Rapid emergence of co-colonization with community-acquired and hospital-acquired methicillin-resistant Staphylococcus aureus strains in the hospital setting
aa r X i v : . [ q - b i o . P E ] J un Rapid emergence of co-colonization with community-acquired andhospital-acquired methicillin-resistant
Staphylococcus aureus strains inthe hospital setting
Erika M. C. D’Agata , Glenn F. Webb , and Joanna Pressley Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Harvard MedicalSchool, Boston, MA 02215, Department of Mathematics, Vanderbilt University, Nashville,TN 37240Keywords: methicillin resistance,
Staphylococcus aureus , community, hospital, co-colonizationRunning title: co-colonization with different MRSA strainsCorrespondence to:Erika D’Agata MD MPHBeth Israel Deaconess Medical Center, Division Infectious Diseases330 Brookline Ave, East Campus Mailstop SL-435GBoston, MA 02215e-mail address: [email protected] (617) 667-8127; fax (617) 667-7251
ABSTRACTBackground:
Community-acquired methicillin-resistant
Staphylococcus aureus (CA-MRSA), a novel strain of MRSA, has recently emerged and rapidly spreadin the community. Invasion into the hospital setting with replacement ofthe hospital-acquired MRSA (HA-MRSA) has also been documented. Co-colonization with both CA-MRSA and HA-MRSA would have important clinicalimplications given differences in antimicrobial susceptibility profiles and the po-tential for exchange of genetic information.
Methods:
A deterministic mathematical model was developed to characterizethe transmission dynamics of HA-MRSA and CA-MRSA in the hospital settingand to quantify the emergence of co-colonization with both strains.
Results:
The model analysis shows that the state of co-colonization becomesendemic over time and that there is no competitive exclusion of either strain.Increasing the length of stay or rate of hospital entry among patients colonizedwith CA-MRSA leads to a rapid increase in the co-colonized state. Comparedto MRSA decolonization strategy, improving hand hygiene compliance has thegreatest impact on decreasing the prevalence of HA-MRSA, CA-MRSA and theco-colonized state.
Conclusions:
The model predicts that with the expanding community reservoirof CA-MRSA, the majority of hospitalized patients will become colonized withboth CA-MRSA and HA-MRSA.
Introduction
Methicillin-resistant
Staphylococcus aureus (MRSA) has been traditionally considereda hospital-acquired bacteria and is implicated in the great majority of infections acquiredin the hospital [1]. The documentation of a novel MRSA strain, which has emerged in thecommunity and has subsequently spread into the hospital, has led to a re-evaluation of thetransmission dynamics of MRSA in the healthcare setting [2, 3]. Several population-basedsurveillance studies have documented that the community-acquired MRSA (CA-MRSA)may be replacing the hospital-acquired MRSA (HA-MRSA) [4, 5, 6]. Mathematicalmodels corroborate these findings and predict that there will be competitive exclusionof HA-MRSA strains by CA-MRSA over time [7]. Previous studies have assumed thatindividuals can only be colonized or infected with either HA-MRSA or CA-MRSA. Datasuggest however, that individual colonization with multiple
Staphylococcus aureus strainsoccurs [8]. Co-colonization with multiple strains of other bacterial species has also beendocumented [9]. Understanding the emergence and spread of co-colonization with bothCA-MRSA and HA-MRSA would have important clinical implications given differences inantimicrobial susceptibility profiles and virulence properties between these two strains [10].Co-colonization can also result in the horizontal transfer of mobile genetic elements betweenstrains, such as antimicrobial-resistance or virulence determinants. These events maylead to the emergence of MRSA strains with novel biological properties. A mathematicalmodel was developed to understand the emergence and spread of co-colonization withboth CA-MRSA and HA-MRSA among hospitalized individuals. This model extends aprevious model characterizing the transmission dynamics of CA-MRSA into the hospitalsetting, which assumed that patients could only be colonized or infected with either CA-or HA-MRSA [7]. Key factors, which contribute to the spread of antibiotic-resistantbacteria and their impact on the emergence of a co-colonized state in the hospital setting,were analyzed through model simulations. The impact of an increased influx of patientsharboring CA-MRSA into the hospital was quantified using data from population-basedsurveillance studies, which document an expanding community reservoir of CA-MRSA.Differences in length of stay (LOS) among patients harboring CA-MRSA were also analyzedsince patients infected with CA-MRSA can present, with severe infections leading to longerLOS. Lastly, infection control strategies aimed at limiting the spread of MRSA and theireffect on the emergence of the co-colonized state were evaluated.
