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Host contributions to Borrelia burgdorferi (Spirochaetales: Spirochaetaceae) infection prevalence in Ixodes scapularis (Acari: Ixodidae) nymphs.

Created on 07 Aug 2026

Authors

Carli Peterson, Erika Gallo, Michael S Allen, Christopher M Kribs

Published in

Journal of medical entomology. Volume 63. Issue 4. Jul 01, 2026.

Abstract

Lyme disease, caused by the bacterium Borrelia burgdorferi (Spirochaetales: Spirochaetaceae) and transmitted by the blacklegged tick, Ixodes scapularis Say (Acari: Ixodidae), in the eastern United States, is the most common vector-borne disease in North America. Human disease risk depends on interactions among ticks and sylvatic hosts, and greater host biodiversity has been hypothesized to reduce risk through the dilution effect. However, the influence of biodiversity varies with community composition, species abundance, and habitat change. We conducted a literature review to compile biological parameter estimates for 15 common host species. These parameters were used in a mathematical model incorporating tick-to-host ratio-dependent host-finding success, allowing for incomplete redistribution of ticks, to assess transmission dynamics in the northeastern United States, where human Lyme disease incidence is high. We evaluated how species richness, evenness, and habitat changes affect nymphal infection prevalence (NIP) and density of infected nymphs (DIN). Our results indicate that many small mammal species play context-dependent roles, acting as dilution hosts in communities of highly competent hosts and as amplification hosts in lower-competence communities. Varying host density revealed "tipping points," where small abundance changes led to communities producing more infected than uninfected ticks. Habitat fragmentation simulations showed that biodiversity can decrease NIP but often increases DIN. Together, these findings provide insight into B. burgdorferi transmission cycles and emphasize the need to consider NIP and DIN jointly when assessing how biodiversity alters transmission dynamics.

PMID:
42565984
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.

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