Agricultural antibiotics and human health

Abstract

Smith and colleagues discuss evidence suggesting that antibiotic use in agriculture has contributed to antibiotic resistance in the pathogenic bacteria of humans.

Figure 1. The Emergence and Spread of Antibiotic Resistance in Bacteria with High Horizontal Transmission Rates

Emergence and spread begins with a honeymoon period following the approval of a new antibiotic; the honeymoon ends when resistance emerges. Prevalence increases exponentially at first, but it eventually approaches a steady state. The impact of agricultural antibiotic use must be assessed by comparing the observed situation with the counterfactual situation, an imaginary world in which antibiotics were never used in agriculture. The impact of agricultural antibiotic use is, then, the total number of cases of resistance that would not have happened without the use of antibiotics in agriculture. This is approximately the difference between the time of actual emergence and the counterfactual emergence, multiplied by the steady-state prevalence. While we don't know what would have happened in any particular case, we can estimate the likely magnitude of agricultural impacts.

Figure 2. How Large Is the Impact of Antibiotic Use in Agriculture?

Comparing the amount of antibiotics used in agriculture with the amount used in medicine means comparing fundamentally different things because they affect the emergence of medically important antibiotic resistance in different ways. For hospital-acquired infections, it is more appropriate to think about ARB carriage in the community as a kind of pollution that flows into hospitals. Thus, the appropriate way to measure impact is by counting how many new carriers are added to the community reservoir from hospital discharges versus from exposure to bacteria that originate on farms. Different formulas describe these processes. To count ARB carriers among hospital discharges, let x denote the proportion of patients from a hospital (or other institution) that are colonized on discharge. In some discharged patients, resistant bacteria clear quickly, but a fraction, p, become ARB carriers. Some proportion of patients were already carriers at the time of admission, denoted by k. Institutions vary by size, H, and average length of stay (1/s). Thus, the rate that new carriers are discharged from a hospital is given by the formula: sH(px − k). This formula measures the contribution of a hospital to the number of ARB carriers in the community. For example, a hospital with 400 filled beds (H = 400 people) serves a US population of about 250,000 people. With a five-day average length of stay (the discharge rate is s = 0.2 per patient per day), the hospital discharges about 80 patients each day. If we suppose that 20% of patients acquire resistant bacteria while hospitalized, and one in four of these patients become carriers (px − k = 0.05), a hospital would discharge about four persistently colonized people per day—about 1,460 carriers after one year, or approximately 0.58% of its catchment population. A different formula characterizes heterospecific transmission, following exposure to ARB on contaminated food. We let g denote the daily per-capita rate that ARB are ingested with a meal. Similarly, we let h denote the proportion of those ARB populations that survive the gastric barrier and persistently colonize. The number of new carriers generated in the community by agricultural antibiotic use in a population of size N is: ghN. For example, if the average person consumes some ARB in 1% of meals (g = 0.03 per person per day), followed by colonization with probability one in 2,000 (h = 0.0005), agricultural antibiotic use would generate about four new carriers per day in a population of 250,000 people, N, approximately the same number as a hospital. The formulas illustrate a general principle: “A large number of people exposed to a small risk may generate many more cases than a small number exposed to a high risk” [34].