Comparison of Human and Animal Surveillance Data for H5N1 Influenza A in Egypt 2006-2011
Comparison of Human and Animal Surveillance Data for H5N1 Influenza A in Egypt 2006-2011
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DOI：
10.1371/journal.pone.0043851
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发表时间：
2012-09-27
期刊：
影响因子：
3.7
通讯作者：
Kane, Michael
中科院分区：
文献类型：
--
作者：
Rabinowitz, Peter M.;Galusha, Deron;Kane, Michael
背景资料：大多数新出现的传染病的起源是人畜共患（动物和人类之间传播），因此建议对人类和动物的疾病事件进行综合监测，以支持对疾病的出现采取有效的全球应对措施。虽然在过去十年中，全球对动物和人类高致病性禽流感（HPAI）感染进行了广泛的监测，但很少有人尝试比较这些数据流并评估这种整合的效用。方法：我们比较了世界动物卫生组织（OIE）编制的2006-2011年埃及鸟类HPAI H5 N1疫情报告。和联合国粮食及农业组织（粮农组织）EMPRESi报告系统与确认人间H5 N1病例报告给世界卫生组织（世卫组织）在同一时期为Egypt.Principal调查结果：人间病例和鸟类疫情显示了一个循环模式，为全国作为一个整体，有统计学显着的时间之间的相关性的数据流。在省一级，一个季节中鸟类中的首次疫情通常但不总是先于首例人间病例，事件之间的时间间隔差异很大，表明人畜共患病风险和/或监测有效性存在区域差异。在一个多变量风险模型中，较低的温度、较低的城市化程度、较高的家禽密度和最近发生的禽类疫情与同一省份人类高致病性禽流感病例风险增加相关，尽管禽类疫情的阳性预测值较低。整合人畜共患病病例监测的数据流有望更好地预测疾病风险，确定可能影响风险的环境和区域因素。这种努力还可以指出人类和动物监测系统的差距，并提出关于疾病传播的假设。
Background: The majority of emerging infectious diseases are zoonotic (transmissible between animals and humans) in origin, and therefore integrated surveillance of disease events in humans and animals has been recommended to support effective global response to disease emergence. While in the past decade there has been extensive global surveillance for highly pathogenic avian influenza (HPAI) infection in both animals and humans, there have been few attempts to compare these data streams and evaluate the utility of such integration.Methodology: We compared reports of bird outbreaks of HPAI H5N1 in Egypt for 2006-2011 compiled by the World Organisation for Animal Health (OIE) and the UN Food and Agriculture Organization (FAO) EMPRESi reporting system with confirmed human H5N1 cases reported to the World Health Organization (WHO) for Egypt during the same time period.Principal Findings: Both human cases and bird outbreaks showed a cyclic pattern for the country as a whole, and there was a statistically significant temporal correlation between the data streams. At the governorate level, the first outbreak in birds in a season usually but not always preceded the first human case, and the time lag between events varied widely, suggesting regional differences in zoonotic risk and/or surveillance effectiveness. In a multivariate risk model, lower temperature, lower urbanization, higher poultry density, and the recent occurrence of a bird outbreak were associated with increased risk of a human case of HPAI in the same governorate, although the positive predictive value of a bird outbreak was low.Conclusions: Integrating data streams of surveillance for human and animal cases of zoonotic disease holds promise for better prediction of disease risk and identification of environmental and regional factors that can affect risk. Such efforts can also point out gaps in human and animal surveillance systems and generate hypotheses regarding disease transmission.