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A flexible tool for the assessment of the economic cost of pig disease in growers and finishers at farm level
Pigmeat is the most consumed red meat globally and consumption is expected to continue to increase. The sector is faced by the risk of epidemic and endemic disease impacts and other adverse influences. The aim of this study was to develop a dynamic simulation model of pig growing and finishing that...
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Published in: | Preventive veterinary medicine 2022-11, Vol.208, p.105757-105757, Article 105757 |
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description | Pigmeat is the most consumed red meat globally and consumption is expected to continue to increase. The sector is faced by the risk of epidemic and endemic disease impacts and other adverse influences. The aim of this study was to develop a dynamic simulation model of pig growing and finishing that can be used to model the financial and economic impacts of a variety of scenarios both related to disease effects and other influences on production. The model consists of a physical performance module and financial performance module. The core of the physical performance module comprises three stocks to model the flow of pigs from purchase to slaughter. Mortality rates, daily live weight gain and feed conversion ratios influence the dynamics of the physical performance. Since contracts between farmers and slaughterhouses often include large price penalties for over- and underweight pigs, carcase weight distribution is an important determinant of revenues. The physical performance module, therefore, simulates slaughter weight variations. The financial performance module calculates revenue, costs and gross margins. The revenue calculations take into account price penalties for over- and underweight pigs. To demonstrate the capabilities of the model, we apply the model to assess the economic consequences of production impacts associated with respiratory disease. We use estimated production impacts associated with respiratory disease from a study of all-in-all out growing and finishing systems based on pig production data and information from slaughterhouse monitoring in the UK. Our model suggests a reduction in the gross margin of nearly 40 % as a consequence of the estimated production impacts associated with a 10% increase in respiratory disease prevalence. Due to the lack of reliable information on slaughter weight variation, we also simulate the model using different assumptions about the slaughter weight distribution. An increase in the standard deviation of carcase weights from 8 kg to 12 kg, holding average weights constant, more than halves gross margins under our scenarios. We suggest that for all-in-all-out systems, carcase weight variation is likely to be a substantial factor in reducing income in the presence of respiratory disease and the economic impact of respiratory disease may be underestimated if the effects of disease on variation in carcase weights are not included in any analysis.
•A flexible modeling tool for physical and financial performanc |
doi_str_mv | 10.1016/j.prevetmed.2022.105757 |
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•A flexible modeling tool for physical and financial performance of pig production.•Variation in carcase weights is important due to common contract arrangements.•Respiratory disease is estimated to decrease gross margins by nearly 40 %.</description><identifier>ISSN: 0167-5877</identifier><identifier>EISSN: 1873-1716</identifier><identifier>DOI: 10.1016/j.prevetmed.2022.105757</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>carcass weight ; disease prevalence ; economic costs ; economic impact ; endemic diseases ; farms ; feed conversion ; finance ; Financial performance ; income ; liveweight gain ; Marketing contracts ; mortality ; physical activity ; Pig ; prices ; profits and margins ; red meat ; Respiratory disease ; respiratory tract diseases ; risk ; simulation models ; slaughter weight ; slaughterhouses ; standard deviation ; swine ; swine production ; Systems dynamics model ; underweight ; veterinary medicine</subject><ispartof>Preventive veterinary medicine, 2022-11, Vol.208, p.105757-105757, Article 105757</ispartof><rights>2022 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c430t-482b604b4ee75a785916350cb993146d763743b5b56d1ee0b85998ce3c72ab43</citedby><cites>FETCH-LOGICAL-c430t-482b604b4ee75a785916350cb993146d763743b5b56d1ee0b85998ce3c72ab43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Pfuderer, Simone</creatorcontrib><creatorcontrib>Bennett, Richard M.</creatorcontrib><creatorcontrib>Brown, Anna</creatorcontrib><creatorcontrib>Collins, Lisa M.