Socio-geographic factors associated with Lyme disease in children
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Objective Lyme disease diagnosis in children is challenging due to atypical presentations and testing limitations. We sought to evaluate the association between Lyme disease and socio-geographic risk factors in children. Materials and methods We enrolled children undergoing evaluation for acute Lyme disease at one of eight Pedi Lyme Net pediatric emergency departments located in high Lyme disease incidence states over a ten-year period (2015-2024). We defined a case of Lyme disease with an erythema migrans (EM) lesion or a positive two-tier serology result in a child with signs and/or symptoms of acute disease. We linked each child’s primary residential county to the following factors: urban-rural residence, socioeconomic status, population-level disease incidence, wildland-urban interface, and “Lyme disease” Google searches. We performed a multi-level logistic regression analysis to evaluate associations between Lyme disease and county factors after adjusting for individual demographics. Results Among 5,529 children enrolled, 1,396 (25.2%) had Lyme disease: 101 (7.2%) with early-localized disease, 584 (41.8%) with early-disseminated disease, and 711 (50.9%) with late-disseminated disease. Rural residence (aOR 1.9, 95% CI 1.3–2.9), higher socioeconomic advantage (aOR 1.3, 95% CI 1.1–1.4), more “Lyme disease” Google searches (aOR 1.1, 95% CI 1.0–1.2), and higher wildland urban interface (aOR 1.2, 95% CI: 1.0–1.4) were independently associated with Lyme disease. Conclusion Incorporating socio-geographic factors alongside clinical data may augment diagnostic risk assessment in children with suspected Lyme disease. However, these factors should be incorporated carefully to ensure clinical assessments are not based on a child’s geographic location alone.
Source: medRxiv
Language: English
Subfield: Parasitology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7161813264