{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/81184"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/81184","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Meta-Analysis on the Effect of Interventions Used in Cattle Processing Plants to Reduce Escherichia coli Contamination in Beef","abstract":"A Quantitative Microbial Risk Assessment (QMRA) has been undertaken to utilize research on Shiga-toxin Escherichia coli (STEC) contamination in beef for the benefit of public health. The QMRA operates as a 2nd order Monte Carlo simulation to create stochastic mathematical models that incorporate all of the key components of STEC contamination from farm to fork. The resulting model is able to identify knowledge gaps, public health risks, and simulate theoretical changes in the beef system. However, high variability in processing plant intervention literature has prompted a meta-analysis to determine informed estimates of intervention effectiveness for QMRA parameterization. Meta-analysis derived least-squares means bacterial log reductions for acetic acid, lactic acid, steam vacuum, and water wash interventions on carcass surfaces (n=249) were 1.44 [95% CI: 0.73 – 2.15], 2.07 [1.48 – 2.65], 3.09 [2.46 – 3.73], and 1.90 [1.33 – 2.47] log CFU/cm2, respectively. Least-squares means log reductions for acetic acid, lactic acid, sodium hydroxide, and water wash on hide surfaces (n=47) were 2.21 [1.36 – 3.05], 3.02 [2.16 – 3.88], 3.66 [2.60 – 4.72], and 0.08 [-0.94 – 1.11] log CFU/cm2, respectively. Meta-regressions showed that temperature, duration of application, microbial starting concentration, extra water washes, inoculation type, organism type, sample method, surface type, and antimicrobial concentrations were all significant predictors of intervention effectiveness. Finally, after observing authors use substituted values for samples found below a detection limit in primary plant intervention literature, simulations were run to assess the impact of substitution on a random-effects meta-analysis. Simulation results show that substitution practices artificially decrease effectiveness estimates and increase heterogeneity.","abstract_html":"A Quantitative Microbial Risk Assessment (QMRA) has been undertaken to utilize research on Shiga-toxin Escherichia coli (STEC) contamination in beef for the benefit of public health. The QMRA operates as a 2nd order Monte Carlo simulation to create stochastic mathematical models that incorporate all of the key components of STEC contamination from farm to fork. The resulting model is able to identify knowledge gaps, public health risks, and simulate theoretical changes in the beef system. However, high variability in processing plant intervention literature has prompted a meta-analysis to determine informed estimates of intervention effectiveness for QMRA parameterization. Meta-analysis derived least-squares means bacterial log reductions for acetic acid, lactic acid, steam vacuum, and water wash interventions on carcass surfaces (n=249) were 1.44 [95% CI: 0.73 – 2.15], 2.07 [1.48 – 2.65], 3.09 [2.46 – 3.73], and 1.90 [1.33 – 2.47] log CFU/cm2, respectively. Least-squares means log reductions for acetic acid, lactic acid, sodium hydroxide, and water wash on hide surfaces (n=47) were 2.21 [1.36 – 3.05], 3.02 [2.16 – 3.88], 3.66 [2.60 – 4.72], and 0.08 [-0.94 – 1.11] log CFU/cm2, respectively. Meta-regressions showed that temperature, duration of application, microbial starting concentration, extra water washes, inoculation type, organism type, sample method, surface type, and antimicrobial concentrations were all significant predictors of intervention effectiveness. Finally, after observing authors use substituted values for samples found below a detection limit in primary plant intervention literature, simulations were run to assess the impact of substitution on a random-effects meta-analysis. Simulation results show that substitution practices artificially decrease effectiveness estimates and increase heterogeneity.","abstract_has_math":false,"creators":["Zhilyaev, Samson"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Environmental Planning","degree_department":"Civil and Environmental Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Gallagher, Daniel L."],"committee_members":["Widdowson, Mark A.","Sanderson, Michael W."],"year":2016,"date_issued":"2016-06-20","date_published":"2016-06-20","updated_at":"2026-07-22T22:19:10Z","subjects":["QMRA","meta-analysis","Escherichia","coli","O157","meta-regression","plant","intervention","beef","cattle","STEC"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:8064"],"render_values":[{"text":"vt_gsexam:8064","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/81184","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Gallagher, Daniel L."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Widdowson, Mark A.","Sanderson, Michael W."]