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Comparative ecological analysis and predictive modeling of tick-borne pathogens

<p>Tick-borne diseases constitute the predominant vector-borne health threat in North America. Recent observations have noted a significant expansion in the range of the black-legged tick (<em>Ixodes scapularis</em> Say, Acari: Ixodidae), alongside a rise in the incidence of diseases caused by its vectored pathogens: <em>Borrelia burgdorferi</em> (Spirochaetales: Spirochaetaceae), <em>Babesia microti</em> (Piroplasmida: Babesiidae), and <em>Anaplasma phagocytophilium</em> (Rickettsiales: Anaplasmataceae), the causative agents of Lyme disease, babesiosis, and anaplasmosis, respectively. Prior research identified environmental features that influence the ecological dynamics of <em>I. scapularis</em> and <em>B. burgdorferi</em> that can be used to predict the distribution and abundance of these organisms, and thus Lyme disease risk. In contrast, there is a paucity of research into the environmental determinants of <em>B. microti</em> and <em>A. phagocytophilium</em>. Here we use over a decade of surveillance data to model the impact of environmental features on the infection prevalence of these increasingly common human pathogens in ticks across New York State (NYS). Our findings reveal a consistent northward and westward expansion of <em>B. microti</em> in NYS from 2009 to 2019, while the range of <em>A. phagocytophilum</em> varied at fine spatial scales. We constructed biogeographic models using data from over 1000 site-year visits and encompassing more than 250 environmental variables to accurately forecast infection prevalence for each pathogen to future years that were not included in model training. Several environmental features were identified to have divergent effects on the pathogens, revealing potential ecological differences governing their distribution and abundance. These validated biogeographic models are immediately useful for disease prevention efforts.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
12
Access
12
Reuse readiness
0
Engagement
12

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