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Can Google® trends predict emergency department admissions in pandemic periods?

Serkan Emre Eroglu, Gokhan Aksel, Ibrahim Altunok, Serdar Ozdemir, Abdullah Algin, Hatice Seyma Akca, Kamil Kokulu.

Abstract
Currently, individual sharing and emotions can affect health behaviors and admissions to hospitals. Google Trends created from Google search can use for screening mood changes associated with people's daily lives. We aimed to investigate the association between emergency department (ED) admissions and Covid-19-associated search engine use. This cross-sectional observational study was carried out in the ED between 2018 to 2020. Since the Covid-19 disease is specific to this year, Google Trends analysis was done between December 31, 2019 and March 31, 2020. However, ED admissions data for the same period were also compared with the data of 2018 and 2019 to observe the change from previous years. The correlation between the IOTs (a kind of search data score defined by google trends) term and the number of admissions to ED were evaluated. A total of 118,765 patients admitted from December 31, 2019 to March 31, 2020. Out of these ED visits, 34.830(29.3%) were admitted by Covid-like symptoms. The average rate of patients with these symptoms in the same periods of the last 3 years was 24%. We discovered that the IOTs for the term ‘corona’, which has the greatest IOTs among other terms, was positively correlated with the ratio of patients with coronavirus-like symptoms to all patients (r = 0.249, p < 0.001) and negatively correlated with the ratio of patients with other symptoms to all patients (r = -0.249, p < 0.001). Contrary to the expectations,the pandemic situation, a decrease in the number of cases should make us question a patients' urgency. Because of the association between search engine using and patient admissions during the coronavirus pandemic, our study is the first study to predict emergency crowding. Due to this characteristic, our research can provide important data for forecasting health system management.

Key words: Emergency departments, patient admission, search engine, pandemics, Covid-19, Covid-19 symptoms, coronavirus, pneumonia.



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