Stochastic modeling of animal epidemics using data collected over three different spatial scales
Abstract A stochastic, spatial, discrete-time, SEIR model of avian influenza epidemics among poultry farms in Pennsylvania is formulated. Using three different spatial scales wherein all the birds within a single farm, ZIP code, or county are clustered into a single point, we obtain three different...
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| Veröffentlicht in: | Epidemics 2011-06, Vol.3 (2), p.61-70 |
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| creator | Rorres, Chris Pelletier, Sky T.K Smith, Gary |
| description | Abstract A stochastic, spatial, discrete-time, SEIR model of avian influenza epidemics among poultry farms in Pennsylvania is formulated. Using three different spatial scales wherein all the birds within a single farm, ZIP code, or county are clustered into a single point, we obtain three different views of the epidemics. For each spatial scale, two parameters within the viral-transmission kernel of the model are estimated using simulated epidemic data. We show that simulated epidemics modeled using data collected on the farm and ZIP-code levels behave similar to the actual underlying epidemics, but this is not true using data collected on the county level. Such analyses of data collected on different spatial scales are useful in formulating intervention strategies to control an ongoing epidemic (e.g., vaccination schedules and culling policies). |
| doi_str_mv | 10.1016/j.epidem.2011.02.003 |
| format | Article |
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Using three different spatial scales wherein all the birds within a single farm, ZIP code, or county are clustered into a single point, we obtain three different views of the epidemics. For each spatial scale, two parameters within the viral-transmission kernel of the model are estimated using simulated epidemic data. We show that simulated epidemics modeled using data collected on the farm and ZIP-code levels behave similar to the actual underlying epidemics, but this is not true using data collected on the county level. 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Such analyses of data collected on different spatial scales are useful in formulating intervention strategies to control an ongoing epidemic (e.g., vaccination schedules and culling policies).</description><subject>Animal Husbandry</subject><subject>Animals</subject><subject>Avian influenza</subject><subject>Computer Simulation</subject><subject>Disease Models, Animal</subject><subject>Disease Outbreaks</subject><subject>Estimators</subject><subject>Geography</subject><subject>Infectious Disease</subject><subject>Influenza in Birds - epidemiology</subject><subject>Influenza in Birds - transmission</subject><subject>Internal Medicine</subject><subject>Likelihood Functions</subject><subject>Mathematical models</subject><subject>Models, Biological</subject><subject>Parameter estimation</subject><subject>Pennsylvania - epidemiology</subject><subject>Poultry</subject><subject>Stochastic Processes</subject><subject>ZIP-codes</subject><issn>1755-4365</issn><issn>1878-0067</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUk1v1DAQtRCIlsI_QMg3TgkeO46TCxKqyodUqYe2Z-O1J10vSbzYzkr99zjaUqAXfLHlmffezLwh5C2wGhi0H3Y17r3DqeYMoGa8Zkw8I6fQqa5irFXPy1tJWTWilSfkVUq78tsAiJfkhIOUXCh2Sr5f52C3JmVv6RQcjn6-o2GgZvaTGelRwttEl7RGnMmG2jCOaDM6Gg4Yad5GROr8MGDEOdO0N9kXbLJmxPSavBjMmPDNw31Gbj9f3Jx_rS6vvnw7_3RZWQkqV0ZIBwNrBicMtIY7ayWXYBB6JzZOuda63rhOSAEtx970DQ4922CPvdy4VpyRj0fe_bKZ0NlSSTSj3sfSR7zXwXj9b2T2W30XDlqwTnHgheD9A0EMPxdMWU8-WRxHM2NYku7aXiroGZTM5phpY0gp4vCoAkyv3uidPg5Or95oxnXxpsDe_V3hI-i3GX9awDKng8eok_U4W3Q-lnlrF_z_FJ4S2OKnLz78wHtMu7DEuXigQacC0NfrfqzrAcDKUUr8AuGvufE</recordid><startdate>20110601</startdate><enddate>20110601</enddate><creator>Rorres, Chris</creator><creator>Pelletier, Sky T.K</creator><creator>Smith, Gary</creator><general>Elsevier B.V</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20110601</creationdate><title>Stochastic modeling of animal epidemics using data collected over three different spatial scales</title><author>Rorres, Chris ; Pelletier, Sky T.K ; Smith, Gary</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c517t-a35d1f04fd3a16a2dcc5251ae19d3bd7d6cd9ad8353162e9a94ef90be9e95bd63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Animal Husbandry</topic><topic>Animals</topic><topic>Avian influenza</topic><topic>Computer Simulation</topic><topic>Disease Models, Animal</topic><topic>Disease Outbreaks</topic><topic>Estimators</topic><topic>Geography</topic><topic>Infectious Disease</topic><topic>Influenza in Birds - epidemiology</topic><topic>Influenza in Birds - transmission</topic><topic>Internal Medicine</topic><topic>Likelihood Functions</topic><topic>Mathematical models</topic><topic>Models, Biological</topic><topic>Parameter estimation</topic><topic>Pennsylvania - epidemiology</topic><topic>Poultry</topic><topic>Stochastic Processes</topic><topic>ZIP-codes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rorres, Chris</creatorcontrib><creatorcontrib>Pelletier, Sky T.K</creatorcontrib><creatorcontrib>Smith, Gary</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Epidemics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rorres, Chris</au><au>Pelletier, Sky T.K</au><au>Smith, Gary</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stochastic modeling of animal epidemics using data collected over three different spatial scales</atitle><jtitle>Epidemics</jtitle><addtitle>Epidemics</addtitle><date>2011-06-01</date><risdate>2011</risdate><volume>3</volume><issue>2</issue><spage>61</spage><epage>70</epage><pages>61-70</pages><issn>1755-4365</issn><eissn>1878-0067</eissn><abstract>Abstract A stochastic, spatial, discrete-time, SEIR model of avian influenza epidemics among poultry farms in Pennsylvania is formulated. 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| ispartof | Epidemics, 2011-06, Vol.3 (2), p.61-70 |
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| language | eng |
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| source | MEDLINE; Access via ScienceDirect (Elsevier) |
| subjects | Animal Husbandry Animals Avian influenza Computer Simulation Disease Models, Animal Disease Outbreaks Estimators Geography Infectious Disease Influenza in Birds - epidemiology Influenza in Birds - transmission Internal Medicine Likelihood Functions Mathematical models Models, Biological Parameter estimation Pennsylvania - epidemiology Poultry Stochastic Processes ZIP-codes |
| title | Stochastic modeling of animal epidemics using data collected over three different spatial scales |
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