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Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes
Author(s) -
Katharine S. Walter,
Kim M. Pepin,
Colleen T. Webb,
Holly Gaff,
Peter J. Krause,
Virginia E. Pitzer,
Maria A. DiukWasser
Publication year - 2016
Publication title -
proceedings of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2016.0834
Subject(s) - enzootic , babesiosis , biological dispersal , lyme disease , tick borne disease , biology , ixodes , tick , ecology , spatial epidemiology , occupancy , vector (molecular biology) , borrelia burgdorferi , transmission (telecommunications) , epidemiology , environmental health , virology , population , medicine , immunology , virus , biochemistry , electrical engineering , antibody , engineering , gene , recombinant dna
Modelling the spatial spread of vector-borne zoonotic pathogens maintained in enzootic transmission cycles remains a major challenge. The best available spatio-temporal data on pathogen spread often take the form of human disease surveillance data. By applying a classic ecological approach-occupancy modelling-to an epidemiological question of disease spread, we used surveillance data to examine the latent ecological invasion of tick-borne pathogens. Over the last half-century, previously undescribed tick-borne pathogens including the agents of Lyme disease and human babesiosis have rapidly spread across the northeast United States. Despite their epidemiological importance, the mechanisms of tick-borne pathogen invasion and drivers underlying the distinct invasion trajectories of the co-vectored pathogens remain unresolved. Our approach allowed us to estimate the unobserved ecological processes underlying pathogen spread while accounting for imperfect detection of human cases. Our model predicts that tick-borne diseases spread in a diffusion-like manner with occasional long-distance dispersal and that babesiosis spread exhibits strong dependence on Lyme disease.

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