MethodsMathematical Model
A deterministic model was developed to characterize the transmission dynamicsof HA-MRSA and CA-MRSA in the hospital setting and to quantify the emergence ofco-colonization with both CA-MRSA and HA-MRSA among hospitalized patients.Individuals in the hospital are in four exclusive states: susceptible ( S ), colonized witheither CA-MRSA ( C ), HA-MRSA ( H ) or both CA- and HA-MRSA ( B ). The infected stateis not included. Patients enter the hospital as S , C or H . To understand the emergenceof the co-colonized state, the model assumes that there is no co-colonization at baselineand that patients do not enter the hospital in the B state. Patients leave the hospitalvia death or hospital discharge in all four states. Through contact with a contaminatedhealthcare workers (HCW), susceptible patients becomes colonized with either CA-MRSAat a rate (1 − η ) β C or HA-MRSA at a rate of rate (1 − η ) β H . Here, η signifies compliancewith hand hygiene measures with 0 ≤ η ≤ η = 0 corresponds to no compliance and η = 1 corresponds to perfect compliance. Transmission rates of CA-MRSA and HA-MRSAare given by β C and β H respectively. Once in the C or H state, patients can transitionto the co-colonization state, B , through contact with a HCW, contaminated with eitherHA-MRSA or CA-MRSA, with rates (1 − η ) β CH or (1 − η ) β HC , respectively (see figure 1and appendix for model details).The LOS among CA-MRSA colonized patients was assumed to equal to the LOS ofsusceptible patients in the baseline model. The LOS for the co-colonized compartmentstarts after acquisition of the second strain and, as a simplification, is set equal tothe larger of the LOS for patients colonized with CA-MRSA or the LOS for patientscolonized with HA-MRSA. Since patients colonized with MRSA can develop an infectionduring their hospitalization, thereby substantially prolonging their LOS, simulations wereperformed to quantify the impact of an increasing LOS on the transmission dynamics ofHA-MRSA, CA-MRSA and the emergence of the co-colonization state. Simulations werealso performed to determine the impact of an increase in the percent of patients enteringthe hospital already colonized with CA-MRSA. Model simulations evaluating the impactof hand-hygiene and decolonization of MRSA colonized patients, two key infection controlstrategies, were also performed. Since several different decolonization strategies are availablewith varying efficacy, the decolonization parameters of patients colonized with CA-MRSA( α C ), HA-MRSA ( α H ), or co-colonized ( α B ) ranged from 0% efficacy (no decolonization) to100% efficacy.The mathematical model assumes that the likelihood of transmission of CA-MRSA andHA-MRSA are equal ( β C = β H ). In vitro data suggest that the growth rate of CA-MRSA isfaster than that of HA-MRSA for certain CA-MRSA strains. This biological difference mayallow CA-MRSA to have an advantage towards colonization and subsequent transmissioncompared to HA-MRSA. To understand the implications of a greater transmission potentialamong CA-MRSA strains, the baseline model and above simulations were re-analyzed with β C > β H [11, 12].Parameter estimates were obtained from infection control data, microbiology data, andpatient data from a 400-bed tertiary care hospital with approximately 25,000 admissionsper year. Estimates were also obtained from published studies focusing on the epidemiologyof CA-MRSA or HA-MRSA (Table 1) [5, 11, 12, 13, 14, 15, 16]. ResultsTransmission dynamics of HA-MRSA and CA-MRSA and co-colonization
Baseline model
A baseline model was developed to quantify the prevalence of patients colonizedwith HA-MRSA, CA-MRSA, or both strains over time. To understand the underlyingtransmission dynamics of HA- and CA-MRSA and the emergence of co-colonization withboth strains, this baseline model assumes that there is no entry of patients who are alreadycolonized with MRSA into the hospital (all entering patients are susceptible). Analysisshows that when the basic reproduction numbers satisfy R H > R C > β = β C = β H = β HC = β CH and α = α C = α H = α B , the model analysisalso demonstrates that there is no competitive exclusion of either strain, when both R C > R H >
