*Corresponding author: ecorisk88@163.com

Wild boars (Sus scrofa) have recently been identified as significant reservoirs and amplifiers of various emerging zoonotic viruses. In northeastern China, the increasing overlap between wild boar habitats, livestock farming areas and human settlements has raised serious concerns about cross-species transmission and spatial spillover of wild boar-borne infectious diseases. This study aimed to define the ecologically suitable distribution of wild boars and associated viruses, identify spatial hotspots of emerging wild boar-borne disease risk and validate the circulation of these pathogens within wild boar populations in high-risk areas. The goal was to provide a scientific basis for surveillance and transboundary prevention in ecologically sensitive regions. The MaxEnt ecological niche model was applied to predict the suitability of wild boars and spatial risk of disease emergence. A fuzzy overlay analysis was then conducted to delineate high-risk zones for wild boar-borne disease emergence. Within these high-risk zones, least-cost path modeling was used to analyze ecological connectivity and to identify major transmission routes. Between January 2023 and December 2024, a total of 158 wild boar serum samples were collected along the identified transmission routes. ELISA assays were used for serological testing and antibody prevalence was calculated. The MaxEnt model showed high predictive accuracy for wild boar distribution (AUC = 0.810, Kappa = 0.816) and for disease risk mapping (AUC = 0.818, Kappa = 0.803). The total area of high-risk zones for emerging wild boar-borne diseases reached 12,188.68 km², mainly located in Mudanjiang, Jixi, and Shuangyashan city. Three major transmission routes were identified within these regions and all converging in Hulin County. This area is characterized by semi-free-range hybrid wild boar farming and strong landscape connectivity, making it a critical node for potential virus spread. Serological testing confirmed PRV antibodies in 8.86% (14/158) of samples and PCV2 antibodies in 5.06% (8/158). The highest PRV antibody prevalence (21.05%, 95%CI: 9.55-37.32) was observed in Hulin County, suggesting its central role in local virus maintenance and transmission. This study proposes a four-stage spatial framework: habitat modeling, risk mapping, routes identification and serological validation for comprehensive assessment of wild boar-borne disease risks. It provides both theoretical and practical value for targeted surveillance and transboundary disease preparedness in ecologically sensitive regions

To Cite This Article: Wang H, Wang Y, Li Y, Wang X, Chen X, Yu S and Wang X, 2025. Spatial risk prediction and serological validation of emerging wild boar-borne diseases in eastern heilongjiang, china. Pak Vet J, 45(4): 1721-1732. http://dx.doi.org/10.29261/pakvetj/2025.xxx