The Veterinary record · 2023
Is the Ollerenshaw fasciolosis forecasting model fit for the 21st century?
СтатьяНазвание и аннотация: Перевод в очереди
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Howell Alison, Caminade Cyril, Brülisauer Franz, Mitchell Sian, Williams Diana
Аннотация
BACKGROUND: The Ollerenshaw forecasting model is based on rainfall and evapotranspiration and has been in use to predict losses from fasciolosis since 1959. We evaluated the performance of the model against observed data.
METHODS: Weather data were used to calculate, map and plot fasciolosis risk values for each year from 1950 to 2019. We then compared the model's predictions with recorded acute fasciolosis losses in sheep from 2010 to 2019 and calculated the sensitivity and specificity of the model.
RESULTS: The forecast risk has varied over time but has not markedly increased over the past 70 years. The model correctly forecasted the highest and lowest incidence years at both the regional and national (Great Britain) levels. However, the sensitivity of the model for predicting fasciolosis losses was poor. Modification to include the full May and October rainfall and evapotranspiration values made only a small improvement.
LIMITATIONS: Reported acute fasciolosis losses are subject to bias and error due to unreported cases and variations in region size and livestock numbers.
CONCLUSION: The Ollerenshaw forecasting model, in either its original or modified forms, is insufficiently sensitive to be relied upon as a standalone early warning system for farmers.
METHODS: Weather data were used to calculate, map and plot fasciolosis risk values for each year from 1950 to 2019. We then compared the model's predictions with recorded acute fasciolosis losses in sheep from 2010 to 2019 and calculated the sensitivity and specificity of the model.
RESULTS: The forecast risk has varied over time but has not markedly increased over the past 70 years. The model correctly forecasted the highest and lowest incidence years at both the regional and national (Great Britain) levels. However, the sensitivity of the model for predicting fasciolosis losses was poor. Modification to include the full May and October rainfall and evapotranspiration values made only a small improvement.
LIMITATIONS: Reported acute fasciolosis losses are subject to bias and error due to unreported cases and variations in region size and livestock numbers.
CONCLUSION: The Ollerenshaw forecasting model, in either its original or modified forms, is insufficiently sensitive to be relied upon as a standalone early warning system for farmers.