Department of Spatial Sciences, Curtin University of Technology, GPO Box U1987, Perth, WA 6845, Australia.
Prev Vet Med. 2013 Jun 1;110(2):159-68. doi: 10.1016/j.prevetmed.2012.12.001. Epub 2012 Dec 29.
To monitor Bluetongue virus (BTV) activity in northern and eastern Australia the National Arbovirus Monitoring Program (NAMP) collects data from a network of sentinel herds. Groups of young cattle, previously unexposed to infection, are regularly tested to detect evidence of seroconversion. While this approach has been successful in fulfilling international surveillance requirements, it is labour and cost intensive and operationally challenging in the remote area of the northern Australian rangelands. The aim of this study was to assess the suitability of remotely sensed data as a means for predicting the distribution of BTV seroprevalence. For the period 2000-2009, bioclimatic variables were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) data products for the entire Northern Territory. A generalised linear model, based on the seasonal Normalised Difference Vegetation Index (NDVI) and minimum land surface temperature, was developed to predict BTV seropositivity. The odds of seropositivity in locations with NDVI estimates >0.45 was 3.90 (95% CI 1.11 to 13.7) times that of locations where NDVI estimates were between 0 and 0.45. Unit increases in minimum night land surface temperature in the previous winter increased the odds of seropositivity by a factor of 1.40 (95% CI 1.02 to 1.91). The area under a Receiver Operator Characteristic curve generated on the basis of the model predictions was 0.8. Uncertainty in the model's predictions was attributed to the spatio-temporal inconsistency in the precision of the available serosurveillance data. The discriminatory ability of models of this type could be improved by ensuring that exact location details and date of NAMP BTV test events are consistently recorded.
为了监测澳大利亚北部和东部的蓝舌病毒(BTV)活动,国家虫媒病毒监测计划(NAMP)从一个监测牛群网络中收集数据。定期对未接触过感染的年轻牛群进行检测,以检测血清转化的证据。虽然这种方法成功地满足了国际监测要求,但在澳大利亚北部偏远地区,这种方法劳动力和成本密集,操作具有挑战性。本研究旨在评估遥感数据作为预测 BTV 血清流行率分布的一种手段的适宜性。在 2000-2009 年期间,从中分辨率成像光谱仪(MODIS)和热带降雨测量任务(TRMM)数据产品中提取了生物气候变量,用于整个北领地。基于季节性归一化差异植被指数(NDVI)和最低地表温度的广义线性模型被开发出来,以预测 BTV 血清阳性率。NDVI 估计值>0.45 的地点的血清阳性率的可能性是 NDVI 估计值在 0 到 0.45 之间的地点的 3.90 倍(95%CI 1.11 至 13.7)。上一个冬季最低夜间地表温度的单位增加会使血清阳性率增加 1.40 倍(95%CI 1.02 至 1.91)。基于模型预测生成的接收者操作特征曲线下面积为 0.8。模型预测的不确定性归因于可用血清监测数据的精度的时空不一致性。通过确保一致记录 NAMP BTV 测试事件的确切位置详细信息和日期,可以提高此类模型的区分能力。