ArticleClinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association2020
Increased Internet Search Interest for GI Symptoms May Predict COVID-19 Cases in US Hotspots.
Article in Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 36 citations in OpenAlex.
- Deep recurrent models for forecasting infectious diseases.Frontiers in public health · 2025Article
- Predicting mobility using limited data during early stages of a pandemic.Journal of business research · 2023Article
- Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review.International journal of environmental research and public health · 2022Review
- Interest in Home Birth During the COVID-19 Pandemic: Analysis of Google Trends Data.Journal of midwifery & women's health · 2022Article
- Article
- Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study.Journal of medical Internet research · 2021Article
- An open repository of real-time COVID-19 indicators.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Non-intrusive wastewater surveillance for monitoring of a residential building for COVID-19 cases.The Science of the total environment · 2021Article
- The COVID-19 Menace.Global challenges (Hoboken, NJ) · 2021Review
- Internet search patterns reveal clinical course of COVID-19 disease progression and pandemic spread across 32 countries.NPJ digital medicine · 2021Article
- Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research.Frontiers in research metrics and analytics · 2021Article
- #MaskOn! #MaskOff! Digital polarization of mask-wearing in the United States during COVID-19.PloS one · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Google Trends is an online tool that allows measurement of search term popularity on Google, spatially and temporally. While not an epidemiological tool for determining incidence, it can estimate the popularity of a certain disease by search volume over time.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.