Background: The outbreak of the new coronavirus disease (COVID-19) has affected human life to a great extent on a worldwide scale. During the coronavirus pandemic, public health professionals at the early outbreak faced an extraordinary challenge to track and quantify the spread of disease. Objective: To investigate whether a digital surveillance model using google trends (GT) is feasible to monitor the outbreak of coronavirus in the Kingdom of Saudi Arabia. Methods: We retrieve GT data using ten common COVID-19 symptoms related keywords from March 2, 2020, to October 31, 2020. Spearman correlation were performed to determine the correlation between COVID-19 cases and the Google search terms. Results: GT data related to Cough and Sore Throat were the most searched symptoms by the Internet users in Saudi Arabia. The highest daily correlation found with the Loss of Smell followed by Loss of Taste and Diarrhea. Strong correlation as well was found between the weekly confirmed cases and the same symptoms: Loss of Smell, Loss of Taste and Diarrhea. Conclusions: We conducted an investigation study utilizing Internet searches related to COVID-19 symptoms for surveillance of the pandemic spread. This study documents that google searches can be used as a supplementary surveillance tool in COVID-19 monitoring in Saudi Arabia.