Publikationsdatenbank

Impact of mobility and contact patterns on disease status of egg-laying hens as revealed via radio frequency identification devices (2024)

Art

Vortrag

Autoren

Belik, Vitaly (WE 16)

Palmini, Andrea (WE 16)

Jarynowski, Andrzej (WE 16)

Welch, Mitchell

Sibanda, Terence

Pokrehl, Saluna

Ruhnke, Isabelle (WE 15)

Kongress

17th International Symposium on Veterinary Epidemiology and Economics

Sydney, Australia, 11. – 15.11.2024

Quelle

Sprache

Englisch

Verweise

URL (Volltext): https://isvee2024-c10000.eorganiser.com.au/data/clients/1/791/submissions/178786/abstract.pdf

Kontakt

Nutztierklinik: Abteilung Geflügel

Königsweg 63
14163 Berlin
+49 30 838 62676
gefluegelkrankheiten@vetmed.fu-berlin.de

Abstract / Zusammenfassung

In precision livestock farming usually the whole pen or shed is a unit of interest. To explore heterogeneity across individual birds, we examined free-range laying hens using RFID (radiofrequency identification) devices within an instrumented, commercial aviary system. These hens were observed throughout their laying cycle (over a 56-week period) and underwent necropsy at the end to detect clinical signs of infectious diseases. Our analysis involved the
following time series data:
Durations spent by individual hens at various locations within the aviary system, including the lower feeder, upper feeder, nest boxes, and the outdoor ranging area.
Recordings of potential contacts between individual hens within the range of specific antennae, with the duration of each contact noted.
Movements of individual hens between consecutively visited antennas.
We employed social network analysis, treating the hens and antennae as nodes, to investigate the spread of infectious diseases within the aviary. This analysis included calculating various types of hens' daily centralities (and their volatility) within a network. We also aimed to model within-farm transmission network dynamics using empirical contact data. Using logistic regression models with mixed effects, we assessed the predictive value of mobility and contact patterns for Spotty Liver Disease (a bacterial infection), Ascaridia galli, and Cestodes infections (both caused by parasites), as confirmed by postmortem examination. We are currently exploring the use of computer vision for monitoring contact patterns as part of ongoing experiments and linking implied contact networks and mobility patterns with egg productivity.