African swine fever detection and transmission estimates using homogeneous versus heterogeneous model formulation in stochastic simulations within pig premises

Research output: Contribution to journalArticlepeer-review

Abstract

Background: African swine fever (ASF) is one of the most important foreign animal diseases to the U.S. swine industry. Stakeholders in the swine production sector are on high alert as they witness the devastation of ongoing outbreaks in some of its most important trade partner countries. Efforts to improve preparedness for ASF outbreak management are proceeding in earnest and mathematical modeling is an integral part of these efforts. Aim: This study aimed to assess the impact on within-herd transmission dynamics of ASF when the models used to simulate transmission assume there is homogeneous mixing of animals within a barn. Methods: Barn-level heterogeneity was explicitly captured using a stochastic, individual pig-based, heterogeneous transmission model that considers three types of infection transmission, (1) within-pen via nose-to-nose contact; (2) between-pen via nose-to-nose contact with pigs in adjacent pens; and (3) both between-and within-pen via distance-independent mechanisms (e.g., via fomites). Predictions were compared between the heterogeneous and the homogeneous Gillespie models. Results: Results showed that the predicted mean number of infectious pigs at specific time points differed greatly between the homogeneous and heterogeneous models for scenarios with low levels of between-pen contacts via distance-independent pathways and the differences between the two model predictions were more pronounced for the slow contact rate scenario. The heterogeneous transmission model results also showed that it may take significantly longer to detect ASF, particularly in large barns when transmission predominantly occurs via nose-to-nose contact between pigs in adjacent pens. Conclusion: The findings emphasize the need for completing preliminary explorations when working with homogeneous mixing models to ascertain their suitability to predict disease outcomes.

Original languageEnglish (US)
Pages (from-to)787-796
Number of pages10
JournalOpen Veterinary Journal
Volume12
Issue number6
DOIs
StatePublished - 2022

Bibliographical note

Funding Information:
The authors would like to acknowledge the informal contributions and support of the entire Secure Food Systems team at the University of Minnesota, which also includes Catherine Alexander, David Halvorson, Michelle Leonard, Rosemary Marusak, and Miranda Medrano. We also greatly appreciate the modeling discussion with Dr. Don Klinkenberg of RIVM in the Netherlands. Swine production data was confidentially and kindly provided by the participants of the ASF risk assessment workgroup. ASF outbreak case descriptions were thoughtfully provided by Dr. Vu Dinh Ton of the Vietnam National University of Agriculture in Hanoi. FundingThe authors are funded by a USDA National Institute of Food and Agriculture (NIFA) grant 2020-68014-30974 (The Secure Food System: a cross-commodity risk-based approach for preserving agricultural business continuity during disease emergencies), from a cooperative agreement between the Center for Epidemiology and Animal Health (CEAH) of the USDA, Animal and Plant Health Inspection Service (APHIS) Veterinary Services (VS) and the University of Minnesota (UMN) as USDA Award # AP20VSCEAH00C054 (Quantitative Analyses to Manage Transboundary/ Emerging Diseases and Support Risk-based Decision-making), and as part of research project #20-077 SHIC for Swine Health Information Center’s agreement with UMN to conduct research entitled, “Determining the pathways for ASF introduction into boar studs and risk of ASF transmission via semen movements during an ASF outbreak.” Cardona and Corzo are also funded by the B.S. Pomeroy Chair in Avian Health and the Leman Chair in Swine Health and Productivity, respectively, at the University of Minnesota, College of Veterinary Medicine.

Funding Information:
The authors are funded by a USDA National Institute of Food and Agriculture (NIFA) grant 2020-68014-30974 (The Secure Food System: a cross-commodity risk-based approach for preserving agricultural business continuity during disease emergencies), from a cooperative agreement between the Center for Epidemiology and Animal Health (CEAH) of the USDA, Animal and Plant Health Inspection Service (APHIS) Veterinary Services (VS) and the University of Minnesota (UMN) as USDA Award # AP20VSCEAH00C054 (Quantitative Analyses to Manage Transboundary/ Emerging Diseases and Support Risk-based Decision-making), and as part of research project #20-077 SHIC for Swine Health Information Center’s agreement with UMN to conduct research entitled, “Determining the pathways for ASF introduction into boar studs and risk of ASF transmission via semen movements during an ASF outbreak.” Cardona and Corzo are also funded by the B.S. Pomeroy Chair in Avian Health and the Leman Chair in Swine Health and Productivity, respectively, at the University of Minnesota, College of Veterinary Medicine. Conflict of interest The authors declare that they have no competing interests. Author contributions AS, SM, PJB, KMS, TCB, TG, CJC, CAC, and MRC conceived the ideas of the study; AS, SM, PJB, and TB conceived the ideas for the analysis; SM, PJB, and AS performed the analyses; SM, AS wrote the manuscript; PJB, MRC were major contributors in writing the manuscript and all other authors commented on the manuscript. All authors read and approved the final manuscript.

Publisher Copyright:
© 2022, Faculty of Veterinary Medicine, University of Tripoli. All rights reserved.

Keywords

  • African swine fever
  • Gillespie algorithm
  • Heterogeneity
  • Homogeneous mixing
  • Transmission models

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