1. Over time, the prevalence of patients colonized with HA-MRSA exceeds theprevalence of patients colonized with CA-MRSA since R H > R C . The greater R H valuefor HA-MRSA compared to the R C value for CA-MRSA reflects the longer LOS amongHA-MRSA patients, which results in greater opportunities for HA-MRSA transmission(figure 2). Simulation 1: increased transmission of CA-MRSA and HA-MRSA
Increasing patient-to-patient transmission through patient contact with HCWcontaminated with either HA-MRSA or CA-MRSA results in a substantial increase in thepercent of co-colonized patients. As transmission increases, more patients are colonizedwith MRSA and less are susceptible, and therefore more patients that are colonized withindividual strains become co-colonized. Above a threshold value of β , the percent ofpatients co-colonized with both strains exceeds those colonized with either CA-MRSA orHA-MRSA (figure 3). Simulation 2: increasing the influx of patients colonized with CA-MRSA intothe hospital and their LOS
Increasing the rate of admission of patients colonized with CA-MRSA or increasingtheir LOS results in an increase in the co-colonized state (figures 4 and 5). LOS hasa substantially greater impact on the prevalence of co-colonization compared to rate ofadmission. Even a minimal increase in LOS from the baseline value of 5 days to 8 daysleads to the majority of colonized patients represented by the co-colonized state. Thepredominance of the co-colonization state when LOS increases is explained by the increasedopportunity for HA-MRSA colonized patients to become colonized with CA-MRSA andbecome colonized with both strains.
Simulation 3: interventions to prevent transmission
The effect of two standard interventions aimed at preventing the transmission of MRSA,improving compliance with hand-hygiene and maximizing the efficacy of decolonization ofpatients with MRSA, were evaluated in simulations which included an influx of patientsharboring HA-MRSA or CA-MRSA. Both interventions decrease the percentage of colonizedpatients in all three states. Compared to decolonization, improving hand-hygiene has thegreater impact with even small increases in compliance having a substantial effect in theoverall prevalence of MRSA. Since there is a constant influx of colonized patients into thehospital setting, CA- and HA-MRSA are never eradicated from the hospital even at 100%hand-hygiene compliance or 100% decolonization efficacy. In contrast, the absence of aninflux of patients who are co-colonized into the hospital explains the extinction of the Bstate when these two interventions are at 100% compliance or efficacy. As hand-hygienecompliance increases, the total percentage of patients colonized decreases monotonically.However, simulations show that after 2 years, the percentage of patients who only haveHA-MRSA increases until hand-hygiene reaches about 45% (figure 6).The explanation for this finding is as follows. Susceptible patients move to the singlecolonized state with a rate (1 − η ) β and from the single colonized state to the both statewith a rate (1 − η ) β . Therefore there is a quadratic effect of hygiene on transmissionto the co-colonized state. When hand-hygiene compliance is low (and the co-colonizedcompartment is large), the quadratic effect of increasing hand-hygiene compliance, causes arapid reduction of the co-colonized compartment, and increases the population of susceptiblepatients in the equilibrium. Transmission to the single colonization compartments ( C and H ) is dependent both on η and S by the term (1 − η ) βN S . Until hand-hygiene reaches about45%, the rise in S due to the quadratic effect on the co-colonization state is stronger thanthe reduction in transmission due to increasing η . Therefore, the sizes of the C and H compartments increase. Simulations assuming greater transmission potential for CA-MRSA comparedto HA-MRSA
