Spatio-temporal variation in environmental features predicts the distribution and abundance of Ixodes scapularis. Issue 4 (March 2021) - Tran, Tam; Prusinski, Melissa A.; White, Jennifer L.; Falco, Richard C.; Vinci, Vanessa; Gall, Wayne K.; Tober, Keith; Oliver, JoAnne; Sporn, Lee Ann; Meehan, Lisa; Banker, Elyse; Backenson, P. Bryon; et al.
Graphical abstract: Highlights: Nymphal tick occurrence and abundance are increasing across New York State, USA. Nymphal demography corresponds with the geographic expansion of Lyme disease. Environmental drivers of spatiotemporal changes in nymph populations were identified. Models accurately predict nymphal population demography in future years. Abstract: Many species have experienced dramatic changes in both geographic range and population sizes in recent history. Increases in the geographic range or population size of disease vectors have public health relevance as these increases often precipitate the emergence of infectious diseases in human populations. Accurately identifying environmental factors affecting the biogeographic patterns of vector species is a long-standing analytical challenge, stemming from a paucity of data capturing periods of rapid changes in vector demographics. We systematically investigated the occurrence and abundance of nymphal Ixodes scapularis ticks at 532 sampling locations throughout New York State (NY), USA, between 2008 and 2018, a time frame that encompasses the emergence of diseases vectored by these ticks. Analyses of these field-collected data demonstrated a range expansion into northern and western NY during the last decade. Nymphal abundances increased in newly colonised areas, while remaining stable in areas with long-standing populations over the last decade. These trends in the geographic range and abundance of nymphs correspond to both the geographic expansion of human Lyme disease cases and increases in incidence rates. Analytic models fitted to these data incorporating time, space, and environmental factors, accurately identified drivers of the observed changes in nymphal occurrence and abundance. These models accounted for the spatial and temporal variation in the occurrence and abundance of nymphs and can accurately predict nymphal population patterns in future years. Forecasting disease risk at fine spatial scales prior to the transmission season can influence both public health mitigation strategies and individual behaviours, potentially impacting tick-borne disease risk and subsequently human disease incidence.