首页> 外文OA文献 >Microclimatic temperatures of Danish cattle farms: a better understanding of the variation in transmission potential of Schmallenberg virus
【2h】

Microclimatic temperatures of Danish cattle farms: a better understanding of the variation in transmission potential of Schmallenberg virus

机译:丹麦养牛场的小气候温度:更好地了解施马伦贝格病毒传播潜力的变化

摘要

Background: Insects inhabiting the surroundings of a cattle farm are exposed to microclimatic temperatures of the habitats surrounding the farm. Microclimatic temperatures are key drivers of the extrinsic incubation period (EIP), the speed by which an infected insect becomes infectious. The objective of this study was to quantify the variation of EIP of Schmallenberg virus among Danish cattle farms and identify possible spatial patterns of the EIPs. Methods: We quantified 21 different land cover classes within a 500 meter radius of all cattle farms in Denmark (N=22092) using CORINE land cover and regrouped them into four major land cover types: dry meadow, wet meadow, hedges, and forest. We then obtained the meteorological temperatures and other parameters (solar radiation, wind speed, humidity) near the farm from the Danish Meteorological Institute (DMI) for the period of 2000-2016. Using recently developed microclimatic temperature prediction models for those four major land cover types, we calculated the hourly microclimatic temperatures of each farm based on their surrounding habitat types and meteorological parameters. We then modelled the daily EIP of Schmallenberg virus for each farm for each year of the period of 2000-2016 using both hourly DMI and hourly microclimatic temperatures and calculated mean EIP of 17 years for each farm. Finally, we plotted the average spatial pattern of farm level EIP for spring (May-June), summer (July-August) and autumn (September-October) in Denmark for the 17 years. Results: Of the 22092 cattle farms, we were able to predict the hourly microclimatic temperatures of 22006 farms (99.6%) - the rest of the farms had habitats either not suitable for insects resting or the microclimatic model was not able to calculate the temperature of the surrounding land covers. We found a surprisingly large between-farm variation in EIP between farms on a specific day. For example, in the year 2016, the EIP of all farms varied (5th and 95th percentiles) from 9-19 days on May 1st, 12-23 days on July 1st and 11-21 days on September 1st . The mean EIP of Schmallenberg virus [inter quantile range (IQR)] of all the cattle farms during spring, summer, and autumn for 17 years period were 16 [13-17], 15 [13-16] and 40 [38-42] days respectively, when using microclimatic temperatures. These estimated EIP values were much shorter compared to EIP estimated using DMI temperatures for the same periods of spring (29 [27-30]), summer (21 [19-24]), and autumn (56 [55-58]) days respectively. For the summer period, we observed a large area where farms with shorter EIP for Schmallenberg virus were grouped together, comprising southern Funen and associated islands, Lolland, Falster, and southern Zealand. Conclusion: Microclimatic temperature is highly important for understanding and predicting insect-borne virus transmission on Danish cattle farms. We were able to predict the daily farm level EIP of Schmallenberg virus for 17 years. We found large variation in EIP between farms and also a spatial pattern with a strong geographical trend suggesting that disease transmission may vary substantially between regions even in a small country like Denmark – and this could be useful for designing risk based surveillance for emerging and reemerging vector-borne diseases.
机译:背景:居住在养牛场周围的昆虫暴露于该农场周围生境的微气候温度下。小气候温度是外在潜伏期(EIP)的关键驱动力,外在潜伏期是被感染昆虫传染的速度。这项研究的目的是量化丹麦奶牛场中Schmallenberg病毒的EIP变异并确定EIP的可能空间格局。方法:我们使用CORINE土地覆被量化了丹麦所有养牛场(N = 22092)半径500米半径内的21种不同的土地覆被类别,并将它们重新划分为四种主要的土地覆被类型:旱地草甸,湿地草甸,树篱和森林。然后,我们从丹麦气象研究所(DMI)获得了2000-2016年期间农场附近的气象温度和其他参数(太阳辐射,风速,湿度)。使用针对这四种主要土地覆盖类型的最新开发的微气候温度预测模型,我们根据其周围的栖息地类型和气象参数计算了每个农场的每小时微气候温度。然后,我们使用每小时DMI和每小时微气候温度对每个农场在2000-2016年期间的每年Schmallenberg病毒的EIP进行建模,并计算每个农场17年的平均EIP。最后,我们绘制了17年中丹麦春季(5月至6月),夏季(7月至8月)和秋季(9月至10月)农场平均EIP的平均空间格局。结果:在22092个牛场中,我们能够预测22006个农场的小时微气候温度(99.6%)-其余农场的生境要么不适合昆虫休息,要么微气候模型无法计算温度。周围的土地覆盖。我们发现特定日期的农场之间EIP的农场间差异非常大。例如,在2016年,所有农场的EIP(第5个百分位数和第95个百分位数)在5月1日的9-19天,7月1日的12-23天和9月1日的11-21天之间变化。在17年的春季,夏季和秋季,所有牛场的Schmallenberg病毒的平均EIP [分位数范围(IQR)]为16 [13-17],15 [13-16]和40 [38-42]使用微气候温度时分别为]天。与在春季(29 [27-30]),夏季(21 [19-24])和秋季(56 [55-58])相同时期使用DMI温度估算的EIP相比,这些估算的EIP值要短得多。分别。在夏季,我们观察到一个大区域,其中Schmallenberg病毒的EIP较短的农场被分组在一起,包括Funen南部和相关岛屿,Lolland,Falster和Southland南部。结论:微气候温度对于了解和预测昆虫传播的病毒在丹麦牛场中至关重要。我们能够预测Schmallenberg病毒在农场中的日常EIP水平达17年。我们发现农场之间的EIP差异很大,而且空间格局具有很强的地理趋势,这表明即使在像丹麦这样的小国,疾病的传播在各个地区之间也可能存在很大差异-这对于设计基于风险的新兴和新兴媒介监测方法可能很有用。传播疾病。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号