Yale Occupational and Environmental Medicine Program, Yale University, New Haven, Connecticut, United States of America.
PLoS One. 2012;7(9):e43851. doi: 10.1371/journal.pone.0043851. Epub 2012 Sep 27.
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.
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.
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.
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.
大多数新发传染病均源于动物源（可在动物与人之间传播），因此，建议对人类和动物的疾病事件进行综合监测，以支持对疾病突发的有效全球应对。虽然过去十年间，对动物和人类中的高致病性禽流感（HPAI）感染进行了广泛的全球监测，但比较这些数据流并评估这种整合的效用的尝试很少。
我们比较了世界动物卫生组织（OIE）和联合国粮食及农业组织（FAO）EMPRESi 报告系统汇编的 2006-2011 年埃及 HPAI H5N1 鸟类疫情报告与同期向世界卫生组织（WHO）报告的埃及确诊人感染 H5N1 病例。
整体而言，人类病例和鸟类疫情均呈周期性模式，两种数据存在统计学上显著的时间相关性。在省一级，一个季节中的鸟类首次爆发通常但不总是先于首例人类病例，而且事件之间的时间间隔差异很大，这表明在动物源风险和/或监测效果方面存在地区差异。在多变量风险模型中，较低的温度、较低的城市化水平、较高的家禽密度以及近期发生的鸟类疫情与同一省内发生人类 HPAI 病例的风险增加相关，尽管鸟类疫情的阳性预测值较低。
整合人类和动物疾病监测数据流有望更好地预测疾病风险，并确定可能影响风险的环境和地区因素。此类努力还可以指出人类和动物监测系统中的差距，并对疾病传播提出假设。
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