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Relevancy Prediction of the Emerging Pathogens with Porcine Diarrhea by Logistic Regression Model

文献类型： 外文期刊

作者： Li, Benqiang 1 ; Tao, Jie 1 ; Li, Xin 1 ; Cheng, Jinghua 1 ; Shi, Ying 1 ; Tang, Pan 1 ; Liu, Huili 1 ;

作者机构： 1.Shanghai Acad Agr Sci, Inst Anim Husb & Vet Med, Shanghai 201106, Peoples R China

2.Shanghai Key Lab Agr Genet & Breeding, Shanghai 201106, Peoples R China

3.Shanghai Engn Res Ctr Pig Breeding, Shanghai 201302, Peoples R China

关键词： porcine diarrheal pathogens; mixed infection; emerging pathogens; logistic regression analysis

期刊名称：MICROORGANISMS （ 影响因子：4.2； 五年影响因子：4.6 ）

ISSN：

年卷期： 2025 年 13 卷 3 期

页码：

收录情况： SCI

摘要： Porcine viral diarrhea has always been one of the main obstacles to the healthy development of the pig industry in China with its variety of pathogens and complexity of co-infections. Analysis of the dominant mixed-infection model is a fundamental step in boosting the prevention and control of porcine diarrhea. In this study, 3256 porcine fecal samples were collected from 17 pig herds in Shanghai, China, from 2015 to 2023 to identify novel pathogenic infection patterns. The results confirmed that porcine astrovirus (PAstV), porcine sapelovirus (PSV), and porcine epidemic diarrhea virus (PEDV) were the top three agents with positive rates of 28.47%, 20.71%, and 20.23%, respectively. Porcine rotavirus (PoRV) and transmissible gastroenteritis virus (TGEV) accounted for only 8.12% and 1.12%, respectively. Importantly, mixed infection rates were high and complicated. The double infection rate was higher than that of a single infection. Next, the mixed-infection model of PEDV and emerging diarrheal pathogens was explored. The predominant dual-infection models were PEDV/PKoV (porcine kobuvirus) (14.18%), PEDV/PAstV (10.02%), and PEDV/PSV (9.29%). The predominant triple infection models were PEDV/PKoV/PAstV (18.93%), PEDV/PSV/PAstV (10.65%), and PEDV/PKoV/PSV (7.10%). The dominant quadruple-infection model was PEDV/PAstV/PSV/PKoV (46.82%). In conclusion, PEDV is mainly mix-infected with PAstV, PSV, and PKoV in clinical settings. Furthermore, multiple-factor logistic regression analysis confirmed that PAstV, PKoV, bovine viral diarrhea virus (BVDV), and PEDV were closely related to porcine diarrhea. PEDV/PKoV, PEDV/porcine sapovirus (PoSaV), PKoV/BVDV, PoSaV/BVDV, and porcine deltacoronavirus (PDCoV)/PoSaV had great co-infection dominance, which will be helpful for porcine co-infection research.

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