RESEARCH TRIANGLE PARK — Researchers at RTI International are working to identifying high-risk areas for Lyme disease in the United States.

Epidemiologists Donal Bisanzio, Ph.D. and Richard Reithinger, Ph.D., researchers at the RTP-based non-profit research institute, in collaboration with Maria Pilar Fernandez, Ph.D and Maria Diuk-Wasser, Columbia University, Ph.D, analyzed publicly available data on Lyme disease to show the geographic spread of the disease across a 17-year period.

The occurrence of Lyme disease, a tick-borne illness, has continued to increase across the U.S. since the year 2000. If left untreated, Lyme disease can lead to life-lasting infection in the joints, nervous system and even the heart.

About 30,000 cases of Lyme disease are reported each year in the United States, yet it is estimated that up to 270,000 cases go unreported. The results of their analyses are published in the Journal of the American Medical Association (JAMA) Network Open, a peer-reviewed journal. The article shows the probability of counties of the Northeastern U.S. to report Lyme disease cases. The results of the study could be used to identify counties in which no cases have been reported most likely due to under-reporting.

“The research we’ve compiled is important information that can be used to further estimate the spread of the disease beyond our study area,” said Donal Bisanzio, lead author and Senior Epidemiologist at RTI, in a statement. “We believe that the difference between our results and the data currently available shows that underreporting could lead to a delay in a county reporting its first case of Lyme disease.”

The researchers studied nearly 500,000 cases of Lyme disease reported to the Centers for Disease Control (CDC) from different counties across the U.S. during a 17-year period from 2000 to 2017 and used the data to create a predictive model to show the likelihood of a county to report the tick-borne illness.

“Our model is the first to take into consideration that although someone is reporting the disease to the CDC from the county in which they live, they could have been exposed to the agent originally in another county,” said Bisanzio.

Models have been created in the past to identify the spread in certain parts of the U.S., but the new model expands the geographic scope to most areas in the U.S. where the disease is considered to occur. The new approach will help health officials focus on emerging areas for potential Lyme disease cases based on ecological and human factors, including optimizing active surveillance of disease cases and tick populations to increase early case detection as well as improving sensitization of the general population and medical community to the risk of tick exposure and Lyme disease.

Counties in which no cases have currently been recorded can use this model to understand if they are at risk for Lyme disease emergence. In the future, the model can be geographically expanded to include updated information of the expansion of Lyme disease and forecasting disease risk for additional counties.