Persistent colonization and the spread of antibiotic resistance in nosocomial pathogens: Resistance is a regional problem

Smith, David L.; Dushoff, Jonathan; Perencevich, Eli N.; Harris, Anthony D.; Levin, Simon A.

doi:10.1073/pnas.0400456101

Cited by 175 publications

(126 citation statements)

References 61 publications

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“…It is likely that the 'mixing' of patients and staff will have important impacts on the transmission dynamics, especially when considering multiple health-care facilities with a single community reservoir. Movements of individuals (particularly persistent carriers) between hospitals, long-term care facilities and community populations need to be included in order to model MRSA transmission dynamics effectively [31,32].…”

Section: Limitations Of the Modelmentioning

confidence: 99%

Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA)

2006

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SUMMARYWith reports of hospital-acquired methicillin-resistant Staphylococcus aureus (MRSA) continuing to increase and therapeutic options decrease, infection control methods are of increasing importance. Here we investigate the relationship between surveillance and infection control. Surveillance plays two roles with respect to control : it allows detection of infected/colonized individuals necessary for their removal from the general population, and it allows quantification of control success. We develop a stochastic model of MRSA transmission dynamics exploring the effects of two screening strategies in an epidemic setting : random and on admission. We consider both hospital and community populations and include control and surveillance in a single framework. Random screening was more efficient at hospital surveillance and allowed nosocomial control, which also prevented epidemic behaviour in the community. Therefore, random screening was the more effective control strategy for both the hospital and community populations in this setting. Surveillance strategies have significant impact on both ascertainment of infection prevalence and its control.

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Section: Limitations Of the Modelmentioning

confidence: 99%

Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA)

2006

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“…Mathematical models have provided important insights into how ARB evolve and proliferate (6,11,12,(17)(18)(19)(20) as well as into the relative efficiency of control strategies (21,22). Integrating a strategic framework that couples the economic incentives faced by institutions with population dynamic models enhances the insights based on models that rely on either one alone.…”

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confidence: 99%

“…Carriers can move resistance among hospitals, so hospitals with endemic resistance can ''infect'' other hospitals by discharging colonized patients or hiring from another hospital health-care workers who are carriers (6)(7)(8)(9). Moreover, recently hospitalized patients are more likely to be hospitalized again; carriers may be rehospitalized and continue to transmit with important epidemic implications (10)(11)(12). Over time, the proportion of people who are already colonized at the time of admission increases, which makes HIC more difficult.…”

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confidence: 99%

Strategic interactions in multi-institutional epidemics of antibiotic resistance

Smith

Levin

Laxminarayan

2005

Proc. Natl. Acad. Sci. U.S.A.

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109

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The increasing frequency of antibiotic resistance in hospital-acquired infections is a major public health concern that has both biological and economic causes. Here we develop conceptual mathematical models that couple the economic incentives and population biology of hospital infection control (HIC). We show that the optimal investment by a hospital for HIC changes with the proportion of patients already colonized with antibiotic-resistant bacteria (ARB) at the time of admission. As that proportion increases, the optimal behavior of a hospital is to increase spending to control ARB with low transmissibility and decrease spending on those with high transmissibility. In some cases, the global optimum investment in HIC can shift discontinuously from one that contains transmission to a do-nothing policy once the proportion already colonized at the time of admission becomes too great. We also show that investments in HIC are determined by a strategic game when several hospitals share patients. Hospitals acting selfishly and rationally will free-ride on the investments of other hospitals, and the level of free-riding should increase with the number of other hospitals in the area. Thus, in areas with many hospitals, the rational strategy for each hospital is to spend less than in areas with few hospitals. Thus, we predict that transmission rates and the prevalence of ARB should be higher in urban hospitals, for instance, compared with rural hospitals. We conclude that regional coordination and planning for HIC is an essential element of public health planning for hospital-acquired infections.game theory ͉ nosocomial infections ͉ infection control ͉ optimal control ͉ transmission dynamics

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“…This mathematical model provides a theoretical framework at the individual level. Structured population models, which incorporate the transmission of antimicrobial-resistant bacteria between patients, healthcare institutions and the community [2,10,34,35], are the next necessary steps to successfully understand the complexities of the emergence and spread of MDRGN, and to direct effective preventive strategies.…”

Section: Discussionmentioning

confidence: 99%

Quantifying the Impact of Bacterial Fitness and Repeated Antimicrobial Exposure on the Emergence of Multidrug-Resistant Gram-Negative Bacilli

D’Agata

Horn

Webb

2007

Math. Model. Nat. Phenom.

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Abstract. The emergence of multidrug resistance among gram-negative bacilli is complex. Numerous factors need to be considered, including the biological fitness cost of resistance, fitnesscompensatory mutations and frequency and type of antibiotic exposure. A mathematical model evaluating these complex relationships was developed in an individual colonized with strains of pan-susceptible, single-, two-and multidrug-resistant (MDR) gram-negative bacilli (GN). The effect of bacterial fitness, compensatory mutations and the frequency of three-antimicrobial regimen exposure to predominance of multidrug-resistant strains were quantified. The model predicts that initially, in the absence of antibiotic exposure, the biologically fitter pan-susceptible strain predominates over the resistant strains. Over time, the fitness of the MDR strains increases faster with repeated antimicrobial exposure, through compensatory-fitness mutations. Increasing the frequency of exposure to the three-antimicrobial regimen or, increasing the initial fitness of the resistant strains, substantially decreases the time to MDR-GN predominance. The model implies that when MDR-GN strains evolve into strains that are fitter than susceptible strains, a reduction in antimicrobial exposure may not result in a decrease of MDR-GN, since the absence of selective antimicrobial pressure would no longer favor susceptible strains. The model also implies that antimicrobial cycling may promote the emergence of MDR-GN.

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Persistent colonization and the spread of antibiotic resistance in nosocomial pathogens: Resistance is a regional problem

Cited by 175 publications

References 61 publications

Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA)

Screening strategies in surveillance and control of methicillin-resistant Staphylococcus aureus (MRSA)

Strategic interactions in multi-institutional epidemics of antibiotic resistance

Quantifying the Impact of Bacterial Fitness and Repeated Antimicrobial Exposure on the Emergence of Multidrug-Resistant Gram-Negative Bacilli

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