Predicting the risk of Lyme borreliosis after a tick bite, using a structural equation model

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Abstract

Background: Understanding and quantification of the risk of Lyme borreliosis after a tick bite can aid development of prevention strategies against Lyme borreliosis. Methods: We used 3,525 single tick bite reports from three large prospective studies on the transmission risk of tick-borne pathogens to humans, with 50 reports of Lyme borreliosis during the follow-up period, among 1,973 reports with known outcome. A structural equation model was applied to estimate the risk of Lyme borreliosis after a tick bite, and quantify the influence of: developmental stage of the tick, detection of Borrelia burgdorferi s.l. DNA in the tick by PCR, tick engorgement, patient-estimated duration of tick attachment, and patient age. Results: The overall risk of developing Lyme borreliosis after a tick bite was 2.6% (95%CI 1.4–5.1). The risk increased with: - Tick engorgement: 1.4% (95%CI 0.7%-2.3%) for low engorgement to 5.5% (95%CI 2.8%-9.2%) for substantially engorged ticks; - Rising patient-estimated tick attachment duration: 2.0% (95%CI 1.3%-2.8%) after <12 hours, to 5.2% (95%CI 3.0%-8.9%) after 4 days; - Detection of Borrelia burgdorferi s.l. DNA in ticks: 6.7% (95%CI 3.6%-13.5%), versus 1.4% (95%CI 0.7%-2.9%) when ticks tested negative. The highest observed risk of Lyme borreliosis was 14.4% (95%CI 6.8%-24.6%) after one tick bite of a substantially engorged tick that tested positive for Borrelia burgdorferi s.l. DNA, which corresponds to one new case of Lyme borreliosis per 7 (95%CI 4–15) of such tick bites. Conclusions: An individual’s risk of Lyme borreliosis after a tick bite can be predicted with tick engorgement, patient-estimated duration of tick attachment, and detection of Borrelia burgdorferi s.l. DNA in the tick.

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Hofhuis, A., Van De Kassteele, J., Sprong, H., Van Den Wijngaard, C. C., Harms, M. G., Fonville, M., … Van Pelt, W. (2017). Predicting the risk of Lyme borreliosis after a tick bite, using a structural equation model. PLoS ONE, 12(7). https://doi.org/10.1371/journal.pone.0181807

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