Young Sean G, Carrel Margaret, Malanson George P, Ali Mohamed A, Kayali Ghazi
Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA 52242, USA.
Department of Epidemiology, University of Iowa, Iowa City, IA 52242, USA.
Int J Environ Res Public Health. 2016 Sep 6;13(9):886. doi: 10.3390/ijerph13090886.
Human outbreaks with avian influenza have been, so far, constrained by poor viral adaptation to non-avian hosts. This could be overcome via co-infection, whereby two strains share genetic material, allowing new hybrid strains to emerge. Identifying areas where co-infection is most likely can help target spaces for increased surveillance. Ecological niche modeling using remotely-sensed data can be used for this purpose. H5N1 and H9N2 influenza subtypes are endemic in Egyptian poultry. From 2006 to 2015, over 20,000 poultry and wild birds were tested at farms and live bird markets. Using ecological niche modeling we identified environmental, behavioral, and population characteristics of H5N1 and H9N2 niches within Egypt. Niches differed markedly by subtype. The subtype niches were combined to model co-infection potential with known occurrences used for validation. The distance to live bird markets was a strong predictor of co-infection. Using only single-subtype influenza outbreaks and publicly available ecological data, we identified areas of co-infection potential with high accuracy (area under the receiver operating characteristic (ROC) curve (AUC) 0.991).
迄今为止,禽流感在人类中的爆发受到病毒对非禽类宿主适应性差的限制。这可以通过共感染来克服,即两种毒株共享遗传物质,从而产生新的杂交毒株。确定最有可能发生共感染的区域有助于确定加强监测的重点区域。利用遥感数据进行生态位建模可用于此目的。H5N1和H9N2流感亚型在埃及家禽中呈地方流行。2006年至2015年期间,在农场和活禽市场对2万多只家禽和野生鸟类进行了检测。我们利用生态位建模确定了埃及境内H5N1和H9N2生态位的环境、行为和种群特征。不同亚型的生态位差异显著。将亚型生态位结合起来,以模拟共感染潜力,并利用已知发生情况进行验证。与活禽市场的距离是共感染的一个有力预测指标。仅使用单亚型流感爆发情况和公开可用的生态数据,我们就高精度地确定了共感染潜力区域(受试者操作特征曲线(ROC)下面积(AUC)为0.991)。