Mapping the Distribution of Lyme Disease in the Mid-Atlantic Region Using Electronic Health Data

Plos One, (Lantos, P. M., et al.)  5.31.2024 published, “Mapping the distribution of Lyme disease at a mid-Atlantic site in the United States using electronic health data.” The study discusses a geospatial analysis of Lyme disease cases using electronic medical records from the Johns Hopkins Hospital in Maryland. The study aims to assess the suitability of electronic medical record (EMR) data for retrospective surveillance of Lyme disease and attempts to map the probability of Lyme disease within 100 km of the Hospital. 

It’s noted by the study that the geographic spread of Lyme disease cases seems to be increasing, and in order to understand its potential range, epidemiologic studies are essential. However, these studies depend on passive public health case reporting and entomologic surveillance of the disease’s causative agent and its tick vector, both of which have their limitations.

The study focuses on individuals with positive Lyme disease tests and corresponding diagnostic codes, along with those referred for Lyme disease evaluation from the Johns Hopkins Health System between the years 2000 and 2013. The study used the patients address information from the John Hopkins Health system and found environmental data from the 2011 National Land Cover Database to determine the land type, such as forests and wetlands. Using this data, researchers found the highest probability of Lyme disease was observed in the north and west of Baltimore, with the probability varying by as much as 30-fold. Adjustment for demographic and ecological variables partially lessened this spatial gradient, but did not change the overall distribution of high-risk areas.

There are, however, several limitations to this study, including:

• It couldn’t include patients with early Lyme disease, as they are typically diagnosed without serologic testing in primary care settings.
• The threshold to refer to specialist centers might vary with distance, introducing potential bias.
• Residential addresses may not accurately represent tick exposure sites, though most Lyme cases are acquired near home.

Even with these limitations, the analysis supports the effectiveness of using electronic medical record data for Lyme disease surveillance and highlights the significant geographic variability in disease risk. It emphasizes the need for enhanced surveillance methods to better understand and manage the endemic range of Lyme disease.

For More Information: 

Read the Plos One Article here.

Read more about Cases, Stats, Maps, and Graphs on Lyme disease on the LDA website here.

Read more about mapping Lyme disease cases from LDA’s Guest Blog by Sarah Maxwell, PhD.