cough, 3,260.04±308.43 vs. 5,590.66±874.25, P<0.001; diarrhea, 4,128.80±200.82 vs. 4,423.55±1,058.01, P<0.001). The pre-SI mean was correlated with population (P=0.004, R=0.813) and gross domestic product (GDP) (P<0.001, R=0.966). The post-SI peak was correlated with population (P=0.007, R=0.789), GDP (P=0.005, R=0.804), and previously confirmed cases (PCC) (P=0.03, R=0.670). The growth rate of the SI was correlated with the post-SI peak (P=0.04, R=0.649), PCC (P=0.003, R=0.835). CONCLUSIONS: Diarrhea was of widespread concern in all provinces before and after the COVID-19 outbreak and may be associated with novel coronavirus infection. Internet big data can reflect the public’s concern about diseases, which is of great significance for the study of the epidemiological characteristics of diseases. |
format | Online Article Text |
id | pubmed-9511189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-95111892022-09-27 Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data Luo, Jianchen Ma, Jing Xu, Liangliang Zhang, Shuqi Zhang, Ming Xu, Mingqing Ann Transl Med Original Article BACKGROUND: From the beginning of 2020, the world was plunged into a pandemic caused by the novel coronavirus disease-19 (COVID-19). People increasingly searched for information related to COVID-19 on internet websites. The Baidu Index is a data sharing platform. The main data provided is the search index (SI), which represents the frequency that keywords are used in searches. METHODS: January 9, 2020 is an important date for the outbreak of COVID-19 in China. We compared the changes of SI before and after for 7 keywords, including “fever”, “cough”, “nausea”, “vomiting”, “abdominal pain”, “diarrhea”, “constipation”. The slope and peak values of SI change curves are compared. Ten provinces in China were selected for a separate analysis, including Beijing, Gansu, Guangdong, Guangxi, Heilongjiang, Hubei, Sichuan, Shanghai, Xinjiang, Tibet. The change of SI was analyzed separately, and the correlation between SI and demographic and economic data was analyzed. RESULTS: During period I, from January 9 to January 25, 2020, the average daily increase (ADI) of the SI for “diarrhea” was lower than that for “cough” (889.47 vs. 1,799.12, F=11.43, P=0.002). In period II, from January 25 to April 8, 2020, the average daily decrease (ADD) of the SI for “diarrhea” was significantly lower than that for “cough”, with statistical significance (cough, 191.40 vs. 441.44, F=68.66, P<0.001). The mean SI after January 9, 2020 (pre-SI) was lower than that before January 9, 2020 (post-SI) (fever, 2,616.41±116.92 vs. 3,724.51±867.81, P<0.001; cough, 3,260.04±308.43 vs. 5,590.66±874.25, P<0.001; diarrhea, 4,128.80±200.82 vs. 4,423.55±1,058.01, P<0.001). The pre-SI mean was correlated with population (P=0.004, R=0.813) and gross domestic product (GDP) (P<0.001, R=0.966). The post-SI peak was correlated with population (P=0.007, R=0.789), GDP (P=0.005, R=0.804), and previously confirmed cases (PCC) (P=0.03, R=0.670). The growth rate of the SI was correlated with the post-SI peak (P=0.04, R=0.649), PCC (P=0.003, R=0.835). CONCLUSIONS: Diarrhea was of widespread concern in all provinces before and after the COVID-19 outbreak and may be associated with novel coronavirus infection. Internet big data can reflect the public’s concern about diseases, which is of great significance for the study of the epidemiological characteristics of diseases. AME Publishing Company 2022-09 /pmc/articles/PMC9511189/ /pubmed/36172094 http://dx.doi.org/10.21037/atm-22-3465 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Luo, Jianchen Ma, Jing Xu, Liangliang Zhang, Shuqi Zhang, Ming Xu, Mingqing Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data |
title | Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data |
title_full | Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data |
title_fullStr | Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data |
title_full_unstemmed | Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data |
title_short | Using search trends before and after the COVID-19 outbreak in China to analyze digestive symptoms: medical informatics study of the Baidu Index data |
title_sort | using search trends before and after the covid-19 outbreak in china to analyze digestive symptoms: medical informatics study of the baidu index data |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511189/ https://www.ncbi.nlm.nih.gov/pubmed/36172094 http://dx.doi.org/10.21037/atm-22-3465 |
work_keys_str_mv | AT luojianchen usingsearchtrendsbeforeandafterthecovid19outbreakinchinatoanalyzedigestivesymptomsmedicalinformaticsstudyofthebaiduindexdata AT majing usingsearchtrendsbeforeandafterthecovid19outbreakinchinatoanalyzedigestivesymptomsmedicalinformaticsstudyofthebaiduindexdata AT xuliangliang usingsearchtrendsbeforeandafterthecovid19outbreakinchinatoanalyzedigestivesymptomsmedicalinformaticsstudyofthebaiduindexdata AT zhangshuqi usingsearchtrendsbeforeandafterthecovid19outbreakinchinatoanalyzedigestivesymptomsmedicalinformaticsstudyofthebaiduindexdata AT zhangming usingsearchtrendsbeforeandafterthecovid19outbreakinchinatoanalyzedigestivesymptomsmedicalinformaticsstudyofthebaiduindexdata AT xumingqing usingsearchtrendsbeforeandafterthecovid19outbreakinchinatoanalyzedigestivesymptomsmedicalinformaticsstudyofthebaiduindexdata |