Google searches for gastric problems can detect new clusters

In full return, many children had to stay at home because of a doubt related to a runny nose or a cough, as a precaution, to avoid taking the risk of introducing the new Covid at school. Many symptoms of a simple cold are indeed similar to those of the coronavirus (fever, cough, runny nose), but unlike the small diseases caused by these viruses which attack us at each change of season when our immune defenses decrease, other symptoms, such as digestive problems, appear to be much more revealing. Thanks to this specificity, it is possible to identify increases in coronavirus cases by monitoring the evolution of gastric disorders. A study even indicates that Google searches for gastric problems would predict the appearance of new coronavirus clusters!

The stool could tell more about the pandemic than you think

Researchers at the Chinese University of Hong Kong published in May 2020 a study in the medical scientific journal GUT which shows that patients with Covid-19 have an active and prolonged viral intestinal infection, even in the absence of gastrointestinal symptoms.
The coronavirus could continue to infect and replicate in the digestive tract after withdrawing from the respiratory tract, which is important both for the identification and for the treatment of cases.
Scientists studied stool samples from 15 patients to better understand virus activity in the gastrointestinal tract. They found an active intestinal infection in seven of them, some of whom did not have nausea, diarrhea or other digestive symptoms. Patients’ stools continued to test positive about a week after their respiratory samples tested negative, up to 30 days after contamination.

Our Google queries related to our stomach ailments could predict an increase in Covid-19 cases

Taking this relative reliability of gastrointestinal symptoms into account, other researchers at Massachusetts General Hospital in the United States have found that Internet research into these symptoms could even predict an increase in Covid-19 cases, with several weeks of ‘advanced. According to the researchers, queries on symptoms of loss of taste and appetite, and diarrhea between January 20 to April 20 were most strongly correlated with areas where the excess mortality was highest three to four times. weeks later. Abdominal pain and diarrhea, according to the study, are warning signs of the disease.
The study suggests that Google Trends could be a valuable tool for predicting pandemics with gastrointestinal manifestations in the same way that the tool helped predict more than 10 years ago the swine flu. At the time, this technique had proved particularly useful for tracking areas where data was lacking or where normal surveillance systems were disturbed.
For Evgeniy Gabrilovich, senior researcher at Google Health, Google Trends could also be useful in studying the side effects of the pandemic on health.

Google and Microsoft want to understand everything about Coronavirus thanks to our research

On September 2, Google released a corpus of Google query trends intended to help researchers study the link between queries and the spread of COVID-19. The COVID-19 research symptom corpus includes Google search trends in the United States for more than 400 symptoms, signs and health conditions such as “cough”, “fever” and “difficulty breathing” over the three last years.
This Google Trends-like tool analyzes research data related to COVID-19 based on popularity trends, taking into account queries made in the United States, in Spanish and in English.
The release of the COVID-19 research symptom dataset is part of Google Cloud’s COVID-19 Public Datasets program, which began earlier this summer.
To ensure the privacy of personal data, Google says symptoms of COVID-19 are anonymized and no personal information or individual search queries are included, in part “thanks to a technique that adds noise to the data to provide guarantees of confidentiality while preserving quality ‘.

The use of big data can go well beyond the analysis of the pandemic or the prediction of a cluster: the technology has also been used by Microsoft to understand the impact of the pandemic on society. Thanks to data from its Bing search engine, the web giant was able to analyze changes in the physiological, socio-economic and psychological needs of people during the pandemic. After applying his system to more than 35 billion web searches, covering approximately 36,000 postal codes over a 14-month period, the researchers say they found evidence that the expression of basic needs was increasing “exponentially” while higher level aspirations decline. Characteristics which help to understand a society completely transformed by the pandemic.

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