Modeling the Sensitivity of Blacklegged Ticks (Ixodes scapularis) to Temperature and Land Cover in the Northeastern United States

Abstract

The prevalence of Lyme disease and other tick-borne diseases is dramatically increasing across the United States. While the rapid rise in Lyme disease is clear, the causes of it are not. Modeling Ixodes scapularis Say (Acari: Ixodidae), the primary Lyme disease vector in the eastern United States, presents an opportunity to disentangle the drivers of increasing Lyme disease, including climate, land cover, and host populations. We improved upon a recently developed compartment model of ordinary differential equations that simulates I. scapularis growth, abundance, and infection with Borrelia burgdorferi (Spirochaetales: Spirochaetaceae) by adding land cover effects on host populations, refining the representation of growth stages, and evaluating output against observed data. We then applied this model to analyze the sensitivity of simulated I. scapularis dynamics across temperature and land cover in the northeastern United States. Specifically, we ran an ensemble of 232 simulations with temperature from Hanover, New Hampshire and Storrs, Connecticut, and land cover from Hanover and Cardigan in New Hampshire, and Windsor and Danielson in Connecticut. Consistent with observations, simulations of I. scapularis abundance are sensitive to temperature, with the warmer Storrs climate significantly increasing the number of questing I. scapularis at all growth stages. While there is some variation in modeled populations of I. scapularis infected with B. burgdorferi among land cover distributions, our analysis of I. scapularis response to land cover is limited by a lack of observations describing host populations, the proportion of hosts competent to serve as B. burgdorferi reservoirs, and I. scapularis abundance.

Keywords: Ixodidae; Lyme disease; ecology; modeling; public health entomology.