Assessing public tick identification ability and tick bite riskiness using passive photograph-based crowdsourced tick surveillance
Date of Original Version
Tick identification is critical for assessing disease risk from a tick bite and for determining requisite treatment. Data from the University of Rhode Island's TickEncounter Resource Center's photo-based surveillance system, TickSpotters, indicate that users incorrectly identified their submitted specimen 83% of the time. Of the top four most commonly submitted tick species, western blacklegged ticks (Ixodes pacificus Cooley & Kohls [Ixodida: Ixodidae]) had the largest proportion of unidentified or misidentified submissions (87.7% incorrectly identified to species), followed by lone star ticks (Amblyomma americanum Linneaus [Ixodida: Ixodidae]; 86.8% incorrect), American dog ticks (Dermacentor variabilis Say [Ixodida: Ixodidae]; 80.7% incorrect), and blacklegged ticks (Ixodes scapularis Say [Ixodida: Ixodidae]; 77.1% incorrect). More than one quarter of participants (26.3%) submitted photographs of ticks that had been feeding for at least 2.5 d, suggesting heightened risk. Logistic regression generalized linear models suggested that participants were significantly more likely to misidentify nymph-stage ticks than adult ticks (odds ratio [OR] = 0.40, 95% confidence interval [CI]: 0.23, 0.68, P < 0.001). Ticks reported on pets were more likely to be identified correctly than those found on humans (OR = 1.07, 95% CI: 1.01-2.04, P < 0.001), and ticks feeding for 2.5 d or longer were more likely to be misidentified than those having fed for one day or less (OR = 0.43, 95% CI: 0.29-0.65, P < 0.001). State and region of residence and season of submission did not contribute significantly to the optimal model. These findings provide targets for future educational efforts and underscore the value of photograph-based tick surveillance to elucidate these knowledge gaps.
Publication Title, e.g., Journal
Journal of Medical Entomology
Kopsco, Heather L., Roland J. Duhaime, and Thomas N. Mather. "Assessing public tick identification ability and tick bite riskiness using passive photograph-based crowdsourced tick surveillance." Journal of Medical Entomology 58, 2 (2021). doi: 10.1093/jme/tjaa196.