The overall results of simulations with β C = 1 . β H were similar to those with β C = β H except for a greater and more rapid increase in CA-MRSA and co-colonized patients (datanot shown). Discussion
The transmission dynamics of MRSA in the hospital setting are complex and requirethe analysis of numerous interrelated and dynamic factors. The emergence of CA-MRSAand its invasion into the hospital setting has led to further complexities in understandingnot only the spread of MRSA, but also the selection of effective antimicrobial therapies andpreventive strategies. Since epidemiological studies cannot fully address these complexities,a mathematical model was developed to specifically quantify the emergence of individualsco-colonized with both CA-MRSA and HA-MRSA strains.The deterministic model shows that over time, there will be no competitive exclusionof either strain but that both CA-MRSA and HA-MRSA will co-exist in the hospitalsetting. The model also shows that individuals co-colonized with both strains will increasein prevalence over time and will predominate over individuals who are colonized witheither CA-MRSA or HA-MRSA. These findings have important implications. First, clinicalcultures will usually identify only one strain, either CA-MRSA or HA-MRSA. Mathematicalmodels have shown that 20 colonies per patient need to be sampled to reliably estimatethe occurrence of multiple strains [17]. Since sampling of multiple colonies is not feasible,co-colonization and polyclonal infections will therefore not be routinely detected. Thedifferent antimicrobial susceptibility profiles of CA-MRSA and HA-MRSA and identification0of only one strain may therefore lead to incorrect antimicrobial therapy. The emergence ofmultidrug-resistant strains of CA-MRSA, with susceptibility profiles similar to HA-MRSAmay however minimize difficulties in selection of the appropriate antimicrobial amongco-colonized patients [18].Factors which increase the reservoir of CA-MRSA in the hospital setting were shownto have substantial effects on the magnitude of the co-colonized patient population.Increasing the influx of patients harboring CA-MRSA into the hospital and increasingtheir LOS resulted in a rapid increase in the number of co-colonized patients. Previousmathematical models have also shown that these two factors are central to the disseminationof antimicrobial-resistant bacteria [7, 19]. Our model shows that even small increases in LOSof only few days from a conservative baseline estimate of 5 days among CA-MRSA patientsresulted in the rapid predominance of patients colonized with both strains. CA-MRSAis associated with severe infections and several studies have documented that CA-MRSAhas become the predominant MRSA strain implicated in the great majority of nosocomialblood stream infections and surgical site infections [4, 20, 21]. These nosocomial infectionswould therefore substantially extend the LOS of patients harboring CA-MRSA.Our model revealed the effects of two interventions targeting the prevention of MRSAspread: improving compliance with hand-hygiene and decolonization strategies. Bothinterventions decreased the prevalence of HA-MRSA, CA-MRSA and co-colonization. Asshown in previous models, improving hand-hygiene compliance had the greatest effect withonly small improvements in compliance [7].Several assumptions were made to simplify the model. First, antibiotic pressure andits effect on the transmission dynamics of CA-MRSA and emergence of co-colonizationwere not assessed. Given the different susceptibility profiles between HA-MRSA andCA-MRSA, selective antibiotic pressure may alter the transmission dynamics between1HA-MRSA and CA-MRSA. Second, environmental contamination was not included sincethere is a paucity of data regarding differences