Person:

Chang, Rose

The use of antibiotics in agriculture is routinely described as a major contributor to the clinical problem of resistant disease in human medicine. While a link is plausible, there are no data conclusively showing the magnitude of the threat emerging from agriculture. Here, we define the potential mechanisms by which agricultural antibiotic use could lead to human disease and use case studies to critically assess the potential risk from each. The three mechanisms considered are as follows 1: direct infection with resistant bacteria from an animal source, 2: breaches in the species barrier followed by sustained transmission in humans of resistant strains arising in livestock, and 3: transfer of resistance genes from agriculture into human pathogens. Of these, mechanism 1 is the most readily estimated, while significant is small in comparison with the overall burden of resistant disease. Several cases of mechanism 2 are known, and we discuss the likely livestock origins of resistant clones of Staphylococcus aureus and Enterococcus faecium, but while it is easy to show relatedness the direction of transmission is hard to assess in robust fashion. More difficult yet to study is the contribution of mechanism 3, which may be the most important of all.

BACKGROUND Staphylococcus aureus is a common cause of bacterial infections worldwide. It is most commonly carried in and transmitted from the anterior nares. Hosts are known to vary in their proclivity for S. aureus nasal carriage and may be divided into persistent carriers, intermittent carriers, and noncarriers, depending on duration of carriage. Mathematical models of S. aureus to predict outcomes of interventions have, however, typically assumed that all individuals are equally susceptible to colonization. OBJECTIVE To characterize biases created by assuming a homogeneous host population in estimating efficacy of control interventions. DESIGN Mathematical model. METHODS We developed a model of S. aureus carriage in the healthcare setting under the homogeneous assumption as well as a heterogeneous model to account for the 3 types of S. aureus carriers. In both models, we calculated the equilibrium carriage prevalence to predict the impact of control measures (reducing contact and decolonization). RESULTS The homogeneous model almost always underestimates S. aureus transmissibility and overestimates the impact of intervention strategies in lowering carriage prevalence compared to the heterogeneous model. This finding is generally consistent regardless of changes in model setting that vary the proportions of various carriers in the population and the duration of carriage for these carrier types. CONCLUSIONS Not accounting for host heterogeneity leads to systematic and substantial biases in predictions of the effects of intervention strategies. Further understanding of the clinical impacts of heterogeneity through modeling can help to target control measures and allocate resources more efficiently.