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

Frontiers in Public Health

article

Dohyeong Kim¹  Sarah Maxwell¹  Quang Le² 

[1]School of Economic, Political and Policy Sciences, University of Texas at Dallas, United States

[2]Department of Bioengineering, University of Texas at Dallas, United States

关键词: lyme disease;    Google Trends;    spatial;    temporal;    non-specific symptoms;   

DOI  :  10.3389/fpubh.2020.00395

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

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.”.

【 授权许可】

CC BY