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Updated: Nov 15, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Comparing two predictive risk models for nematodirosis in Great Britain
Aidan Hopkinson1, Hannah R Vineer1, Dave Armstrong2
1Institute of Infection, Veterinary and Ecological Sciences, Leahurst Campus, University of Liverpool, Liverpool, UK.
Background:
Nematodirus battus infection is a major health concern in lambs. Development and hatch of infective larvae on pastures is temperature dependent, making model-based risk forecasting a useful tool for disease control.
Methods:
Air and 30 cm soil temperature-based risk models were used to predict hatch dates using meteorological data from 2019 and compared to infection dates, estimated from the first appearance of N. battus eggs, on 18 sheep farms distributed across Great Britain.
Results:
The air temperature model was more accurate in its predictions than the soil temperature model on 12 of the 18 farms, but tended to predict late hatch dates in the early part of the season.
Conclusion:
Overall, the air temperature model appears the more appropriate choice for predicting N. battus peak hatch in the UK in terms of accuracy and practicality, but some adjustment might be needed to account for microclimatic variations at the soil-air interface.
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