Evidence map›Paper›PMID 38939559›Full record

ArticleFrontiers in public health2024

Trending ticks: using Google Trends data to understand tickborne disease prevention.

Cheng-Xian Yang, Lauri M Baker, Ashley McLeod-Morin

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Cheng-Xian YangDepartment of Agricultural Education and Communication, University of Florida, Gainesville, FL, United States.
Lauri M BakerDepartment of Agricultural Education and Communication, University of Florida, Gainesville, FL, United States.
Ashley McLeod-MorinUF/IFAS Center for Public Issues Education in Agriculture and Natural Resources, Gainesville, FL, United States.

Funding

ACL HHS U01CK000662
6 · The paper itself

Abstract

Introduction: Ticks and pathogens they carry seriously impact human and animal health, with some diseases like Lyme and Alpha-gal syndrome posing risks. Searching for health information online can change people's health and preventive behaviors, allowing them to face the tick risks. This study aimed to predict the potential risks of tickborne diseases by examining individuals' online search behavior. Methods: By scrutinizing the search trends across various geographical areas and timeframes within the United States, we determined outdoor activities associated with potential risks of tick-related diseases. Google Trends was used as the data collection and analysis tool due to its accessibility to big data on people's online searching behaviors. We interact with vast amounts of population search data and provide inferences between population behavior and health-related phenomena. Data were collected in the United States from April 2022 to March 2023, with some terms about outdoor activities and tick risks. Results and Discussion: Results highlighted the public's risk susceptibility and severity when participating in activities. Our results found that searches for terms related to tick risk were associated with the five-year average Lyme Disease incidence rates by state, reflecting the predictability of online health searching for tickborne disease risks. Geographically, the results revealed that the states with the highest relative search volumes for tick-related terms were predominantly located in the Eastern region. Periodically, terms can be found to have higher search records during summer. In addition, the results showed that terms related to outdoor activities, such as "corn maze," "hunting," "u-pick," and "park," have moderate associations with tick-related terms. This study provided recommendations for effective communication strategies to encourage the public's adoption of health-promoting behaviors. Displaying warnings in the online search results of individuals who are at high risk for tick exposure or collaborating with outdoor activity locations to disseminate physical preventive messages may help mitigate the risks associated with tickborne diseases.

Indexed as

Search EngineTick-Borne DiseasesAnimalsHumansInformation Seeking BehaviorInternetLyme DiseaseTicksUnited StatesGoogle Trendshealth communicationonline searchrisk communicationtickborne diseaseticksvector-borne diseases

Identifiers

PMID38939559
PMCPMC11208696

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LicenceCC BY
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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.