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<p>The wild boar (<i>Sus scrofa</i>) has emerged as a growing concern for animal and public health due to its role as a reservoir for multiple pathogens, many notifiable to the World Organization for Animal Health, and its high invasive potential. In countries like Argentina, this species poses a persistent threat to the swine industry. The potential introduction of exotic diseases, such as African swine fever, into wild boar populations presents a serious risk to national food security and international trade. The interface between wild boars and domestic pigs represents a critical spatial overlap where disease transmission may occur. Although risk mapping can support surveillance and control efforts, it remains challenging in data-scarce contexts. To address this, we applied expert elicitation within a multicriteria decision analysis (MCDA) framework to identify areas at highest risk for wild boar-domestic pig interactions in Argentina. Model validation confirmed its effectiveness in identifying risk zones, with high and medium-risk areas mostly concentrated in Córdoba, San Luis, Buenos Aires, Santa Fe, La Pampa, and Entre Ríos provinces. While most of the country exhibited an absence of risk, the identified medium- and high-risk areas warrant targeted mitigation efforts and active surveillance. This study provides a practical tool to guide surveillance strategies and demonstrates a replicable, knowledge-driven modeling approach suitable for data-limited environments.</p>

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Let’s meet at the interface: modeling the spatial interaction between wild boar and domestic pigs in Argentina

  • 期刊论文

  • 发表日期：

    2025年7月21日

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  • Luciano F. La Sala,
  • Nicolás Caruso,
  • Guillermo Capobianco,
  • Laura Alarcón,
  • Andrea Marcos

摘要

The wild boar (Sus scrofa) has emerged as a growing concern for animal and public health due to its role as a reservoir for multiple pathogens, many notifiable to the World Organization for Animal Health, and its high invasive potential. In countries like Argentina, this species poses a persistent threat to the swine industry. The potential introduction of exotic diseases, such as African swine fever, into wild boar populations presents a serious risk to national food security and international trade. The interface between wild boars and domestic pigs represents a critical spatial overlap where disease transmission may occur. Although risk mapping can support surveillance and control efforts, it remains challenging in data-scarce contexts. To address this, we applied expert elicitation within a multicriteria decision analysis (MCDA) framework to identify areas at highest risk for wild boar-domestic pig interactions in Argentina. Model validation confirmed its effectiveness in identifying risk zones, with high and medium-risk areas mostly concentrated in Córdoba, San Luis, Buenos Aires, Santa Fe, La Pampa, and Entre Ríos provinces. While most of the country exhibited an absence of risk, the identified medium- and high-risk areas warrant targeted mitigation efforts and active surveillance. This study provides a practical tool to guide surveillance strategies and demonstrates a replicable, knowledge-driven modeling approach suitable for data-limited environments.