Individual or collective treatments: how to target antimicrobial use to limit the spread of \textit{Mannheimia haemolytica} among beef cattle?

TL;DR

This study uses a stochastic model to evaluate how different treatment strategies can reduce the spread of Mannheimia haemolytica in beef cattle, aiming to optimize antimicrobial use and improve animal health.

Contribution

It introduces a novel criterion based on disease spread speed for collective treatments, potentially reducing antimicrobial use more effectively than traditional methods.

Findings

Alternative treatment criterion reduces BRD incidence

Speed-based criteria outperform conventional methods

Highlights importance of responsible antimicrobial practices

Abstract

The overuse of antibiotics has become a major global concern due to its role in diminishing treatment effectiveness and positively selecting antibiotic-resistant bacterial strains. This issue is particularly important in the beef cattle sector, where Bovine Respiratory Diseases (BRD) impose significant economic and welfare burdens. BRD are complex, multifactorial conditions primarily affecting young calves and feedlot cattle, caused by a combination of viral and bacterial pathogens, environmental factors, and stressors. Despite efforts to reduce antimicrobial use (AMU), the cattle production system remains heavily reliant on antibiotics to control BRD, often through the implementation of collective treatments to prevent outbreaks. This study aimed at evaluating the impact of various treatment practices on the spread of BRD, specifically focusing on criteria for implementing collective treatments. Using a mechanistic stochastic model, we simulated the spread of \textit{Mannheimia haemolytica} in a multi-pen fattening operation under sixteen different scenarios, considering pen composition, individual risk levels, and treatment strategies. Our findings suggest that an alternative criterion for collective treatments based on the speed of the disease spread, could reduce BRD incidence and AMU more effectively than conventional methods. This research highlights the importance of responsible treatment practices and the potential benefits of novel criteria for collective treatment strategies in improving animal health. Moreover, it emphasizes the need for transparency on the exposure to risk factors along the production chain.