Evaluating spatial and temporal patterns of tick encounters using community science data submitted through a smartphone application

Research Square (Research Square)(2022)

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摘要
Abstract Research initiatives that engage the public (i.e., community science) increasingly provide insights into tick exposures in the United States. However, these data have limitations, particularly with respect to reported travel history and tick identification. Here, we assessed whether The Tick App provides reliable and novel insights into tick exposures across three domains—travel history and habitat exposure, broad spatial and temporal patterns of species-specific encounters, and tick identification. During 2019–2021, we received 11,424 tick encounter submissions from across the United States, with nearly all generated in the Midwest and Northeast regions. Encounters were predominantly with human hosts (71%); although one-fourth of ticks were found on animals. Half (51%) of the reported encounters resulted from peri-domestic exposures, while 37% were recreational exposures. Using phone-based location services, we detected differences in travel history outside of the users’ county of residence along an urbanicity gradient. Approximately 75% of users from large metropolitan and rural counties had travel out-of-county in the four days preceding tick detection, whereas an estimated 50–60% of users from suburban or smaller metropolitan areas did. Furthermore, we generated tick encounter maps for Dermacentor variabilis and Ixodes scapularis that accounted for travel history to the extent possible—overall mirroring previously published species distributions, while revealing 45 counties with new reports of D. variabilis exposures. Finally, using photo submissions, prompts of tick coloration and size engaged and guided users towards species and life stage classification moderately well, with 60% of users correctly identifying D. variabilis adults and 46% correctly identifying I. scapularis adults. Together, these results indicate the importance of bolstering the use of mobile applications to engage community scientists and complement other methods of active and passive tick surveillance.
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关键词
tick encounters,community science data,temporal patterns
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