Lyme borreliosis (LB) occurs when an infected Ixodes tick transmits Borrelia bacteria to humans during a prolonged bite, typically after acquiring the bacteria from small mammals or birds, leading to local and sometimes widespread infection. Because neither a robust surveillance system based on routine data collection nor recent population-based studies quantifying disease burden are available, understanding the local risk of LB in recent years has not been feasible.
Research challenge
The primary objective was to provide a recent and comprehensive overview of LB epidemiology in the Netherlands.
This study faced several research challenges due to the absence of statutory LB reporting in the Netherlands, which meant no robust national surveillance system is available. In this context, the key methodological requirement was a data source with a well-defined denominator (i.e., a clearly observable population at risk over time) and consistent capture of diagnoses within that population.
Relying on GP records also comes with limitations that were not fully mitigated in this study, because doing so would require linkage to other data sources in the PHARMO Data Network (e.g., ambulatory consultations (for specialist diagnoses), clinical laboratory data) and the study prioritized the epidemiology objective over broader care-pathway completeness. As a result, specialist-diagnosed cases may be incompletely captured (e.g., when specialist findings are not consistently communicated back to, or recorded by, the GP). Diagnostic uncertainty was another challenge: inclusion of suspected or probable cases can inflate estimates, and GP diagnostic and testing behavior, such as ordering serology in low-suspicion cases, may increase the risk of misclassification and overestimation. Some patient characteristics are also imperfectly measured in GP-only data—for example, immunocompromised status may be under-recorded if managed primarily in specialist care, and socioeconomic status (SES) is often approximated at neighborhood rather than individual level. Finally, smaller numbers in certain regions can reduce statistical reliability, and unmeasured behavioral/cultural factors (e.g., outdoor activities, tick-awareness efforts) may contribute to observed geographic or SES patterns.
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