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Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends

Non-specific symptoms in later stages of Lyme disease (LD) may mimic a variety of autoimmune, viral, or complex diseases. Patients lacking erythema migrans or who test negative under CDC guidelines, but suspect LD may search online symptoms in vein. As a result, patients with lingering and undiagnos...

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Autores principales: Kim, Dohyeong, Maxwell, Sarah, Le, Quang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456861/
https://www.ncbi.nlm.nih.gov/pubmed/32923420
http://dx.doi.org/10.3389/fpubh.2020.00395
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author Kim, Dohyeong
Maxwell, Sarah
Le, Quang
author_facet Kim, Dohyeong
Maxwell, Sarah
Le, Quang
author_sort Kim, Dohyeong
collection PubMed
description Non-specific symptoms in later stages of Lyme disease (LD) may mimic a variety of autoimmune, viral, or complex diseases. Patients lacking erythema migrans or who test negative under CDC guidelines, but suspect LD may search online symptoms in vein. As a result, patients with lingering and undiagnosed symptoms turn to alternative lab tests. This study addresses patient's perceived illness in relation to CDC surveillance data. Extending the literature beyond basic searches for symptoms or disease terms, this study examines spatiotemporal dynamics among symptom, disease, and unconventional lab test searches on Google Trends, in compared with CDC confirmed cases of LD. The search terms used for the Google Trends analysis between 2011 and 2015 include: (1) “lyme” and “lyme disease” for disease, (2) “tick bite,” “bone pain,” “stiff neck,” “circular rash,” and “brain fog” for symptoms, and (3) “IGENEX” for the alternative lab test. Spatial and temporal analyses illustrate noticeable similar patterns between the search frequency and the actual LD incidence. Beyond basic searches for symptoms or disease terms, we demonstrate the improved utility of Google Trends analysis in discovering spatial and temporal patterns of perceived LD and comparing with the reported LD cases. The public health and medical communities benefit from this research through improved knowledge of undiagnosed patients who are searching for alternative labs to explain lingering symptoms. This study validates the need for further research into Google Trends data and surveillance protocols of diseases characterized by non-specific symptoms, prompting patients to “self-diagnose.”
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spelling pubmed-74568612020-09-11 Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends Kim, Dohyeong Maxwell, Sarah Le, Quang Front Public Health Public Health Non-specific symptoms in later stages of Lyme disease (LD) may mimic a variety of autoimmune, viral, or complex diseases. Patients lacking erythema migrans or who test negative under CDC guidelines, but suspect LD may search online symptoms in vein. As a result, patients with lingering and undiagnosed symptoms turn to alternative lab tests. This study addresses patient's perceived illness in relation to CDC surveillance data. Extending the literature beyond basic searches for symptoms or disease terms, this study examines spatiotemporal dynamics among symptom, disease, and unconventional lab test searches on Google Trends, in compared with CDC confirmed cases of LD. The search terms used for the Google Trends analysis between 2011 and 2015 include: (1) “lyme” and “lyme disease” for disease, (2) “tick bite,” “bone pain,” “stiff neck,” “circular rash,” and “brain fog” for symptoms, and (3) “IGENEX” for the alternative lab test. Spatial and temporal analyses illustrate noticeable similar patterns between the search frequency and the actual LD incidence. Beyond basic searches for symptoms or disease terms, we demonstrate the improved utility of Google Trends analysis in discovering spatial and temporal patterns of perceived LD and comparing with the reported LD cases. The public health and medical communities benefit from this research through improved knowledge of undiagnosed patients who are searching for alternative labs to explain lingering symptoms. This study validates the need for further research into Google Trends data and surveillance protocols of diseases characterized by non-specific symptoms, prompting patients to “self-diagnose.” Frontiers Media S.A. 2020-08-14 /pmc/articles/PMC7456861/ /pubmed/32923420 http://dx.doi.org/10.3389/fpubh.2020.00395 Text en Copyright © 2020 Kim, Maxwell and Le. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Kim, Dohyeong
Maxwell, Sarah
Le, Quang
Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends
title Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends
title_full Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends
title_fullStr Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends
title_full_unstemmed Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends
title_short Spatial and Temporal Comparison of Perceived Risks and Confirmed Cases of Lyme Disease: An Exploratory Study of Google Trends
title_sort spatial and temporal comparison of perceived risks and confirmed cases of lyme disease: an exploratory study of google trends
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456861/
https://www.ncbi.nlm.nih.gov/pubmed/32923420
http://dx.doi.org/10.3389/fpubh.2020.00395
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