Estimating the density of questing Ixodes scapularis nymphs in the eastern United States using climate and land cover data

Tick-borne diseases pose a persistent and increasing threat to public health. In the United States, the majority of human infections are caused by pathogens spread by the blacklegged tick, Ixodes scapularis. Most infections are reported during the summer months, when nymphal ticks are active in states in the Northeast and Upper Midwest. The density of questing I. scapularis nymphs (DON) provides an estimate for the risk of human encounters with nymphs, but it is a resource intensive metric to obtain from field sampling. Thus, DON estimates are limited in the US national tick surveillance database, the ArboNET Tick Module. We estimated DON across all counties in the eastern US using a zero-inflated negative binomial model utilizing tick surveillance data reported to ArboNET (2004-2023) as well as climate and land cover data. The model estimated generally low DON across the southeastern US and Great Plains states with higher estimates in the Upper Midwest and Northeast regions. We assigned counties to relative acarological encounter risk categories based on estimated DON: zero or lower quartile DON estimates were scored as low risk, whereas inter- and upper-quartile DON estimates were scored as moderate-high risk. Counties with moderate-high DON reported from field sampling were accurately categorized by the model as moderate-high encounter risk (99 % sensitivity). However, 80 % of sampled counties reporting low DON were classified as moderate-high risk (20 % specificity). These misclassified counties were typically situated in recently colonized areas in the Northeast and Upper Midwest and likely indicated areas potentially suitable for tick population expansion. Our model yielded a very high negative predictive value (96 %) indicating the model did very well estimating low relative encounter risk in counties where no or few nymphs were collected, and a fair positive predictive value (60 %) indicated that densities may not have reached an expected peak in some locations, particularly in the Northeast, Upper Midwest, and northern states in the Southeast. Further tick surveillance is needed to evaluate and to refine these predictions. The resulting maps are useful for estimating relative risk of nymphal encounters across the eastern US where field data are sparse and may aid in efforts aimed at promoting the use of personal protective measures in communities that are at risk for nymphal tick encounters.