Many months into the COVID-19 pandemic, there is still a lot about the virus that we do not yet know. While initial symptoms included a dry cough and fever, later medical observations noted that some patients suffered from other symptoms such as stomachache and diarrhea.
With such confusion abounding, many patients are taking to Google search to try and understand the source of their symptoms. Now, a new study by the Massachusetts General Hospital in the US has discovered that Google search trends can actually be used to identify COVID-19 hotspots, particularly when users search for certain gastrointestinal (GI) symptoms. While not all correlate to an increase in COVID-19 cases, the following symptoms have been associated with infection by previous studies: ageusia (loss of taste), abdominal pain, loss of appetite, anorexia, diarrhea, and vomiting.
The research monitored search queries in 15 states between January 20 and April 20, and found that Google search interest in ageusia, loss of appetite, and diarrhea in particular increased 4 weeks prior to the rise in COVID-19 cases for most states, effectively serving as a warning sign for where the virus would surge in number ahead of time.
“Our data underscore the importance of GI symptoms as a potential harbinger of Covid-19 infection and suggests that Google Trends may be a valuable tool for prediction of pandemics with GI manifestations,” Kyle Staller, a gastroenterologist and the director of Mass General’s gastrointestinal motility laboratory, and colleagues wrote in the study.
A similar method of disease forecasting was previously used more than a decade ago to detect influenza, the study said.
Over the years, we’ve seen many scientific reports utilize online data based on search queries and social media networks to help predict and understand disease outbreaks.
“Traditional systems and techniques [of disease detection] mainly use epidemiological data, such as medical data or health log files obtained from doctors and hospitals. However, several studies have recently included non-epidemiological data obtained through the Internet as an alternative, concretely data extracted from search engines or messages interchanged in social media,” a study published in online medical journal Scientific Reports stated. “Internet technologies have demonstrated their value for the early detection and prediction of epidemics. In diverse cases, electronic surveillance systems can be created by obtaining and analyzing on-line data, complementing other existing monitoring resources.”
In 2018, a similar study was conducted in India, where Google search trends in the country were used in correlation with epidemiological data to predict a surge in chikungunya, dengue fever, malaria and enteric fever cases 2 to 3 weeks prior.
However, while this novel form of predicting outbreaks is certainly groundbreaking and could hold great benefits for society over the years, it is not perfect by any measure, and should not be used as the sole defining metric of prediction and prevention.
“Correlations alone should not be viewed as definitive evidence of impending outbreaks or epidemics as the analyses performed were univariate and exploratory in nature,” the study in India noted. “The results of this study should be interpreted with caution keeping in mind the biological plausibility and natural history of the disease concerned.”
Additionally, one has to account for other factors such as internet penetration in a country, as search trends are only relevant if a country or region has a large number of digitally literate users.