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Aimee Hurt

Publications and source records attributed to Aimee Hurt.

2 recordsLinked to original sources

Scent detection dogs detect a species of hard tick, Dermacentor albipictus, with comparable accuracy and efficiency to traditional tick drag surveys

Background Accurate surveillance data are critical for addressing tick and tick-borne pathogen risk to human and animal health. Current surveillance methods for detecting invading or expanding tick species are limited in their ability to scale efficiently to state or national levels. In this study we explored the potential use of scent detection dogs to assist field surveys for a hard tick species: Dermacentor albipictus . Methods We used a series of indoor and in situ training simulations to teach scent detection dogs to recognize D. albipictus scent, distinguish tick scent from associated vegetation, and develop a cautious search pattern. After training, we deployed both a scent detection dog survey team and a human-only survey team on transect and surveillance plot surveys then compared the detection rates and efficiency of both methods. Results Scent detection dogs required more time and money to train on field surveys but were comparable to traditional tick drags when accounting for cost per unit area surveyed. There was a lack of agreement on positive (ticks present) versus negative (ticks not present) sites between the two methods, implying that neither method is particularly reliable at detecting D. albipictus . Conclusions Estimating detection bias and false negative rates for tick surveillance methods such as tick drags will be important for accurately evaluating tick-borne disease risk across space and into the future. We found scent detection dogs to be a reasonable alternative sampling approach to consider when ticks are at low abundance or patchily distributed such as during tick range expansion or novel invasions. Scent detection dogs may also be useful for sampling for ticks in areas or along surfaces that are difficult to sample with the traditional tick drag technique like at ports of entry or livestock competitions.

Wyoming

Effectiveness of canine-assisted surveillance and human searches for early detection of invasive spotted lanternfly

Prevention and early detection of invasive species are championed as the most cost-effective and efficient strategies for reducing or preventing negative impacts on ecosystems. Spotted lanternfly (SLF), Lycorma delicatula , is a recently introduced invasive insect whose range in the United States has been expanding rapidly since it was first discovered in Pennsylvania in 2014. Feeding by this planthopper can cause severe impacts on agricultural production, particularly grapes ( Vitis spp.). Human visual surveys are the most common search method employed for detection but can be ineffective due to the insect's cryptic egg masses and low density during early stages of infestation. Therefore, finding alternative early detection methods has become a priority for agencies tasked with addressing SLF management. This study experimentally tested whether trained detector dogs could improve the probability of detecting SLF in both agricultural and forest settings. We surveyed transects in 20 vineyards and their adjacent wooded areas in Pennsylvania and New Jersey, USA, and used a multiscale occupancy model to estimate detection probability achieved by human observers and detection dogs as a function of SLF infestation level, weather, and habitat covariates. We modeled transect-level occupancy of SLF as a function of infestation level, habitat type, topographic position index, and distance to forests. Occupancy probability of SLF was higher on vines within vineyards than in forests, and occupancy declined with increasing distance from forests, which is informative for future search efforts. Detection probability of SLF was lower at forested sites but was higher at high infestation sites. Detection dogs had a lower detection probability than humans in the vineyards, but the detection probability of dogs was >3× greater than that of humans in forested sites. Our study suggests that detection dogs are more effective than human visual searches as an early detection method for SLF in forested areas, and utilizing detector dogs could strengthen SLF early detection efforts. This study demonstrates the potential applicability of using canine-assisted search strategies combined with occupancy models to enhance the surveillance and prevention of other difficult-to-detect invasive species.

New Jersey, Pennsylvania