Evaluating spatial and temporal patterns of tick exposure in the United States using community science data submitted through a smartphone application

Abstract

Research initiatives that engage the public (i.e., community science or citizen science) increasingly provide insights into tick exposures in the United States. However, these data have important caveats, particularly with respect to reported travel history and tick identification. Here, we assessed whether a smartphone application, The Tick App, provides reliable and novel insights into tick exposures across three domains - travel history, 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 of the encounters (51%) consisted of self-reported peri‑domestic exposures, while 37% consisted of self-reported 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 prior to tick detection, whereas an estimated 50-60% of users from smaller metropolitan areas did. Furthermore, we generated tick encounter maps for Dermacentor variabilis and Ixodes scapularis that partially accounted for travel history and overall mirrored previously published species distributions. Finally, we evaluated whether a streamlined three-question sequence (on tick size, feeding status, and color) would inform a simple algorithm to optimize image-based tick identification. Visual aides of tick coloration and size engaged and guided users towards species and life stage classification moderately well, with 56% of one-time submitters correctly selecting photos of D. variabilis adults and 76% of frequent-submitters correctly selecting photos of D. variabilis adults. Together, these results indicate the importance of bolstering the use of smartphone applications to engage community scientists and complement other active and passive tick surveillance systems.

Keywords: Citizen science; Community science; Mobile app; Tick encounters; Tick surveillance; Ticks.