A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Ehrlichia species in domestic dogs within the contiguous United States
作者: Yan LiuRobert B. LundShila K. NordoneMichael J. YabsleyChristopher S. McMahan
作者单位: 1Clemson University
2North Carolina State University
3The University of Georgia
刊名: Parasites & Vectors, 2017, Vol.10 (1)
来源数据库: Springer Nature Journal
DOI: 10.1186/s13071-017-2068-x
关键词: AutoregressionCAR ModelEhrlichiosisHead-bangingKrigingPrevalenceSpatio-temporal modeling
英文摘要: Dogs in the United States are hosts to a diverse range of vector-borne pathogens, several of which are important zoonoses. This paper describes factors deemed to be significantly related to the prevalence of antibodies to Ehrlichia spp. in domestic dogs, including climatic conditions, geographical factors, and societal factors. These factors are used in concert with a spatio-temporal model to construct an annual seroprevalence forecast. The proposed method of forecasting and an assessment of its fidelity are described.
原始语种摘要: Dogs in the United States are hosts to a diverse range of vector-borne pathogens, several of which are important zoonoses. This paper describes factors deemed to be significantly related to the prevalence of antibodies to Ehrlichia spp. in domestic dogs, including climatic conditions, geographical factors, and societal factors. These factors are used in concert with a spatio-temporal model to construct an annual seroprevalence forecast. The proposed method of forecasting and an assessment of its fidelity are described.
全文获取路径: Springer Nature  (合作)
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来源刊物:
影响因子:3.246 (2012)

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关键词翻译
关键词翻译
  • temporal 现世的
  • contiguous 连续
  • forecasting 预报
  • banging 消音器内爆炸
  • modeling 制祝型
  • domestic 国产的
  • zoonoses 人畜共患病
  • geographical 地理的
  • annual 年刊
  • CAR CARriage-RETurn