Canine vector-borne disease: mapping and the accuracy of forecasting using big data from the veterinary community

Author:

Self Stella C. W.,Liu Yan,Nordone Shila K.,Yabsley Michael J.,Walden Heather S.,Lund Robert B.,Bowman Dwight D.,Carpenter Christopher,McMahan Christopher S.,Gettings Jenna R.ORCID

Abstract

AbstractDiagnosis, treatment, and prevention of vector-borne disease (VBD) in pets is one cornerstone of companion animal practices. Veterinarians are facing new challenges associated with the emergence, reemergence, and rising incidence of VBD, including heartworm disease, Lyme disease, anaplasmosis, and ehrlichiosis. Increases in the observed prevalence of these diseases have been attributed to a multitude of factors, including diagnostic tests with improved sensitivity, expanded annual testing practices, climatologic and ecological changes enhancing vector survival and expansion, emergence or recognition of novel pathogens, and increased movement of pets as travel companions. Veterinarians have the additional responsibility of providing information about zoonotic pathogen transmission from pets, especially to vulnerable human populations: the immunocompromised, children, and the elderly. Hindering efforts to protect pets and people is the dynamic and ever-changing nature of VBD prevalence and distribution. To address this deficit in understanding, the Companion Animal Parasite Council (CAPC) began efforts to annually forecast VBD prevalence in 2011. These forecasts provide veterinarians and pet owners with expected disease prevalence in advance of potential changes. This review summarizes the fidelity of VBD forecasts and illustrates the practical use of CAPC pathogen prevalence maps and forecast data in the practice of veterinary medicine and client education.

Publisher

Cambridge University Press (CUP)

Subject

Animal Science and Zoology

Reference61 articles.

1. A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Borrelia burgdorferi, causative agent of Lyme disease, in domestic dogs within the contiguous United States

2. National Notifiable Diseases Surveillance System (NNDSS), Centers for Disease Control and Prevention. https://wwwn.cdc.gov/nndss/ (Accessed 5 January 2018).

3. Factors influencing U.S. canine heartworm (Dirofilaria immitis) prevalence

4. United States Food and Drug Administration (2018) Prevent heartworms in dogs, cats, and ferrets year-round. https://www.fda.gov/ForConsumers/ConsumerUpdates/ucm371377.htm (Accessed 3 April 2019).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3