摘要
目的分析2017-2020年重庆市南川区外环境禽流感病毒检测数据,预测南川区外环境禽流感发病趋势,为预警及早期防控人感染高致病性禽流感流行提供依据。方法用Microsoft Excel 365对南川区2017-2020年外环境禽流感检测数据进行统计分析,应用移动平均法季节趋势模型建立禽流感趋势预测模型,预测外环境禽流感变化趋势。结果南川区活禽市场外环境禽流感阳性率为46.43%;阳性标本中,以H5、H9亚型为主;不同监测样本和不同季度禽流感病毒阳性检出率比较,差异均有统计学意义(P<0.05)。移动平均法季节趋势模型拟合结果较好,平均百分比相对误差为5.56%。阳性高峰在第一季度。结论南川区禽类市场环境中存在H5、H9及多种亚型混合的致病性禽流感病毒感染,且呈逐年上升趋势,冬春季发病较高。需加强对外环境及高危人群禽流感监测并规范市场管理,降低人感染高致病性禽流感发生风险。
Objective To analyze the external environmental avian influenza virus detection data outside Nanchuan District of Chongqing City from 2017 to 2020,predict the trend of environmental avian influenza outside Nanchuan District,and provide evidence for early warning and early prevention and control of human infection with highly pathogenic avian influenza.Methods Microsoft Excel 365 was used to statistically analyze the avian influenza detection data in the external environment from 2017 to 2020 in Nanchuan District,and the seasonal trend model of moving average method was used to establish the trend prediction model of avian influenza in the external environment to predict the change trend of avian influenza in the external environment.Results The positive rate of avian influenza in the external environment of live poultry market in Nanchuan district was 46.43%;the positive samples were mainly H5 and H9 subtypes;the positive detection rates of avian influenza virus in different monitoring samples and different quarters were statistically significant(P<0.05).The seasonal trend model based on moving average method was used to predict the model,and the fitting result was good,with an average relative error of 5.56%.The positive peak was in the first quarter.Conclusion In the poultry market environment of Nanchuan District,there are pathogenic avian influenza virus infections of H5,H9 and multiple subtypes,and the infection is increasing year by year,with higher incidence in winter and spring.It is necessary to strengthen the external environment and high-risk population avian influenza monitoring and standardize market management to reduce the risk of human infection with highly pathogenic avian influenza.
作者
曹霞
吴汶禧
李龙
巴莹莹
严欣婷
CAO Xia;WU Wenxi;LI Long;BA Yingying;YAN Xinting(Chongqing Nanchuan District Center for Disease Control and Prevention,Chongqing 408400,China)
出处
《现代医药卫生》
2021年第2期215-218,共4页
Journal of Modern Medicine & Health
关键词
禽流感
监测
移动平均法
季节趋势模型
预测
Avian influenza
Surveillance
Moving average method
Seasonal trend model
Prediction
