ArticleJMIR public health and surveillance2021
Using Google Trends to Inform the Population Size Estimation and Spatial Distribution of Gay, Bisexual, and Other Men Who Have Sex With Men: Proof-of-concept Study.
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 4 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
4 citing papers in PubMed.
- Population Size Estimation of Men Who Have Sex With Men in Low- and Middle-Income Countries: Google Trends Analysis.JMIR public health and surveillance · 2025Article
- Quantifying the basic reproduction number and underestimated fraction of Mpox cases worldwide at the onset of the outbreak.Journal of the Royal Society, Interface · 2024Article
- Seasonality of Hashimoto Thyroiditis: Infodemiology Study of Google Trends Data.JMIR bioinformatics and biotechnology · 2022Article
- A Google Trends Approach to Identify Distinct Diurnal and Day-of-Week Web-Based Search Patterns Related to Conjunctivitis and Other Common Eye Conditions: Infodemiology Study.Journal of medical Internet research · 2022Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundWe must triangulate data sources to understand best the spatial distribution and population size of marginalized populations to empower public health leaders to address population-specific needs. Existing population size estimation techniques are difficult and limited.
objectiveWe sought to identify a passive surveillance strategy that utilizes internet and social media to enhance, validate, and triangulate population size estimates of gay, bisexual, and other men who have sex with men (gbMSM).
methodsWe explored the Google Trends platform to approximate an estimate of the spatial heterogeneity of the population distribution of gbMSM. This was done by comparing the prevalence of the search term "gay porn" with that of the search term "porn."
resultsOur results suggested that most cities have a gbMSM population size between 2% and 4% of their total population, with large urban centers having higher estimates relative to rural or suburban areas. This represents nearly a double up of population size estimates compared to that found by other methods, which typically find that between 1% and 2% of the total population are gbMSM. We noted that our method was limited by unequal coverage in internet usage across Canada and differences in the frequency of porn use by gender and sexual orientation.
conclusionsWe argue that Google Trends estimates may provide, for many public health planning purposes, adequate city-level estimates of gbMSM population size in regions with a high prevalence of internet access and for purposes in which a precise or narrow estimate of the population size is not required. Furthermore, the Google Trends platform does so in less than a minute at no cost, making it extremely timely and cost-effective relative to more precise (and complex) estimates. We also discuss future steps for further validation of this approach.
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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.