Changing Trends in Age and Sex Distributions of Lyme Disease—United States, 1992-2016. (July 2022)

• Record Type: Journal Article
• Authors: Kugeler, Kiersten J.; Mead, Paul S.; Schwartz, Amy M.; Hinckley, Alison F.
• Is Part Of: Public health reports. Volume 137:Number 4(2022)
• Page Start: 655
• Page End: 659
• Publication Date: 2022-07
• Subjects: Lyme disease -- epidemiology -- surveillance -- demographic; Public health -- United States -- Periodicals; 614.0973
• DOI: 10.1177/00333549211026777
• Languages: English
• ISSNs: 0033-3549

Abstract

Lyme disease is the most common vector-borne disease in the United States and is characterized by a bimodal age distribution and male predominance. We examined trends in reported cases during a 25-year period to describe changes in the populations most affected by Lyme disease in the United States. We examined demographic characteristics of people with confirmed cases of Lyme disease reported to the Centers for Disease Control and Prevention during 1992-2016 through the National Notifiable Diseases Surveillance System. We grouped cases into 5-year periods (1992-1996, 1997-2001, 2002-2006, 2007-2011, 2012-2016). We calculated the average annual incidence by age and sex and used incidence rate ratios (IRRs) to describe changes in Lyme disease incidence by age and sex over time. We converted patient age at time of illness into patient birth year to ascertain disease patterns according to birth cohorts. The incidence of Lyme disease in the United States doubled from 1992-1996 to 2012-2016 (IRR = 1.74; 95% CI, 1.70-1.78) and increased disproportionately among males; IRRs were 39%-89% higher among males than among females for most age groups. During the study period, children aged 5-9 years were most frequently and consistently affected. In contrast, the average age of adults with Lyme disease increased over time; of all adults, people born during 1950-1964 were the most affected by Lyme disease. Our findings suggest that age-related behaviors and susceptibilities may drive infections among children, and the shifting peak among adults likely reflects a probability proportional to the relative size of the baby boom population. These findings can inform targeted and efficient public health education and intervention efforts.