Google trends as an aid in predicting the course of the COVID-19 epidemic in Serbia - Nikolić, Vladimir; Subotić, Nikola; Subotić, Jovana; Marković-Denić, Ljiljana (Medicinski časopis, 2021)
Aim: Determination of the correlations between the search for key terms related to the COVID-19 pandemic and the course of the epidemic in Serbia. Methods: A survey was conducted by a type of cross-sectional study, in November 2020. The research was conducted through the website Google trends. This open-access platform is based on automatic data collection, in order to estimate the percentage of searches for relevant keywords of interest. Data collected are anonymous and were divided by days, months, years, and geographical regions. Results: The study included 32 key terms related to the COVID-19 pandemic. There was a statistically significant positive correlation with the number of registered cases per day for the terms: "coronavirus", "corona", "covid-19", "covid", "kovid", "virus", "corona symptoms", "loss of smell", "loss of taste", "loss of smell and taste", "loss of sense of smell", "loss of sense of taste", "pneumonia", "kovid infirmary", "infirmary", "kovid test", "corona test", "PCR", "serology ", "antibodies ", "corona antibodies", "vaccine ", "corona vaccine ". Conclusion: The shown correlation between the search for appropriate terms related to the COVID-19 pandemic and the course of the epidemic in Serbia can significantly help in predicting the course of the COVID-19 epidemic. In the future, we should work on developing predictive models and software tools based on these resources, not only for COVID-19 but also for other diseases, which would monitor Internet searches in real-time, all with the aim of adequate and timely organization of public health activities. Keywords: COVID-19, Google trends, pandemic, coronavirus