兰光, 闫静, 张璟, 申艳琴, 李欣颖, 刘小菊, 何婕, 李保娣. 2022-2023年甘肃省食源性腹泻病病原的监测分析及多病原检测方法的探索[J]. 疾病监测, 2024, 39(5): 542-546. DOI: 10.3784/jbjc.202311160606
引用本文: 兰光, 闫静, 张璟, 申艳琴, 李欣颖, 刘小菊, 何婕, 李保娣. 2022-2023年甘肃省食源性腹泻病病原的监测分析及多病原检测方法的探索[J]. 疾病监测, 2024, 39(5): 542-546. DOI: 10.3784/jbjc.202311160606
Lan Guang, Yan Jing, Zhang Jing, Shen Yanqin, Li Xinying, Liu Xiaoju, He Jie, Li Baodi. Etiological surveillance and exploration of multi-pathogen detection methods for foodborne diarrheal disease in Gansu, 2022–2023[J]. Disease Surveillance, 2024, 39(5): 542-546. DOI: 10.3784/jbjc.202311160606
Citation: Lan Guang, Yan Jing, Zhang Jing, Shen Yanqin, Li Xinying, Liu Xiaoju, He Jie, Li Baodi. Etiological surveillance and exploration of multi-pathogen detection methods for foodborne diarrheal disease in Gansu, 2022–2023[J]. Disease Surveillance, 2024, 39(5): 542-546. DOI: 10.3784/jbjc.202311160606

2022-2023年甘肃省食源性腹泻病病原的监测分析及多病原检测方法的探索

Etiological surveillance and exploration of multi-pathogen detection methods for foodborne diarrheal disease in Gansu, 2022–2023

  • 摘要:
    目的 了解2022—2023年甘肃省食源性腹泻病的流行情况和病原学变化趋势,为制定相关防控策略提供依据;同时探索新的检测方法,为食源性腹泻病的监测提供新技术、新线索。
    方法 对2022—2023年甘肃省3 447例食源性腹泻病病例进行病例信息调查和粪便标本采集,采集粪便标本进行病原体分离培养鉴定(即常规方法)。 分离鉴定病原体包括沙门菌、志贺菌、副溶血弧菌、致泻性大肠埃希菌和诺如病毒。 对以上任一病原体阳性和采用常规方法未筛选出可疑病原体但同时伴有腹泻、腹痛、发热及呕吐症状的病例的粪便标本使用QIAGEN公司推出的QIAstat-Dx胃肠道Panel法做进一步检测。
    结果 2022—2023年共调查甘肃省腹泻病病例3 447例,常规方法检出阳性病例标本383份(11.11%),主要为诺如病毒阳性,共220份(57.44%),致泻性大肠埃希菌阳性96份(25.07%)。 不同年龄组(χ2=66.007,P<0.05)、地区(χ2=169.054,P<0.05)和职业(χ2=74.469,P<0.05)病例病原体阳性率差异有统计学意义。 QIAstat-Dx胃肠道 Panel法检出5种目标病原体与常规方法检出5种目标病原体的一致性较好(Kappa=0.817),除5种目标病原体以外,QIAstat-Dx胃肠道 Panel法检出腺病毒(F40/41)阳性标本85份(15.89%),致病弯曲菌阳性标本69份(12.90%),轮状病毒A阳性标本56份(10.47%)。
    结论 2022—2023年甘肃省食源性腹泻病的病原体分布及流行情况不同,应根据不同情况分类防治。 与常规分离培养法相比,QIAstat-Dx胃肠道Panel法检测胃肠道病原体较全面,在一定程度上实现了多种病原同时检测,并相对准确地反映腹泻病例病原感染谱情况。

     

    Abstract:
    Objective To understand the incidence and etiological characteristics of foodborne diarrheal disease in Gansu province from 2022 to 2023, and provide evidence for the development of relevant prevention and control strategies. At the same time, new detection methods were explored to provide new technology and new clues for the surveillance for foodborne diarrheal diseases.
    Methods Stool samples were collected from 3 447 cases of foodborne diarrhea disease in Gansu from 2022 to 2023 for pathogen isolation, culture and identification by conventional assays. Pathogens isolated and identified included Salmonella, Shigella, Vibrio Parahaemolyticus, diarrheic Escherichia coli and norovirus. In the diarrheal disease cases with abdominal pain, fever and vomiting, stool samples which were positive for any of the above pathogens and were not identified by conventional assays were detected by using QIAGEN's QIAstat-Dx gastrointestinal Panel assay.
    Results A total of 3 447 cases of diarrheal disease were investigated in Gansu from 2022 to 2023, of which 383 samples (11.11%) were positive detected by conventional assays, including 220 norovirus positive ones (57.44%) and 96 diarrheic E. coli positive ones (25.07%). There were significant differences in the positive rate of pathogen among different age groups (χ2=66.007, P<0.05), areas (χ2=169.054, P<0.05) and occupation groups (χ2=74.469, P<0.05). The detection of the 5 target pathogens by gastrointestinal Panel assay of QIAstat-Dx was in good agreement with the detection of the 5 target pathogens by conventional assays (Kappa=0.817). Except 5 targeted pathogens, QIAstat-Dx gastrointestinal Panel assay detected 85 adenovirus (F40/41) positive samples (15.89%), 69 pathogenic Campylobacter positive samples (12.90%), and 56 rotavirus A positive samples (10.47%).
    Conclusion The pathogen distribution and incidence of foodborne diarrheal disease varied in Gansu from 2022 to 2023, and it is necessary to take targeted prevention and treatment measures. Compared with conventional isolation and culture assays, QIAstat-Dx gastrointestinal Panel assay is more effective in detecting gastrointestinal pathogens in terms of simultaneous detection of multi-pathogens, and more accurate detection of pathogen spectrum of diarrheal disease cases.

     

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