Roadmap for nematode control strategies

How can we use environmental and animal data to improve risk prediction for nematode infections at various geographical levels?
Can we understand farmers’ perspectives and experience to better identify high risk of negative impacts in livestock systems?

We need to better define whether animals with high production and large prolificacy are more at risk of nematode infection and impacts.
Explore the use of sentinel animals vs. the whole flock monitoring as the best approach to detect and prevent problems.

Knowledge of impacts of climate on transmission processes can be used to generate risk predictions for key nematode species.
Models to predict infection should consider climatic data, stocking rates, nutritional conditions, level of production and physiological stage to make a better early warning system for negative impacts on productivity rather than only for infection hazard.

User-friendly tools to non-invasively measure infection and its impacts, for farmer early warning and also to calibrate risk models.
Analysis of complex data (e.g. production metrics and animal sensors) in real time depends on big-data approaches, e.g. machine learning.

There are already some areas of the world where weather data are used to predict transmission risks (e.g. Haemonchus contortus, Nematodirus battus, Fasciola hepatica); these are usually large scale and generic and not easily translated to farmer decision support.
Tools for early warning of health status are in use for some nematodes (e.g. FAMACHA), and behavioural sensors are being widely evaluated.