An integrated individual-based model of transmission, clinical outcomes, and economic impact of Mycoplasma hyopneumoniae infection in a commercial pig fattening unit

Mycoplasma (M.) hyopneumoniae remains a major economic and health challenge for pig production worldwide, causing lung lesions and coughing that reduce production performance and farm profitability. However, the interplay between transmission, clinical outcomes, and economic consequences has not yet been fully characterised. To address this gap, a stochastic, individual-based bio-economic simulation model was developed using the EMULSION modelling framework. The model integrates infection dynamics, the development of lung lesions and coughing, and their subsequent effects on production performance and economic outcomes. Pigs were grouped within pens to represent within- and between-pen transmission. Production losses and additional labour requirements were translated into economic outcomes using a partial-budgeting approach. Model parameters were derived from scientific literature, representative industry reports and expert elicitation. Sensitivity analyses explored alternative distributions or values for key epidemiological parameters and assessed the effect of ± 20% variation in all input variables on biological and economic outputs. Simulations indicated that infection spread rapidly, reaching all pigs within 4-8 weeks, with peak prevalence approximately four weeks after fattening unit entry. Lung lesions followed a similar pattern, persisting at high prevalence for around two months, and a median of 14% of pigs still had unresolved lesions at slaughter. Coughing lagged about one week behind the rise in infection prevalence, reflecting the delay between infection and clinical signs. Median economic losses were €6 per pig, with reduced feed efficiency accounting for 73% of total losses. Sensitivity analyses identified between-pen transmission and initial prevalence as the most influential drivers of infection progression and profitability. The findings highlight key knowledge gaps, including the prevalence, infectiousness, and production impact of subclinical infections, as well as the need for longitudinal field data on lesion progression and between-pen transmission, to refine model assumptions and better align simulations with observations in practice. The modelling framework presented here provides a novel, integrated understanding of the biological and economic consequences of M. hyopneumoniae infection and a foundation for evaluating future control strategies.