The basic reproduction quotient (Q0) as a potential spatial predictor of the seasonality of ovine haemonchosis
The basic reproduction quotient (Q0) as a potential spatial predictor of the seasonality of ovine haemonchosis
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DOI：
10.4081/gh.2015.356
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发表时间：
2015-01-01
影响因子：
1.7
通讯作者：
Morgan, Eric R.
中科院分区：
文献类型：
--
作者：
Bolajoko, Muhammad-Bashir;Rose, Hannah;Morgan, Eric R.
捻转血矛线虫是一种小型反刍动物的胃肠道线虫寄生虫，以血液为食，会导致绵羊和山羊严重疾病和产量损失，特别是在世界温暖地区。生命周期包括自由生活的未成熟阶段，其发育、生存和可用性受到气候影响，因此该物种在其感染压力方面表现出基于盛行气候的时空异质性。更好地解释这种异质性的模型可以预测未来的流行病学变化。基本繁殖商数 (Q(0)) 被用作一个简单的基于过程的模型来预测气候驱动的 H. contortus 在不同地理气候带的潜在传播变化，并与绵羊胃肠道线虫动物群中观察到的该物种的频率非常一致 (r = 0.81，P < 0.01)。地理信息系统 (GIS) 进一步使用平均月 Q0 输出来绘制英国 (UK) 四年历史跨度和未来气候变化情景下的初步血吸虫病风险地图。预计英国各地的传播季节将延长，特别是在南部，尽管由于降雨限制，夏季高峰传播受到限制。如果宿主密度和分布、放牧模式和土壤条件等信息作为风险层包含在基于 GIS 的风险地图中，则可能会实现额外的预测能力。然而，此类风险地图的验证提出了重大挑战，因为具有足够空间和时间分辨率的地理参考观测数据很少可用且难以获得。
Haemonchus contortus is a gastrointestinal nematode parasite of small ruminants, which feeds on blood and causes significant disease and production loss in sheep and goats, especially in warmer parts of the world. The life cycle includes free-living immature stages, which are subject to climatic influences on development, survival and availability, and this species therefore exhibits spatio-temporal heterogeneity in its infection pressure based on the prevailing climate. Models that better explain this heterogeneity could predict future epidemiological changes. The basic reproduction quotient (Q(0)) was used as a simple process-based model to predict climate-driven changes in the potential transmission of H. contortus across widely different geo-climatic zones, and showed good agreement with the observed frequency of this species in the gastrointestinal nematode fauna of sheep (r = 0.81, P < 0.01). Averaged monthly Q0 output was further used within a geographical information system (GIS) to produce preliminary haemonchosis risk maps for the United Kingdom (UK) over a four-year historical span and under future climate change scenarios. Prolonged transmission seasons throughout the UK are predicted, especially in the south although with restricted transmission in peak summer due to rainfall limitation. Additional predictive ability might be achieved if information such as host density and distribution, grazing pattern and edaphic conditions were included as risk layers in the GIS-based risk map. However, validation of such risk maps presents a significant challenge, with georeferenced observed data of sufficient spatial and temporal resolution rarely available and difficult to obtain.