Controlling methicillin-resistant Staphylococcus aureus: quantifying the effects of interventions and rapid diagnostic testing

Abstract

Control of nosocomial transmission of methicillin-resistant Staphylococcus aureus (MRSA) has been unsuccessful in most countries. Yet, some countries have maintained low endemic levels by implementing nationwide MRSA-specific infection control measures, such as "search & destroy" (S&D). These strategies, however, are not based on well designed studies, and their use in countries with high levels of endemicity is controversial. We present a stochastic three-hospital model and an analytical one-hospital model to quantify the effectiveness of different infection control measures and to predict the effects of rapid diagnostic testing (RDT) on isolation needs. Isolation of MRSA carriers identified by clinical cultures is insufficient to control MRSA. However, combined with proactive search (of high-risk patients on admission and/or contacts of index patients), it will maintain prevalence levels <1%. Concerted implementation of S&D in countries with high nosocomial endemicity reduces nosocomial prevalence to <1% within 6 years. Stepwise implementation of control measures can reduce isolation capacities needed. RDT can reduce isolation needs by >90% in low-endemic settings and by 20% in high-endemic settings. Surveillance of colonization and improved hand hygiene can markedly increase control efficacy. These findings strongly suggest that: (i) causality exists between S&D and low MRSA prevalence; (ii) isolating MRSA carriers identified by clinical cultures as a single measure is insufficient for control; (iii) a combined approach of isolation and screening confers efficacy; and (iv) MRSA-prevalence levels can be reduced to <1% in high-endemic settings by S&D or a stepwise approach to interventions. RDT can markedly enhance feasibility.

Fig. 1.

Patient dynamics (a) and MRSA dynamics (b) within a hospital. Solid arrows, relatively frequent processes; dotted arrows, relatively infrequent ones.

Fig. 2.

Extramural (a) and intramural (b) MRSA prevalence starting from low endemicity. The black line denotes the mean result of 1,000 simulations with 90% of the simulations falling in the gray region. The two colored lines in a represent individual simulations. The prevalence in these simulations rises faster than the mean over 1,000 simulations.

Fig. 3.

Effect of intervention strategies on nosocomial prevalence levels when isolation is 100% effective. (a) Initial low prevalence. (b) Initial high prevalence. For description of interventions, see Interventions.

Fig. 4.

Changes in critical reproduction ratio (R₀^c) for several combinations of intervention measures according to changes in model parameters. Default values of the parameter are shown in Table 1. (a) Relative increase in critical transmission parameter β_c for a hospital with wards of size N compared with a hospital consisting of wards of infinite size (i.e., without depletion of susceptibles). (b–e) Critical reproduction ratio R₀^c for one of the intervention strategies as function of one of the parameters. (b) Effect of improvement of hand hygiene. (c) Core group size. (d) Detection rate of colonized patients (one per day). (e) Mean length of colonization. (See Figs. 7–10, which are published as supporting information on the PNAS web site, for more information.)

Fig. 5.

Effect of RDT. (a) Effect in low-endemicity settings with S&D. RDT will reduce unnecessary precautionary isolation days of high-risk patients. However, with suboptimal test characteristics, RDT may fail to identify some of the MRSA carriers among contact patients (because of false-negative RDT results) and may identify noncarriers as MRSA carriers (because of false-positive RDT results). Both effects will balance for certain test characteristics, and these lines are depicted. The upper line represents the scenario in which conventional cultures are used as back-up; the lower line is the scenario without back-up cultures. Above the lines, the use of RDT will increase the number of isolation days needed. Below the lines, reduction of isolation days will dominate and the net effect will thus be fewer isolation days. (b and c) Effect of RDT with measures I + II + III for four culture regimes: No RDT, RDT with sensitivity and specificity of 90%, RDT with sensitivity and specificity of 90% with backup of standard culture methods, and RDT with sensitivity of 90% and specificity of 100% with backup of standard culture methods. For the first 5 years, efficacy of isolation is 50%; afterward, efficacy is 80%. (b) Effect on the prevalence level in hospitals. (c) Expected isolation (iso) days.

Fig. 6.

Effect of (stepwise) introduction of intervention measures for high-endemic settings. (Upper) Nosocomial prevalence. (Lower) Number of isolation days. (a and d) Isolation of patients with a positive clinical culture for different levels of isolation efficacy. (b and e) Increment of isolation efficacy from 50% to 80% after 5 years for several intervention measures. (c and f) First 5 years, isolation of colonized patients (measure I) with 80% efficacy. Additional interventions are implemented after 5 years (isolation efficacy remains at 80%).