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A modelling framework for the prediction of the herd-level probability of infection from longitudinal data
View ORCID ProfileAurélien Madouasse, Mathilde Mercat, Annika van Roon, David Graham, Maria Guelbenzu, Inge Santman Berends, View ORCID ProfileGerdien van Schaik, Mirjam Nielen, Jenny Frössling, Estelle Ågren, Roger Humphry, View ORCID ProfileJude Eze, George Gunn, Madeleine Henry, Jörn Gethmann, Simon J. More, View ORCID ProfileChristine Fourichon
doi: https://doi.org/10.1101/2020.07.10.197426
Aurélien Madouasse
1BIOEPAR, INRA, Oniris, La Chantrerie, Nantes 44307, France
Mathilde Mercat
1BIOEPAR, INRA, Oniris, La Chantrerie, Nantes 44307, France
Annika van Roon
2Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, PO Box 80151, 3508, TD Utrecht, the Netherlands
David Graham
3Animal Health Ireland, Unit 4/5, The Archways, Bridge St., Carrick-on-Shannon, Co. Leitrim N41 WN27, Ireland
Maria Guelbenzu
3Animal Health Ireland, Unit 4/5, The Archways, Bridge St., Carrick-on-Shannon, Co. Leitrim N41 WN27, Ireland
Inge Santman Berends
2Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, PO Box 80151, 3508, TD Utrecht, the Netherlands
4GD Animal Health, PO Box 9, 7400 AA, Deventer, the Netherlands
Gerdien van Schaik
2Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, PO Box 80151, 3508, TD Utrecht, the Netherlands
4GD Animal Health, PO Box 9, 7400 AA, Deventer, the Netherlands
Mirjam Nielen
2Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, PO Box 80151, 3508, TD Utrecht, the Netherlands
Jenny Frössling
5Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), 751 89 Uppsala, Sweden
Estelle Ågren
5Department of Disease Control and Epidemiology, National Veterinary Institute (SVA), 751 89 Uppsala, Sweden
Roger Humphry
6Scotland’s Rural College, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, United Kingdom
Jude Eze
6Scotland’s Rural College, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, United Kingdom
George Gunn
6Scotland’s Rural College, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, United Kingdom
Madeleine Henry
6Scotland’s Rural College, Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, United Kingdom
Jörn Gethmann
7Institute of Epidemiology, Friedrich-Loeffler-Institute, Südufer 10, 17493 Greifswald, Germany
Simon J. More
8Centre for Veterinary Epidemiology and Risk Analysis, UCD School of Veterinary Medicine, University College Dublin, Belfield, Dublin D04 W6F6, Ireland
Christine Fourichon
1BIOEPAR, INRA, Oniris, La Chantrerie, Nantes 44307, France
Posted July 14, 2020.
A modelling framework for the prediction of the herd-level probability of infection from longitudinal data
Aurélien Madouasse, Mathilde Mercat, Annika van Roon, David Graham, Maria Guelbenzu, Inge Santman Berends, Gerdien van Schaik, Mirjam Nielen, Jenny Frössling, Estelle Ågren, Roger Humphry, Jude Eze, George Gunn, Madeleine Henry, Jörn Gethmann, Simon J. More, Christine Fourichon
bioRxiv 2020.07.10.197426; doi: https://doi.org/10.1101/2020.07.10.197426
A modelling framework for the prediction of the herd-level probability of infection from longitudinal data
Aurélien Madouasse, Mathilde Mercat, Annika van Roon, David Graham, Maria Guelbenzu, Inge Santman Berends, Gerdien van Schaik, Mirjam Nielen, Jenny Frössling, Estelle Ågren, Roger Humphry, Jude Eze, George Gunn, Madeleine Henry, Jörn Gethmann, Simon J. More, Christine Fourichon
bioRxiv 2020.07.10.197426; doi: https://doi.org/10.1101/2020.07.10.197426
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