Tech giant Google has been released search trends dataset of COVID-19 symptoms to help researchers to examine the correlation between search queries and COVID-19 spread. This dataset includes Google search patterns for over 400 symptoms, signs, and health conditions like “cough,” “fever,” and “difficulty breathing,” which based on U.S. county level over the past three years.
Public health experts indicated that trends in search patterns might be helpful in broadly understanding how COVID-19 impacts communities and even in detecting outbreaks earlier. Microsoft researchers also used Bing search data to characterize the changes in people’s needs during the pandemic.
Previously, group of scientists have analyzed Google search data to measure the health impact of heatwaves, improve prediction models for influenza-like illnesses, and monitor Lyme disease incidence.
In a recent study published in the Journal of Medical Internet Research, scientists at Cedars-Sinai Medical Center, Indiana University, and Kentuckiana ENT found a correlation between searches for symptoms of the disease and new confirmed cases and deaths. Moreover, they managed to tie increased symptom searches to super-spreading events including the February Champions League soccer match in Italy.
According to the Google blog, “Public health currently uses a range of datasets to track and forecast the spread of COVID-19. Researchers could use this dataset to study if search trends can provide an earlier and more accurate indication of the reemergence of the virus in different parts of the country. And since measures such as shelter-in-place have reduced the accessibility of care and affected people’s wellbeing more generally, this dataset—which covers a broad range of symptoms and conditions, from diabetes to stress—could also be useful in studying the secondary health effects of the pandemic.”
Moreover, the privacy of the your search queries are protected as google adds noise to the data while preserving quality.”To further protect people’s privacy, we ensure that no personal information or individual search queries are included in the dataset, and we don’t link any search-based health inferences to an individual user”, says google.
This search pattern dataset also normalized based on symptoms’ relative popularities, allowing researchers to study spikes in search interest over periods of time. Although the initial release is limited to the U.S. and covers searches made in English and Spanish in states and countries.
The release of new Google search patterns dataset is a part of Google Cloud’s ongoing COVID-19 Public Datasets program, which kicked off earlier this summer. This COVID-19 Public Datasets program includes the Johns Hopkins Center for Systems Science and Engineering (JHU CSSE) data set, Global Health Data from the World Bank, and OpenStreetMap data, all of which Google stores for free on Google Cloud.