Delivering training that is context specific and adapted to different audiences and actors in a surveillance network is absolutely critical to the effectiveness of this training, and eventually the success of the surveillance network. Help us create a library of training resource that can be used, re-used, and adapted.

As wildlife health practitionners, we often take for granted the value of wildlife health surveillance, yet sustainable support for wildlife health surveillance requires a rigorous articulation of the value of wildlife health surveillance data. A first step in this direction can be the collection of case studies where wildlife health surveillance data has effectively resulted in management action or policy changes. We are seeking your support in collecting these stories from your own experience.

Many emerging wildlife surveillance system are lacking appropriate data management system. However, expecting each surveillance system to build their own data management platform would be costly and inefficient. WHIN aim to leverage community input and best practices in data management to offer a standard data model and implement a data management platform that is made available for end-users to manage their data privately and securely. TO ensure the data model is suitable for a wide diversity of data types, help us test our data model with your exemples of data structures.