Animal antibiotic use has an early but important impact on the emergence of antibiotic resistance in human commensal bacteria

Abstract

Antibiotic use is known to promote the development of antibiotic resistance, but substantial controversy exists about the impact of agricultural antibiotic use (AAU) on the subsequent emergence of antibiotic-resistant bacteria among humans. AAU for animal growth promotion or for treatment or control of animal diseases generates reservoirs of antibiotic-resistant (AR) bacteria that contaminate animal food products. Mathematical models are an important tool for understanding the potential medical consequences of this increased exposure. We have developed a mathematical model to evaluate factors affecting the prevalence of human commensal AR bacteria that cause opportunistic infections (e.g., enterococci). Our analysis suggests that AAU hastens the appearance of AR bacteria in humans. Our model indicates that the greatest impact occurs very early in the emergence of resistance, when AR bacteria are rare, possibly below the detection limits of current surveillance methods.

Figure 1

New strains of high-level resistant bacteria enter the human population because of background processes at rate μW or AAU at rate λW, where the fraction of humans carrying no resistant bacteria is W = 1 − X − Y − Z. Initially, humans are exposed (X), and the populations are transient. Exposed populations colonize (Y) at per capita rate θ or are lost at the per capita rate α. Colonized populations are lost at the much lower per capita rate σ < α. Both transient and persistent populations are assumed to have low-population densities, but antibiotic use in humans generates amplified population densities (Z) at the population rate ρ(X + Y). Once amplified, populations are lost at the per capita rate γ and recolonize at the per capita rate φ. Human-to-human transmission occurs at the rate βZW + ηYW, where the rate is higher after contact with amplified populations than colonized populations (β > η).

Figure 2

(A) The projected prevalence of AR over time with AAU (dotted line) and without AAU (solid line). AAU does not change the equilibrium prevalence dramatically, but it does cause AR to invade 3 years sooner. The cumulative excess prevalence is the area between these two curves. The medical consequences of AAU are contrasted with a 50% increase in the rate of MAU (dashed line). Increasing MAU use makes resistance invade earlier and reach a higher equilibrium. The parameter values correspond to Fig. 1. (B) The equilibrium prevalence is very sensitive to changes in the rate of MAU (ρ, solid line) relative to changes in the rate of exposure caused by AAU (λ, dashed line). The equilibrium was computed by multiplying the two parameters by a sensitivity factor, s, ranging from 0.5 to 2.0. At the square, R₀ = 1. The parameters at the circle correspond to Fig. 1. (C) The cumulative excess prevalence caused by AAU declines dramatically if exposure resulting from AAU is delayed. The longer AAU is delayed, the lower the impact. The units are scaled to the maximum impact. Each point, t, represents a numerical simulation identical to the top panel in every way except one. For each point, λ = 0 before t.