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Global internet search trends related to gastrointestinal symptoms predict regional COVID-19 outbreaks - 05/01/22

Doi : 10.1016/j.jinf.2021.11.003 
Shuai Ben a, b, 1, Junyi Xin a, b, 1, Silu Chen a, b, 1, Yan Jiang c, Qianyu Yuan d, Li Su d, David C. Christiani d, e, Zhengdong Zhang a, b, , Mulong Du b, f, , Meilin Wang a, b, g,
a Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China 
b Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China 
c Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China 
d Departments of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States of America 
e Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, United States of America 
f Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China 
g Suzhou Municipal Hospital, Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Nanjing Medical University, Suzhou, China 

Corresponding authors at: Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, 101 Longmian Avenue, Jiangning District, Nanjing 211166, China.Department of Environmental GenomicsJiangsu Key Laboratory of Cancer BiomarkersPrevention and TreatmentCollaborative Innovation Center for Cancer Personalized MedicineNanjing Medical University101 Longmian Avenue, Jiangning DistrictNanjing211166China

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Abstract

Background

Real-time surveillance of search behavior on the internet has achieved accessibility in measuring disease activity. In this study, we systematically assessed the associations between internet search trends of gastrointestinal (GI) symptom terms and daily newly confirmed COVID-19 cases at both global and regional levels.

Methods

Relative search volumes (RSVs) of GI symptom terms were derived from internet search engines. Time-series analyses with autoregressive integrated moving average models were conducted to fit and forecast the RSV trends of each GI symptom term before and after the COVID-19 outbreak. Generalized additive models were used to quantify the effects of RSVs of GI symptom terms on the incidence of COVID-19. In addition, dose-response analyses were applied to estimate the shape of the associations.

Results

The RSVs of GI symptom terms could be characterized by seasonal variation and a high correlation with symptoms of “fever” and “cough” at both global and regional levels; in particular, “diarrhea” and “loss of taste” were abnormally increased during the outbreak period of COVID-19, with elevated point changes of 1.31 and 8 times, respectively. In addition, these symptom terms could effectively predict a COVID-19 outbreak in advance, underlying the lag correlation at 12 and 5 days, respectively, and with mutual independence. The dose-response curves showed a consistent increase in daily COVID-19 risk with increasing search volumes of “diarrhea” and “loss of taste”.

Conclusion

This is the first and largest epidemiologic study that comprehensively revealed the advanced prediction of COVID-19 outbreaks at both global and regional levels via GI symptom indicators.

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Keywords : Google trends, COVID-19, Gastrointestinal symptoms, Time-series analysis


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© 2021  Publié par Elsevier Masson SAS.
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Vol 84 - N° 1

P. 56-63 - janvier 2022 Retour au numéro
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