Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data

Paul M Lantos; Mark Janko; Lise E Nigrovic; Felicia Ruffin; Takaaki Kobayashi; Yvonne Higgins; Paul G Auwaerter

doi:10.1371/journal.pone.0301530

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Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data

Journal article

Open access

Peer reviewed

Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data

Paul M Lantos, Mark Janko, Lise E Nigrovic, Felicia Ruffin, Takaaki Kobayashi, Yvonne Higgins and Paul G Auwaerter

PloS one, Vol.19(5), e0301530

05/31/2024

DOI: 10.1371/journal.pone.0301530

PMCID: PMC11142662

PMID: 38820472

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Abstract

Lyme disease is a spatially heterogeneous tick-borne infection, with approximately 85% of US cases concentrated in the mid-Atlantic and northeastern states. Surveillance for Lyme disease and its causative agent, including public health case reporting and entomologic surveillance, is necessary to understand its endemic range, but currently used case detection methods have limitations. To evaluate an alternative approach to Lyme disease surveillance, we have performed a geospatial analysis of Lyme disease cases from the Johns Hopkins Health System in Maryland. We used two sources of cases: a) individuals with both a positive test for Lyme disease and a contemporaneous diagnostic code consistent with a Lyme disease-related syndrome; and b) individuals referred for a Lyme disease evaluation who were adjudicated to have Lyme disease. Controls were individuals from the referral cohort judged not to have Lyme disease. Residential address data were available for all cases and controls. We used a hierarchical Bayesian model with a smoothing function for a coordinate location to evaluate the probability of Lyme disease within 100 km of Johns Hopkins Hospital. We found that the probability of Lyme disease was greatest in the north and west of Baltimore, and the local probability that a subject would have Lyme disease varied by as much as 30-fold. Adjustment for demographic and ecological variables partially attenuated the spatial gradient. Our study supports the suitability of electronic medical record data for the retrospective surveillance of Lyme disease.

Electronic Health Records

Adolescent

Adult

Aged

Bayes Theorem

Child

Female

Humans

Lyme Disease - diagnosis

Lyme Disease - epidemiology

Male

Maryland - epidemiology

Mid-Atlantic Region - epidemiology

Middle Aged

United States - epidemiology

Young Adult

Details

Title: Subtitle: Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data
Creators: Paul M Lantos - Duke University
Mark Janko - Duke Global Health Institute, Durham, NC, United States of America
Lise E Nigrovic - Boston Children's Hospital
Felicia Ruffin - Duke University School of Medicine
Takaaki Kobayashi - University of Iowa
Yvonne Higgins - Johns Hopkins University School of Medicine
Paul G Auwaerter - Johns Hopkins University School of Medicine
Resource Type: Journal article
Publication Details: PloS one, Vol.19(5), e0301530
DOI: 10.1371/journal.pone.0301530
PMID: 38820472
PMCID: PMC11142662
ISSN: 1932-6203
eISSN: 1932-6203
Language: English
Date published: 05/31/2024
Academic Unit: Infectious Diseases; Internal Medicine
Record Identifier: 9984635160202771

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