人禽流感（H5N1）流行病学监测
发布时间：2019-06-02 09:30
【摘要】： 背景和目的人禽流感(Human avian influenza,HAI)是人接触禽流感病毒污染的排泄物或者分泌物而感染,并出现以呼吸道感染、粘膜充血等症状为主要表现的人畜共患疾病,死亡率较高。部分高致病性禽流感毒株(如H5N1)的患者可出现呼吸衰竭和多器官损害。2003年12月～2009年2月,人禽流感疫情相继波及全球15个国家,涵盖亚洲、欧洲、非洲、美洲四大洲,共计408例人禽流感病例,其中254人死亡,病死率高达62.3%。因此,有必要通过分析全球历年来实验室确诊人甲型流感(H5N1)病例的流行病学资料以持续监测其发病模式是否发生改变,探索短期病例数的预测方法和影响病例死亡的可能因素;也为建立我国的监测及预警方法打下基础。 方法收集2003年12月至2009年2月全球15个国家向WHO报告的实验室确诊人甲型流感(H5N1)病例的资料建立数据库;通过对全球人禽流感病例的逐年的年龄和性别分布、发病至住院的中位时间及发病至死亡的中位时间、家庭聚集性变化、季节趋势和病死率等指标进行分析,判断人禽流感发病模式有无变化;用灰色动态模型和时间序列ARIMA模型对人禽流感病例月发病例数和月累计发病例数进行预测;运用多水平logstic模型和单水平logstic回归筛选可能影响病例死亡的因素。 结果 1.人禽流感发病模式监测 各年龄组男女均可发病,男女性别比为0.9:1,各年份间和各年龄段间性别比差异无统计学意义;发病到住院的中位时间为4天(范围0～20天),发病到死亡的中位时间为9天(2～31天),各年份间差异无统计学意义;发病高峰期为11月20日～3月6日,不同年份和不同国家间差异无统计学意义;总病死率为62.3%,且不随时间而变化;历年家庭聚集性也无增加趋势。 2.人禽流感病例数预测效果 对月累计发病例数进行预测,时间序列的中位预测误差为0.94%,灰色模型的中位预测误差为1.5%;对月发病例数进行预测,时间序列的中位预测误差为4.46%,灰色模型的中位预测误差为23.36%。 3.影响人禽流感病例存活的相关因素 病例年龄每减少1岁,存活的可能性将增加1.03倍;病例发病到住院时间间隔每减少1天,病例存活可能性将增加1.20倍;有家庭聚集性的人禽流感病例,其存活的概率是无家庭聚集性病例的2.71倍。 结论 1.人禽流感发病模式监测 全球人禽流感H5N1发病模式过去6年没有重大改变:各年龄段男女均可发病;冬春季节高发的特征比较稳定;历年家庭聚集性无增加趋势。 2.人禽流感病例数的预测效果 时间序列ARIMA模型是对人禽流感H5N1月发病数进行预测的比较理想方法。 3.影响人禽流感病例存活的相关因素 年龄、发病到住院天数和有无家庭聚集性可能对病例的存活有影响。
[Abstract]:Background and objective Human avian influenza (Human avian influenza,HAI) is infected by human contact with excreta or secretion contaminated by avian influenza virus, and the main symptoms such as respiratory tract infection and mucous congestion are zoonotic diseases, and the mortality rate is high. Respiratory failure and multiple organ damage can occur in some patients with highly pathogenic avian influenza strains (such as H5N1). From December 2003 to February 2009, the human avian influenza epidemic spread to 15 countries around the world, covering four continents: Asia, Europe, Africa and the United States. A total of 408 cases of avian influenza were reported, of which 254 died, with a fatality rate of 62.3%. It is therefore necessary to continuously monitor changes in the pattern of influenza A through the analysis of epidemiological data from laboratories around the world to confirm cases of human influenza A (H5N1) over the years, To explore the prediction method of short-term case number and the possible factors affecting case death. It also lays a foundation for the establishment of monitoring and early warning methods in China. Methods from December 2003 to February 2009, the data of laboratory confirmed human influenza A (H5N1) cases reported to WHO in 15 countries around the world were collected to establish a database. Based on the analysis of the annual age and sex distribution of human avian influenza cases, the median time from onset to hospitalization, the median time from onset to death, the change of family aggregation, seasonal trend and mortality, To determine whether the incidence pattern of human avian influenza has changed or not. Grey dynamic model and time series ARIMA model were used to predict the number of monthly and cumulative cases of human avian influenza, and multi-level logstic model and single-level logstic regression were used to screen the factors that might affect the death of human avian influenza. Result 1. The incidence pattern of human avian influenza was monitored between men and women in all age groups, and the sex ratio of male to female was 0.9 鈮，
本文编号：2490991
[Abstract]:Background and objective Human avian influenza (Human avian influenza,HAI) is infected by human contact with excreta or secretion contaminated by avian influenza virus, and the main symptoms such as respiratory tract infection and mucous congestion are zoonotic diseases, and the mortality rate is high. Respiratory failure and multiple organ damage can occur in some patients with highly pathogenic avian influenza strains (such as H5N1). From December 2003 to February 2009, the human avian influenza epidemic spread to 15 countries around the world, covering four continents: Asia, Europe, Africa and the United States. A total of 408 cases of avian influenza were reported, of which 254 died, with a fatality rate of 62.3%. It is therefore necessary to continuously monitor changes in the pattern of influenza A through the analysis of epidemiological data from laboratories around the world to confirm cases of human influenza A (H5N1) over the years, To explore the prediction method of short-term case number and the possible factors affecting case death. It also lays a foundation for the establishment of monitoring and early warning methods in China. Methods from December 2003 to February 2009, the data of laboratory confirmed human influenza A (H5N1) cases reported to WHO in 15 countries around the world were collected to establish a database. Based on the analysis of the annual age and sex distribution of human avian influenza cases, the median time from onset to hospitalization, the median time from onset to death, the change of family aggregation, seasonal trend and mortality, To determine whether the incidence pattern of human avian influenza has changed or not. Grey dynamic model and time series ARIMA model were used to predict the number of monthly and cumulative cases of human avian influenza, and multi-level logstic model and single-level logstic regression were used to screen the factors that might affect the death of human avian influenza. Result 1. The incidence pattern of human avian influenza was monitored between men and women in all age groups, and the sex ratio of male to female was 0.9 鈮，
本文编号：2490991
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