Using Object-Oriented Simulation to Assess the Impact of the Frequency and Accuracy of Mobility Scoring on the Estimation of Epidemiological Parameters for Lameness in Dairy Herds.

dairy cattle duration frequency incidence lameness mobility scoring object-oriented simulation prevalence sensitivity specificity

Journal

Animals : an open access journal from MDPI
ISSN: 2076-2615
Titre abrégé: Animals (Basel)
Pays: Switzerland
ID NLM: 101635614

Informations de publication

Date de publication:
11 Jun 2024
Historique:
received: 24 04 2024
revised: 17 05 2024
accepted: 04 06 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 27 6 2024
Statut: epublish

Résumé

Mobility scoring data can be used to estimate the prevalence, incidence, and duration of lameness in dairy herds. Mobility scoring is often performed infrequently with variable sensitivity, but how this impacts the estimation of lameness parameters is largely unknown. We developed a simulation model to investigate the impact of the frequency and accuracy of mobility scoring on the estimation of lameness parameters for different herd scenarios. Herds with a varying prevalence (10, 30, or 50%) and duration (distributed around median days 18, 36, 54, 72, or 108) of lameness were simulated at daily time steps for five years. The lameness parameters investigated were prevalence, duration, new case rate, time to first lameness, and probability of remaining sound in the first year. True parameters were calculated from daily data and compared to those calculated when replicating different frequencies (weekly, two-weekly, monthly, quarterly), sensitivities (60-100%), and specificities (95-100%) of mobility scoring. Our results showed that over-estimation of incidence and under-estimation of duration can occur when the sensitivity and specificity of mobility scoring are <100%. This effect increases with more frequent scoring. Lameness prevalence was the only parameter that could be estimated with reasonable accuracy when simulating quarterly mobility scoring. These findings can help inform mobility scoring practices and the interpretation of mobility scoring data.

Identifiants

pubmed: 38929379
pii: ani14121760
doi: 10.3390/ani14121760
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Innovate UK
ID : 48717

Auteurs

Rachel Clifton (R)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.

Robert Hyde (R)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.

Edna Can (E)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.

Matthew Barden (M)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.

Al Manning (A)

Quality Milk Management Services Ltd., Cedar Barn, Wells BA5 1DU, UK.

Andrew Bradley (A)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.
Quality Milk Management Services Ltd., Cedar Barn, Wells BA5 1DU, UK.

Martin Green (M)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.

Luke O'Grady (L)

School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, UK.

Classifications MeSH