Generation of swine movement network and analysis of efficient mitigation strategies for African swine fever virus

Autoři: Tanvir Ferdousi aff001;  Sifat Afroj Moon aff001;  Adrian Self aff002;  Caterina Scoglio aff001
Působiště autorů: Department of Electrical and Computer Engineering, Kansas State University, Manhattan, Kansas, United States of America aff001;  National Agricultural Biosecurity Center, Kansas State University, Manhattan, Kansas, United States of America aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article


Animal movement networks are essential in understanding and containing the spread of infectious diseases in farming industries. Due to its confidential nature, movement data for the US swine farming population is not readily available. Hence, we propose a method to generate such networks from limited data available in the public domain. As a potentially devastating candidate, we simulate the spread of African swine fever virus (ASFV) in our generated network and analyze how the network structure affects the disease spread. We find that high in-degree farm operations (i.e., markets) play critical roles in the disease spread. We also find that high in-degree based targeted isolation and hypothetical vaccinations are more effective for disease control compared to other centrality-based mitigation strategies. The generated networks can be made more robust by validation with more data whenever more movement data will be available.

Klíčová slova:

Centrality – Epidemiology – Fevers – Infectious disease control – Livestock – Network analysis – Swine – Vaccination and immunization


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Článek vyšel v časopise


2019 Číslo 12
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