ArticleJMIR public health and surveillance2021
Estimation of Asthma Symptom Onset Using Internet Search Queries: Lag-Time Series Analysis.
Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Potential Association Between Changes in Microbiota Level and Lung Diseases: A Meta-Analysis.Frontiers in medicine · 2021Pooled it
- Seasonal Variation in Public Interest in Gout: Longitudinal Infodemiology Study Using Google Trends (2014-2024).Journal of medical Internet research · 2025Article
- Temporal Association Between ChatGPT-Generated Diarrhea Synonyms in Internet Search Queries and Emergency Department Visits for Diarrhea-Related Symptoms in South Korea: Exploratory Study.Journal of medical Internet research · 2025Article
- Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?Einstein (Sao Paulo, Brazil) · 2024Article
- The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study.JMIR public health and surveillance · 2022Observational
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAsthma affects over 330 million people worldwide. Timing of an asthma event is extremely important and lack of identification of asthma increases the risk of death. A major challenge for health systems is the length of time between symptom onset and care seeking, which could result in delayed treatment initiation and worsening of symptoms.
objectiveThis study evaluates the utility of the internet search query data for the identification of the onset of asthma symptoms.
methodsPearson correlation coefficients between the time series of hospital admissions and Google searches were computed at lag times from 4 weeks before hospital admission to 4 weeks after hospital admission. An autoregressive integrated moving average (ARIMAX) model with an autoregressive process at lags of 1 and 2 and Google searches at weeks -1 and -2 as exogenous variables were conducted to validate our correlation results.
resultsGoogle search volume for asthma had the highest correlation at 2 weeks before hospital admission. The ARIMAX model using an autoregressive process showed that the relative searches from Google about asthma were significant at lags 1 (P<.001) and 2 (P=.04).
conclusionsOur findings demonstrate that internet search queries may provide a real-time signal for asthma events and may be useful to measure the timing of symptom onset.
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