in contamination of inanimate surfacesbetween CA-MRSA and HA-MRSA. Future models will need to include these factors.Our main model assumed that the likelihood of transmission between CA-MRSA andHA-MRSA from HCW to patient and vice versa was equal. In vitro studies have shownthat the growth rate of certain CA-MRSA strains is faster compared to HA-MRSA strainssuggesting that CA-MRSA may have an advantage towards colonization and thereforegreater transmissibility [11, 12]. Model simulations using greater transmission parametersfor CA-MRSA showed similar conclusions to the baseline model except for more rapiddynamics of CA-MRSA spread and emergence of co-colonization. Lastly, a deterministicmodel was used which compartmentalizes patients into homogeneous groups and thereforeindividual-level behavior was not addressed. Although stochastic individual-based modelscan simulate the heterogeneity of patients and HCW interactions, the increase in behavioraldetails provided by these models may result in greater difficulty in interpretation of findings.Colonization with different strains and species of bacteria is common [9]. Thisstudy quantified the emergence and spread of co-colonization with both CA-MRSA andHA-MRSA. The study demonstrated that the expanding community reservoir of CA-MRSAresulting in an increase influx of CA-MRSA patients into the hospital setting coupledwith prolonged LOS associated with severe CA-MRSA infections will rapidly lead to apredominance of patients who are colonized with both strains. The impact of these findingson patient outcomes and the potential for transfer of genetic information between thesestrains will require ongoing evaluation.2
Acknowledgments
This work was supported in part by the joint DMS/NIGMS Initiative through theNational Institute of Health Grant R01GM083607 (EMCD, GFW, JP).Potential Conflicts of interest: EMCD, GFW, JP no conflicts.3
Appendix
A reduced version of D’Agata et al [7] was developed, which exhibits the samequalitative properties as the original, but which lacks the infective states. The patientpopulation is split into three compartments: S - susceptible patients, C - patients colonizedwith CA-MRSA and H - patients colonized with HA-MRSA. We added the assumptionthat the total number of patients was conserved at size N = 400, allowing us to reduceby one dimension to the compartments C and H , by letting S = N − C − H − B . Themodel is analyzed without this assumption in an accompanying paper, and the results arequalitatively the same.We then extended the model, allowing patients to be concurrently co-colonized withCA-MRSA and HA-MRSA, which adds a third (or fourth if there is no conservation)compartment, B - patients colonized with ”B”oth CA-MRSA and HA-MRSA. The rate ofchange of the size of the compartments due to the transmission of MRSA in the hospital isthen described by the following system of nonlinear ordinary differential equations: dCdt = ( δ S S + δ C C + δ H H ) λ C + (1 − η ) β C N S ( C + B ) − (1 − η ) β CH N C ( H + B ) − ( δ C + α C ) C (1) dHdt = ( δ S S + δ C C + δ H H ) λ H + (1 − η ) β H N S ( H + B ) − (1 − η ) β CH N H ( C + B ) − ( δ H + α H ) H (2) dBdt = ( δ S S + δ C C + δ H H ) λ B + (1 − η ) β CH N C ( H + B ) + (1 − η ) β HC N H ( C + B ) − ( δ B + α B ) B, (3)with S = N − C − H − B . Parameter explanations and values are given in Table 1.Assuming that all patients enter the hospital susceptible ( λ C = λ H = λ B = 0),there exists a disease free equilibrium (DFE) of the system, where all patients are4susceptible, S = N and ( C, H, B ) = (0 , , max { R H , R C } <
1, where R H = (1 − η ) β H α H + δ H is the basicreproduction number for HA-MRSA and R C = (1 − η ) β C α C + δ C is the basic reproduction numberfor CA-MRSA. This means that if max { R H , R C } <