</creatorcontrib><title>A flexible tool for the assessment of the economic cost of pig disease in growers and finishers at farm level</title><title>Preventive veterinary medicine</title><description>Pigmeat is the most consumed red meat globally and consumption is expected to continue to increase. The sector is faced by the risk of epidemic and endemic disease impacts and other adverse influences. The aim of this study was to develop a dynamic simulation model of pig growing and finishing that can be used to model the financial and economic impacts of a variety of scenarios both related to disease effects and other influences on production. The model consists of a physical performance module and financial performance module. The core of the physical performance module comprises three stocks to model the flow of pigs from purchase to slaughter. Mortality rates, daily live weight gain and feed conversion ratios influence the dynamics of the physical performance. Since contracts between farmers and slaughterhouses often include large price penalties for over- and underweight pigs, carcase weight distribution is an important determinant of revenues. The physical performance module, therefore, simulates slaughter weight variations. The financial performance module calculates revenue, costs and gross margins. The revenue calculations take into account price penalties for over- and underweight pigs. To demonstrate the capabilities of the model, we apply the model to assess the economic consequences of production impacts associated with respiratory disease. We use estimated production impacts associated with respiratory disease from a study of all-in-all out growing and finishing systems based on pig production data and information from slaughterhouse monitoring in the UK. Our model suggests a reduction in the gross margin of nearly 40 % as a consequence of the estimated production impacts associated with a 10% increase in respiratory disease prevalence. Due to the lack of reliable information on slaughter weight variation, we also simulate the model using different assumptions about the slaughter weight distribution. An increase in the standard deviation of carcase weights from 8 kg to 12 kg, holding average weights constant, more than halves gross margins under our scenarios. We suggest that for all-in-all-out systems, carcase weight variation is likely to be a substantial factor in reducing income in the presence of respiratory disease and the economic impact of respiratory disease may be underestimated if the effects of disease on variation in carcase weights are not included in any analysis.
•A flexible modeling tool for physical and financial performance of pig production.•Variation in carcase weights is important due to common contract arrangements.•Respiratory disease is estimated to decrease gross margins by nearly 40 %.</description><subject>carcass weight</subject><subject>disease prevalence</subject><subject>economic costs</subject><subject>economic impact</subject><subject>endemic diseases</subject><subject>farms</subject><subject>feed conversion</subject><subject>finance</subject><subject>Financial performance</subject><subject>income</subject><subject>liveweight gain</subject><subject>Marketing contracts</subject><subject>mortality</subject><subject>physical activity</subject><subject>Pig</subject><subject>prices</subject><subject>profits and margins</subject><subject>red meat</subject><subject>Respiratory disease</subject><subject>respiratory tract diseases</subject><subject>risk</subject><subject>simulation models</subject><subject>slaughter weight</subject><subject>slaughterhouses</subject><subject>standard deviation</subject><subject>swine</subject><subject>swine production</subject><subject>Systems dynamics model</subject><subject>underweight</subject><subject>veterinary medicine</subject><issn>0167-5877</issn><issn>1873-1716</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqNkctOwzAQRS0EEqXwDXjJJsWOn1lWiJeExIa95TgT6iqJiyfl8fekLWILq9FcnbmamUvIJWcLzri-Xi82Gd5h7KFZlKwsJ1UZZY7IjFsjCm64PiaziTSFssackjPENWNMa6tmpF_StoPPWHdAx5Q62qZMxxVQjwiIPQwjTe1egZCG1MdAQ8K9uImvtIkIHoHGgb7m9AEZqR8a2sYh4mrfjbT1uafdtGN3Tk5a3yFc_NQ5ebm7fbl5KJ6e7x9vlk9FkIKNhbRlrZmsJYBR3lhVcS0UC3VVCS51Y7QwUtSqVrrhAKyeiMoGEMGUvpZiTq4Otpuc3raAo-sjBug6P0DaoitNKXa_M9V_UCZLa6WdUHNAQ06IGVq3ybH3-ctx5nZ2bu1-o3C7KNwhimlyeZiE6eb3CNlhiDAEaGKGMLomxT89vgFJw5Y1</recordid><startdate>202211</startdate><enddate>202211</enddate><creator>Pfuderer, Simone</creator><creator>Bennett, Richard M.</creator><creator>Brown, Anna</creator><creator>Collins, Lisa M.