Google Trend as an Early Warning System for Corona Outbreak Investigation in Iran
نویسندگان
1 Student Research Committee, School of Nursing and Midwifery, Sabzevar University of Medical Sciences, Sabzevar, Iran
2 Student Research Committee, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
3 Assistant professor, Department of Epidemiology and Biostatistics, School of Public Health, Shahrekord University of Medical Sciences, Shahrekord, Iran
4 Department of Public Health Behbahan Faculty of Medical Sciences, Behbahan, Iran
5 Alimentary Tract Research Center, Imam Khomeini Hospital Clinical Research Development Unit, Jundishapur University of Medical Sciences, Ahvaz, Iran
6 School of Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran
7 Assistant professor, Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran -Assistant professor, Department of Epidemiology and Biostatistics, School of Public Health, Shahrekord University of Medical Sciences, Shahrekord, Iran
doi
10.30476/jhmi.2022.94812.1122چکیده
Introduction: Digital epidemiology is introduced as a major aspect of epidemiology; itssources are digital data and it uses spaces such as Google, YouTube and Twitter as databases.In the recent Covid-19 pandemic, the use of digital epidemiology, as an early warning system,has been considered. This study aimed to investigate the context of Google Trend as an earlywarning system in the study of coronavirus outbreaks in Iran.Methods: The coronavirus epidemic in Iran started on February 24, 2020, and with somedifferences to consider the rumors in the community, we consider the date before theannouncement of all by February 16, 2020 until November 16, 2021. We searched usingkeywords related to symptoms such as “fever”, “cough” and “sore throat” and the keyword“corona symptoms”; information was extracted and entered in Microsoft Excel and thekeyword chart was drawn according to the date of each wave. Spearman correlation test wasperformed to find the correlation between keywords in SPSS version 18.Results: The trend chart of the keywords “fever”, “cough” and “sore throat” and the keyword“corona symptoms” in different waves of coronavirus in Iran showed an increase in keywordsearches before the onset of the corona epidemic wave. Spearman correlation coefficientbetween sore throat and fever was 0.645, sore throat and cough 0.775, sore throat and coronasymptoms 0.684, between fever and cough keywords 0.435, fever and corona symptoms 0.779and between keyword cough and corona symptoms 0.503. In all these coefficients, the level oferror of the first type was 0.05 significant (P<0.001)Conclusion: Google Trend, a digital epidemiology tool, can be used as an effective earlywarning system to control the corona pandemic, and this field of epidemiological knowledgewith all its limitations needs further research.
