About: Using the internet search data to investigate symptom characteristics of COVID-19: a big data study

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About: Using the internet search data to investigate symptom characteristics of COVID-19: a big data study Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Using the internet search data to investigate symptom characteristics of COVID-19: a big data study
Creator	Zheng, Rui Huang, Yang, Huang, Xue-Kun Qiu, Hui-Jun Wu, Qing-Wu Yang, Qin-Tai Yuan, Lian-Xiong Zhou, Yu-Qi
Source	Elsevier; Medline; PMC
abstract	OBJECTIVE: Analyzing the symptom characteristics of Coronavirus Disease 2019(COVID-19) to improve control and prevention. METHODS: Using the Baidu Index Platform (http://index.baidu.com) and the website of Chinese Center for Disease Control and Prevention as data resources to obtain the search volume (SV) of keywords for symptoms associated with COVID-19 from January 1 to February 20 in each year from 2017 to 2020 and the epidemic data in Hubei province and the other top 9 impacted provinces in China. Data of 2020 were compared with those of the previous three years. Data of Hubei province were compared with those of the other 9 provinces. The differences and characteristics of the SV of COVID-19-related symptoms, and the correlations between the SV of COVID-19 and the number of newly confirmed/suspected cases were analyzed. The lag effects were discussed. RESULTS: Comparing the SV from January 1, 2020 to February 20, 2020 with those for the same period of the previous three years, Hubei's SV for cough, fever, diarrhea, chest tightness, dyspnea, and other symptoms were significantly increased. The total SV of lower respiratory symptoms was significantly higher than that of upper respiratory symptoms (P<0.001). The SV of COVID-19 in Hubei province was significantly correlated with the number of newly confirmed/suspected cases (r(confirmed) = 0.723, r(suspected) = 0.863, both P< 0.001). The results of the distributed lag model suggested that the patients who searched relevant symptoms on the Internet may begin to see doctors in 2-3 days later and be confirmed in 3-4 days later. CONCLUSION: The total SV of lower respiratory symptoms was higher than that of upper respiratory symptoms, and the SV of diarrhea also increased significantly. It warned us to pay attention to not only the symptoms of the lower respiratory tract but also the gastrointestinal symptoms, especially diarrhea in patients with COVID-19. Internet search behavior had a positive correlation with the number of newly confirmed/suspected cases, suggesting that big data has an important role in the early warning of infectious diseases.
has issue date	2020-05-19(xsd:dateTime)
bibo:doi	10.1016/j.wjorl.2020.05.003
bibo:pmid	32837757
has license	no-cc
sha1sum (hex)	804c56140ea5d25f0991b484e6c56b49f8052da5
schema:url	https://doi.org/10.1016/j.wjorl.2020.05.003
resource representing a document's title	Using the internet search data to investigate symptom characteristics of COVID-19: a big data study
has PubMed Central identifier	PMC7236685
has PubMed identifier	32837757
schema:publication	World J Otorhinolaryngol Head Neck Surg
resource representing a document's body	covid:804c56140ea5d25f0991b484e6c56b49f8052da5#body_text
is schema:about of	named entity 'COVID-19' named entity 'diarrhea' named entity 'lag' named entity 'symptoms' named entity 'suspected' named entity 'CASES' named entity 'TOTAL' named entity 'HUBEI PROVINCE' named entity 'LOWER' named entity 'FEVER' named entity 'EARLY' named entity 'POSITIVE' named entity 'impacted' named entity 'doctors' named entity 'fatigue' named entity 'respiratory symptoms' named entity 'Baidu' named entity 'COVID' named entity 'sneezing' named entity 'diarrhea' named entity 'diarrhea' named entity 'chest tightness' named entity 'cough' named entity 'chest pain' named entity 'symptoms' named entity 'suspected' named entity 'period' named entity 'respiratory' named entity 'early warning' named entity 'Baidu' named entity 'upper respiratory tract' named entity 'COVID' named entity 'big data' named entity 'Baidu' named entity 'inflammation' named entity 'dyspnea' named entity 'ACE2 receptor' named entity 'rhinitis' named entity 'fecal-oral transmission' named entity 'chronic obstructive pulmonary disease' named entity 'conjunctival' named entity 'chest tightness' named entity 'chest pain' named entity 'medical development' named entity 'cognition' named entity 'Henan' named entity 'fever' named entity 'gastrointestinal symptoms' named entity 'Internet' named entity 'ACE2' named entity 'February 12' named entity 'respiratory' named entity 'higher' named entity 'Hubei' named entity 'infectious diseases' named entity 'respiratory symptoms' named entity 'cough' named entity 'dyspnea' named entity 'Hubei' named entity 'epidemic' named entity 'sputum' named entity 'China' named entity 'December 2019' named entity 'SARS' named entity 'symptom' named entity 'ACE2' named entity 'symptom' named entity 'palpitations' named entity 'respiratory symptoms' named entity 'COVID' named entity 'respiratory symptoms' named entity 'SARS-CoV-2' named entity 'gastrointestinal symptoms'

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