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BACKGROUND there are evidences for the fact that infodemiology studies can predict the prevalence of diseases and general health problems. This study aimed to investigate the infodemiology of new coronavirus disease (COVID-19) in Iran. OBJECTIVE This study aimed to investigate the infodemiology of new coronavirus disease (COVID-19) in Iran. METHODS To confirm the searches conducted by Iranian users in the Google search engine, three keywords such as Corona, Coronavirus and COVID-19 were used in Persian. In addition, 16 keywords related to the symptoms of the disease were used to look into how searches were conducted on the symptoms of COVID-19. All of the study keywords were searched in Google Trends (GTr). In GTr results the geographical area and the search period were limited to Iran and the last 12 months, respectively. The search results were saved as an Excel output and analyzed via SPSS software (V.23). RESULTS The searches conducted by Iranian users with the three keywords Corona, Coronavirus and COVID-19 increased significantly from January to March 2020, and then decreased significantly in April 2020. There was a positive and significant correlation between the search rate of COVID-19 and the number of new cases of COVID-19 on the day of searches, 3 and 7 days after searches (P = 0.00). Search rates with COVID-19 were able to predict the number of COVID-19 new cases 3 days after the search (B = 16.74, 95% CI: 1.67-31.82). Search rates with COVID-19 and taste disorders were also able to predict the number of COVID-19 new cases, 7 days after the searches (B = 22.75, 95% CI: 11.72-33.78; B = 12.50, 95% CI: 5.30-16.96). CONCLUSIONS The information behavior of Iranian users in the Google can predict the incidence of COVID-19 in this country. On the other hand GTr reports are free and real-time, so this tool can be used to manage and control the COVID-19 pandemic in Iran. |