</creator><general>Elsevier B.V</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>202211</creationdate><title>A flexible tool for the assessment of the economic cost of pig disease in growers and finishers at farm level</title><author>Pfuderer, Simone ; Bennett, Richard M. ; Brown, Anna ; Collins, Lisa M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c430t-482b604b4ee75a785916350cb993146d763743b5b56d1ee0b85998ce3c72ab43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>carcass weight</topic><topic>disease prevalence</topic><topic>economic costs</topic><topic>economic impact</topic><topic>endemic diseases</topic><topic>farms</topic><topic>feed conversion</topic><topic>finance</topic><topic>Financial performance</topic><topic>income</topic><topic>liveweight gain</topic><topic>Marketing contracts</topic><topic>mortality</topic><topic>physical activity</topic><topic>Pig</topic><topic>prices</topic><topic>profits and margins</topic><topic>red meat</topic><topic>Respiratory disease</topic><topic>respiratory tract diseases</topic><topic>risk</topic><topic>simulation models</topic><topic>slaughter weight</topic><topic>slaughterhouses</topic><topic>standard deviation</topic><topic>swine</topic><topic>swine production</topic><topic>Systems dynamics model</topic><topic>underweight</topic><topic>veterinary medicine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pfuderer, Simone</creatorcontrib><creatorcontrib>Bennett, Richard M.</creatorcontrib><creatorcontrib>Brown, Anna</creatorcontrib><creatorcontrib>Collins, Lisa M.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Preventive veterinary medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pfuderer, Simone</au><au>Bennett, Richard M.</au><au>Brown, Anna</au><au>Collins, Lisa M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A flexible tool for the assessment of the economic cost of pig disease in growers and finishers at farm level</atitle><jtitle>Preventive veterinary medicine</jtitle><date>2022-11</date><risdate>2022</risdate><volume>208</volume><spage>105757</spage><epage>105757</epage><pages>105757-105757</pages><artnum>105757</artnum><issn>0167-5877</issn><eissn>1873-1716</eissn><abstract>Pigmeat is the most consumed red meat globally and consumption is expected to continue to increase. The sector is faced by the risk of epidemic and endemic disease impacts and other adverse influences. The aim of this study was to develop a dynamic simulation model of pig growing and finishing that can be used to model the financial and economic impacts of a variety of scenarios both related to disease effects and other influences on production. The model consists of a physical performance module and financial performance module. The core of the physical performance module comprises three stocks to model the flow of pigs from purchase to slaughter. Mortality rates, daily live weight gain and feed conversion ratios influence the dynamics of the physical performance. Since contracts between farmers and slaughterhouses often include large price penalties for over- and underweight pigs, carcase weight distribution is an important determinant of revenues. The physical performance module, therefore, simulates slaughter weight variations. The financial performance module calculates revenue, costs and gross margins. The revenue calculations take into account price penalties for over- and underweight pigs. To demonstrate the capabilities of the model, we apply the model to assess the economic consequences of production impacts associated with respiratory disease. We use estimated production impacts associated with respiratory disease from a study of all-in-all out growing and finishing systems based on pig production data and information from slaughterhouse monitoring in the UK. Our model suggests a reduction in the gross margin of nearly 40 % as a consequence of the estimated production impacts associated with a 10% increase in respiratory disease prevalence. Due to the lack of reliable information on slaughter weight variation, we also simulate the model using different assumptions about the slaughter weight distribution. An increase in the standard deviation of carcase weights from 8 kg to 12 kg, holding average weights constant, more than halves gross margins under our scenarios. We suggest that for all-in-all-out systems, carcase weight variation is likely to be a substantial factor in reducing income in the presence of respiratory disease and the economic impact of respiratory disease may be underestimated if the effects of disease on variation in carcase weights are not included in any analysis.
•A flexible modeling tool for physical and financial performance of pig production.•Variation in carcase weights is important due to common contract arrangements.•Respiratory disease is estimated to decrease gross margins by nearly 40 %.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.prevetmed.2022.105757</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | carcass weight disease prevalence economic costs economic impact endemic diseases farms feed conversion finance Financial performance income liveweight gain Marketing contracts mortality physical activity Pig prices profits and margins red meat Respiratory disease respiratory tract diseases risk simulation models slaughter weight slaughterhouses standard deviation swine swine production Systems dynamics model underweight veterinary medicine |
title | A flexible tool for the assessment of the economic cost of pig disease in growers and finishers at farm level |
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