Literature DB >> 25364787

Synthesized Population Databases: A Geospatial Database of US Poultry Farms.

Mark C Bruhn, Breda Munoz, James Cajka, Gary Smith, Ross J Curry, Diane K Wagener, William D Wheaton.   

Abstract

The pervasive and potentially severe economic, social, and public health consequences of infectious disease in farmed animals require that plans be in place for a rapid response. Increasingly, agent-based models are being used to analyze the spread of animal-borne infectious disease outbreaks and derive policy alternatives to control future outbreaks. Although the locations, types, and sizes of animal farms are essential model inputs, no public domain nationwide geospatial database of actual farm locations and characteristics currently exists in the United States. This report describes a novel method to develop a synthetic dataset that replicates the spatial distribution of poultry farms, as well as the type and number of birds raised on them. It combines county-aggregated poultry farm counts, land use/land cover, transportation, business, and topographic data to generate locations in the conterminous United States where poultry farms are likely to be found. Simulation approaches used to evaluate the accuracy of this method when compared to that of a random placement alternative found this method to be superior. The results suggest the viability of adapting this method to simulate other livestock farms of interest to infectious disease researchers.

Entities:  

Year:  2012        PMID: 25364787      PMCID: PMC4215551          DOI: 10.3768/rtipress.2012.mr.0023.1201

Source DB:  PubMed          Journal:  Methods Rep RTI Press


  16 in total

1.  Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape.

Authors:  M J Keeling; M E Woolhouse; D J Shaw; L Matthews; M Chase-Topping; D T Haydon; S J Cornell; J Kappey; J Wilesmith; B T Grenfell
Journal:  Science       Date:  2001-10-03       Impact factor: 47.728

2.  Results of epidemic simulation modeling to evaluate strategies to control an outbreak of foot-and-mouth disease.

Authors:  Thomas W Bates; Mark C Thurmond; Tim E Carpenter
Journal:  Am J Vet Res       Date:  2003-02       Impact factor: 1.156

3.  Estimating the kernel parameters of premises-based stochastic models of farmed animal infectious disease epidemics using limited, incomplete, or ongoing data.

Authors:  Chris Rorres; Sky T K Pelletier; Matt J Keeling; Gary Smith
Journal:  Theor Popul Biol       Date:  2010-05-07       Impact factor: 1.570

4.  Modeling spatial and temporal transmission of foot-and-mouth disease in France: identification of high-risk areas.

Authors:  Arnaud Le Menach; Judith Legrand; Rebecca F Grais; Cécile Viboud; Alain-Jacques Valleron; Antoine Flahault
Journal:  Vet Res       Date:  2005 Sep-Dec       Impact factor: 3.683

5.  A proposed methodology to determine accuracy of location and extent of geographically isolated wetlands.

Authors:  Breda Munoz; Virginia M Lesser; John R Dorney; Rick Savage
Journal:  Environ Monit Assess       Date:  2008-12-13       Impact factor: 2.513

6.  Finding the real case-fatality rate of H5N1 avian influenza.

Authors:  F C K Li; B C K Choi; T Sly; A W P Pak
Journal:  J Epidemiol Community Health       Date:  2008-06       Impact factor: 3.710

7.  Impact of spatial clustering on disease transmission and optimal control.

Authors:  Michael J Tildesley; Thomas A House; Mark C Bruhn; Ross J Curry; Maggie O'Neil; Justine L E Allpress; Gary Smith; Matt J Keeling
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-01       Impact factor: 11.205

8.  Stochastic modeling of animal epidemics using data collected over three different spatial scales.

Authors:  Chris Rorres; Sky T K Pelletier; Gary Smith
Journal:  Epidemics       Date:  2011-06       Impact factor: 4.396

9.  Ongoing estimation of the epidemic parameters of a stochastic, spatial, discrete-time model for a 1983-84 avian influenza epidemic.

Authors:  C Rorres; S T K Pelletier; M C Bruhn; G Smith
Journal:  Avian Dis       Date:  2011-03       Impact factor: 1.577

10.  A dynamic, optimal disease control model for foot-and-mouth-disease: II. Model results and policy implications.

Authors:  Mimako Kobayashi; Tim E Carpenter; Bradley F Dickey; Richard E Howitt
Journal:  Prev Vet Med       Date:  2007-02-05       Impact factor: 2.670

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  6 in total

1.  Highly Pathogenic Avian Influenza Virus, Midwestern United States.

Authors:  Chau M Bui; Lauren Gardner; C Raina MacIntyre
Journal:  Emerg Infect Dis       Date:  2016-01       Impact factor: 6.883

2.  Species distribution models: A comparison of statistical approaches for livestock and disease epidemics.

Authors:  Tracey Hollings; Andrew Robinson; Mary van Andel; Chris Jewell; Mark Burgman
Journal:  PLoS One       Date:  2017-08-24       Impact factor: 3.240

3.  Biosecurity and geospatial analysis of mycoplasma infections in poultry farms at Al-Jabal Al-Gharbi region of Libya.

Authors:  Abdulwahab Kammon; Paolo Mulatti; Monica Lorenzetto; Nicola Ferre; Monier Sharif; Ibrahim Eldaghayes; Abdunaser Dayhum
Journal:  Open Vet J       Date:  2017-04-14

4.  Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States.

Authors:  Stefan Sellman; Michael J Tildesley; Christopher L Burdett; Ryan S Miller; Clayton Hallman; Colleen T Webb; Uno Wennergren; Katie Portacci; Tom Lindström
Journal:  PLoS Comput Biol       Date:  2020-02-20       Impact factor: 4.475

5.  Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms.

Authors:  Christopher L Burdett; Brian R Kraus; Sarah J Garza; Ryan S Miller; Kathe E Bjork
Journal:  PLoS One       Date:  2015-11-16       Impact factor: 3.240

6.  Modeling livestock population structure: a geospatial database for Ontario swine farms.

Authors:  Salah Uddin Khan; Terri L O'Sullivan; Zvonimir Poljak; Janet Alsop; Amy L Greer
Journal:  BMC Vet Res       Date:  2018-01-30       Impact factor: 2.741

  6 in total

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