PMID- 29169685
OWN - NLM
STAT- MEDLINE
DCOM- 20180731
LR  - 20220408
IS  - 1873-1716 (Electronic)
IS  - 0167-5877 (Linking)
VI  - 150
DP  - 2018 Feb 1
TI  - Surveillance of porcine reproductive and respiratory syndrome virus in the United 
      States using risk mapping and species distribution modeling.
PG  - 135-142
LID - S0167-5877(17)30008-9 [pii]
LID - 10.1016/j.prevetmed.2017.11.011 [doi]
AB  - Porcine reproductive and respiratory syndrome virus (PRRSv) outbreaks cause 
      significant financial losses to the U.S. swine industry, where the pathogen is 
      endemic. Seasonal increases in the number of outbreaks are typically observed 
      using PRRSv epidemic curves. However, the nature and extent to which demographic 
      and environmental factors influence the risk for PRRSv outbreaks in the country 
      remains unclear. The objective of this study was to develop risk maps for PRRSv 
      outbreaks across the United States (U.S.) and compare ecological dynamics of the 
      disease in five of the most important swine production regions of the country. 
      This study integrates spatial information regarding PRRSv surveillance with 
      relevant demographic and environmental factors collected between 2009 and 2016. 
      We used presence-only Maximum Entropy (Maxent), a species distribution modeling 
      approach, to model the spatial risk of PRRSv in swine populations. Data fitted 
      the selected model relatively well when the modeling approach was conducted by 
      region (training and testing AUCs<0.75). All of the Maxent models selected 
      identified high-risk areas, with probabilities greater than 0.5. The relative 
      contribution of pig density to PRRSv risk was highest in pig-densely populated 
      areas (Minnesota, Iowa and North Carolina), whereas climate and land cover were 
      important in areas with relatively low pig densities (Illinois, Indiana, South 
      Dakota, Nebraska, Kansas, Oklahoma, Colorado, and Texas). Although many previous 
      studies associated the risk of PRRSv with high pig density and climatic factors, 
      the study here quantifies, for the first time in the peer-reviewed literature, 
      the spatial variation and relative contribution of these factors across different 
      swine production regions in the U.S. The results will help in the design and 
      implement of early detection, prevention, and control strategies for one of the 
      most devastating diseases affecting the swine industry in the U.S.
CI  - Copyright (c) 2017 Elsevier B.V. All rights reserved.
FAU - Alkhamis, Moh A
AU  - Alkhamis MA
AD  - Department of Veterinary Population Medicine, College of Veterinary Medicine, 
      University of Minnesota, St. Paul, USA; Faculty of Public Heath, Health Sciences 
      Center, Kuwait University, Kuwait. Electronic address: malkahmi@umn.edu.
FAU - Arruda, Andreia G
AU  - Arruda AG
AD  - Department of Veterinary Preventive Medicine, College of Veterinary Medicine, The 
      Ohio State University, Columbus, USA.
FAU - Vilalta, Carles
AU  - Vilalta C
AD  - Department of Veterinary Population Medicine, College of Veterinary Medicine, 
      University of Minnesota, St. Paul, USA.
FAU - Morrison, Robert B
AU  - Morrison RB
AD  - Department of Veterinary Population Medicine, College of Veterinary Medicine, 
      University of Minnesota, St. Paul, USA.
FAU - Perez, Andres M
AU  - Perez AM
AD  - Department of Veterinary Population Medicine, College of Veterinary Medicine, 
      University of Minnesota, St. Paul, USA.
LA  - eng
PT  - Journal Article
DEP - 20171116
PL  - Netherlands
TA  - Prev Vet Med
JT  - Preventive veterinary medicine
JID - 8217463
SB  - IM
MH  - Animal Husbandry/*methods
MH  - Animals
MH  - Disease Outbreaks/*veterinary
MH  - Epidemiological Monitoring/*veterinary
MH  - Geographic Mapping
MH  - Models, Theoretical
MH  - Porcine Reproductive and Respiratory Syndrome/*epidemiology/virology
MH  - Porcine respiratory and reproductive syndrome virus/physiology
MH  - Risk Factors
MH  - Swine
MH  - United States/epidemiology
OTO - NOTNLM
OT  - Climate
OT  - Maximum entropy
OT  - PRRSv
OT  - Pig density
OT  - Risk mapping
OT  - Swine production systems
EDAT- 2017/11/25 06:00
MHDA- 2018/08/01 06:00
CRDT- 2017/11/25 06:00
PHST- 2017/01/15 00:00 [received]
PHST- 2017/05/11 00:00 [revised]
PHST- 2017/11/09 00:00 [accepted]
PHST- 2017/11/25 06:00 [pubmed]
PHST- 2018/08/01 06:00 [medline]
PHST- 2017/11/25 06:00 [entrez]
AID - S0167-5877(17)30008-9 [pii]
AID - 10.1016/j.prevetmed.2017.11.011 [doi]
PST - ppublish
SO  - Prev Vet Med. 2018 Feb 1;150:135-142. doi: 10.1016/j.prevetmed.2017.11.011. Epub 
      2017 Nov 16.