Literature DB >> 33359203

Spatio-temporal variation in environmental features predicts the distribution and abundance of Ixodes scapularis.

Tam Tran1, Melissa A Prusinski2, Jennifer L White2, Richard C Falco3, Vanessa Vinci3, Wayne K Gall4, Keith Tober4, JoAnne Oliver5, Lee Ann Sporn6, Lisa Meehan7, Elyse Banker8, P Bryon Backenson2, Shane T Jensen9, Dustin Brisson10.   

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.
Copyright © 2020 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Distribution; Environmental change; Lyme disease; Predictive models; Ticks

Mesh:

Year:  2020        PMID: 33359203      PMCID: PMC7940570          DOI: 10.1016/j.ijpara.2020.10.002

Source DB:  PubMed          Journal:  Int J Parasitol        ISSN: 0020-7519            Impact factor:   3.981


  53 in total

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