},{"key":"dc:contributor.department","label":"Department","values":["Civil and Environmental Engineering"]},{"key":"dc:creator","label":"Author","values":["Zhilyaev, Samson"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-12-13T07:00:50Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-12-13T07:00:50Z"]},{"key":"dc:date.issued","label":"Date","values":["2016-06-20"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Environmental Planning"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["QMRA","meta-analysis","Escherichia","coli","O157","meta-regression","plant","intervention","beef","cattle","STEC"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:8064"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/81184"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A Quantitative Microbial Risk Assessment (QMRA) has been undertaken to utilize research on Shiga-toxin Escherichia coli (STEC) contamination in beef for the benefit of public health. The QMRA operates as a 2nd order Monte Carlo simulation to create stochastic mathematical models that incorporate all of the key components of STEC contamination from farm to fork. The resulting model is able to identify knowledge gaps, public health risks, and simulate theoretical changes in the beef system. However, high variability in processing plant intervention literature has prompted a meta-analysis to determine informed estimates of intervention effectiveness for QMRA parameterization. Meta-analysis derived least-squares means bacterial log reductions for acetic acid, lactic acid, steam vacuum, and water wash interventions on carcass surfaces (n=249) were 1.44 [95% CI: 0.73 – 2.15], 2.07 [1.48 – 2.65], 3.09 [2.46 – 3.73], and 1.90 [1.33 – 2.47] log CFU/cm2, respectively. Least-squares means log reductions for acetic acid, lactic acid, sodium hydroxide, and water wash on hide surfaces (n=47) were 2.21 [1.36 – 3.05], 3.02 [2.16 – 3.88], 3.66 [2.60 – 4.72], and 0.08 [-0.94 – 1.11] log CFU/cm2, respectively. Meta-regressions showed that temperature, duration of application, microbial starting concentration, extra water washes, inoculation type, organism type, sample method, surface type, and antimicrobial concentrations were all significant predictors of intervention effectiveness. Finally, after observing authors use substituted values for samples found below a detection limit in primary plant intervention literature, simulations were run to assess the impact of substitution on a random-effects meta-analysis. Simulation results show that substitution practices artificially decrease effectiveness estimates and increase heterogeneity."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Meta-Analysis on the Effect of Interventions Used in Cattle Processing Plants to Reduce Escherichia coli Contamination in Beef"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Gallagher, Daniel L."],"dc:contributor.committeemember":["Widdowson, Mark A.","Sanderson, Michael W."],"dc:contributor.department":["Civil and Environmental Engineering"],"dc:creator":["Zhilyaev, Samson"],"dc:date.accessioned":["2017-12-13T07:00:50Z"],"dc:date.available":["2017-12-13T07:00:50Z"],"dc:date.issued":["2016-06-20"],"dc:description.abstract":["A Quantitative Microbial Risk Assessment (QMRA) has been undertaken to utilize research on Shiga-toxin Escherichia coli (STEC) contamination in beef for the benefit of public health. The QMRA operates as a 2nd order Monte Carlo simulation to create stochastic mathematical models that incorporate all of the key components of STEC contamination from farm to fork. The resulting model is able to identify knowledge gaps, public health risks, and simulate theoretical changes in the beef system. However, high variability in processing plant intervention literature has prompted a meta-analysis to determine informed estimates of intervention effectiveness for QMRA parameterization. Meta-analysis derived least-squares means bacterial log reductions for acetic acid, lactic acid, steam vacuum, and water wash interventions on carcass surfaces (n=249) were 1.44 [95% CI: 0.73 – 2.15], 2.07 [1.48 – 2.65], 3.09 [2.46 – 3.73], and 1.90 [1.33 – 2.47] log CFU/cm2, respectively. Least-squares means log reductions for acetic acid, lactic acid, sodium hydroxide, and water wash on hide surfaces (n=47) were 2.21 [1.36 – 3.05], 3.02 [2.16 – 3.88], 3.66 [2.60 – 4.72], and 0.08 [-0.94 – 1.11] log CFU/cm2, respectively. Meta-regressions showed that temperature, duration of application, microbial starting concentration, extra water washes, inoculation type, organism type, sample method, surface type, and antimicrobial concentrations were all significant predictors of intervention effectiveness. Finally, after observing authors use substituted values for samples found below a detection limit in primary plant intervention literature, simulations were run to assess the impact of substitution on a random-effects meta-analysis. Simulation results show that substitution practices artificially decrease effectiveness estimates and increase heterogeneity."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:8064"],"dc:identifier.uri":["http://hdl.handle.net/10919/81184"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["QMRA","meta-analysis","Escherichia","coli","O157","meta-regression","plant","intervention","beef","cattle","STEC"],"dc:title":["Meta-Analysis on the Effect of Interventions Used in Cattle Processing Plants to Reduce Escherichia coli Contamination in Beef"],"dc:type":["Thesis"],"thesis:degree_discipline":["Environmental Planning"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:10Z"}