1, both strains of MRSA will beextinguished over time.In addition to the DFE, there are two other analytically known equilibria, E H and E C ,which describe states where one disease is endemic while the other absent. When E H isstable, HA-MRSA will be endemic in the hospital and CA-MRSA will be extinguished overtime. Therefore, the size of the compartments S and H will be positive and the size ofcompartments C and B will be zero. Symmetrically, when E C is stable, CA-MRSA will beendemic and HA-MRSA will be extinguished over time.A fourth equilibrium, in which the size of every compartment is positive, does not havea known analytic form but is consistently found in numerical simulations.The invasion reproduction number [22] I E H and E C . When I E H > E H is unstable, CA-MRSAinvades, or becomes endemic, and both strains become prevalent in the hospital over time.Conversely, if I E H < E H is stable and only HA-MRSA will be endemic in the hospitalover time. Symmetrically, when I E C > E C is unstable and both strains become endemicover time. Conversely, if I E C < E C is stable and only CA-MRSA will be endemic in thehospital. I E H = R C R H (1 − η ) β CH ( α B + δ B ) (cid:0) − R H (cid:1) + 1 (1 − η ) β CH ( α C + δ C ) (cid:0) − R H (cid:1) + 1 ! + (1 − η ) β HC α B + δ B (cid:18) − R H (cid:19) . (4)A symmetric form is found for I E C , since the model is symmetric in C and H .5Assuming β C = β H = β CH = β HC and α C = α H = α B , as we do in this paper, I E H = 11 − R H + R C + R H − R H > R C > I E H > I E C . Therefore, neither endemic equilibrium is stable when R H > R C >
1, and there is never competitive exclusion. If patients continuallyenter the hospital colonized with MRSA, then it can never be completely extinguished. Inan accompanying paper, the model is more thoroughly investigated mathematically.6
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USA 300 genotype as a major cause ofhealth care-associated blood stream infections. Clin Infect Dis ;42;647-66.22. Xiridou M, Borkent-Raven B, Hulshof J, Wallinga J. How Hepatitis D Virus Can Hinderthe Control of Hepatitis B Virus. PLoS ONE. ; 4:e5247.This manuscript was prepared with the AAS L A TEX macros v5.2.9Table 1: Parameter estimates for the transmission dynamics of community-acquired andhospital-acquired methicillin-resistant
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Parameter Symbol Baseline Value Source
Total number of patients N 400Percent of admissions per dayColonized CA-MRSA 100 λ C λ H /δ S /δ C /δ H /δ B η β C β H β CH β HC α C
0% 15,16HA-MRSA 100 α H α B SC H ∆ S H -Λ C -Λ H -Λ B L Α C I - Η L Β C I - Η L Β H Α H ∆ H Λ H Λ C ∆ C B I - Η L Β HC I - Η L Β CH Α B Λ B ∆ B Fig. 1.— A compartment model describing the transmission dynamics of CA-MRSA andHA-MRSA in a 400-bed hospital. The arrows and parameter values correspond to entry andexit from the 4 compartments ( S -susceptible patients, C -patients colonized with CA-MRSA, H -patients colonized with HA-MRSA, and B -patients co-colonized with both strains). Thepercentages of patients admitted colonized with CA-MRSA, colonized with HA-MRSA, orcolonized with both strains are expressed as 100 λ C , 100 λ H , and 100 λ B , respectively. Dis-charge and death rates from the compartments are expressed as follows: δ S , δ C , δ H , and δ B for susceptible patients, patients colonized with CA-MRSA, patients colonized with HA-MRSA, and patients co-colonized with both strains, respectively (with mean length of staysdefined as 1 /δ S , 1 /δ C , 1 /δ H , and 1 /δ B ). The colonization rates of susceptible patients to theCA-MRSA compartment is (1 − η ) β C and to the HA-MRSA compartment is (1 − η ) β H . Theco-colonization rate from C to the co-colonized compartment ( B ) is (1 − η ) β CH and from H to B is (1 − η ) β HC , where 100 η signifies the percentage of hand-hygiene compliance (where η = 0 corresponds to 0% compliance and η = 1 corresponds to 100% compliance). The ratesof decolonization of patients with CA-MRSA, HA-MRSA, or both strains are given by α C , α H , and α B , respectively.1 Time H Days L % C o l on i ze d Co - colonizedCA - MRSAHA - MRSA