Hospital-community interactions foster coexistence between methicillin-resistant strains of Staphylococcus aureus

A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance

The use of an antibiotic may lead to the emergence and spread of bacterial strains resistant to this antibiotic. Experimental and theoretical studies have investigated the drug dose that minimizes the risk of resistance evolution over the course of treatment of an individual, showing that the optimal dose will either be the highest or the lowest drug concentration possible to administer; however, no analytical results exist that help decide between these two extremes. To address this gap, we develop a stochastic mathematical model of bacterial dynamics under antibiotic treatment. We explore various scenarios of density regulation (bacterial density affects cell birth or death rates), and antibiotic modes of action (biostatic or biocidal). We derive analytical results for the survival probability of the resistant subpopulation until the end of treatment, the size of the resistant subpopulation at the end of treatment, the carriage time of the resistant subpopulation until it is replaced by a sensitive one after treatment, and we verify these results with stochastic simulations. We find that the scenario of density regulation and the drug mode of action are important determinants of the survival of a resistant subpopulation. Resistant cells survive best when bacterial competition reduces cell birth and under biocidal antibiotics. Compared to an analogous deterministic model, the population size reached by the resistant type is larger and carriage time is slightly reduced by stochastic loss of resistant cells. Moreover, we obtain an analytical prediction of the antibiotic concentration that maximizes the survival of resistant cells, which may help to decide which drug dosage (not) to administer. Our results are amenable to experimental tests and help link the within and between host scales in epidemiological models.

Bioprospecting of aqueous phase from pyrolysis of plant waste residues to disrupt MRSA biofilms

Methicillin resistant Staphylococcus aureus (MRSA) infections have increased at an alarming rate, recently. In India, stubble burning and air pollution due to the burning of agricultural and forest residues have also increased over the past decade causing environmental and health hazards. This work evaluates the anti-biofilm property of the aqueous phase obtained from pyrolysis of wheat straw (WS AQ) and pine cone (PC AQ) against an MRSA isolate. The WS AQ and PC AQ compositions were determined by GC-MS analysis. The minimum inhibitory concentration was found to be 8% (v v^-1) and 5% (v v^-1) for WS AQ and PC AQ, respectively. The eradication of biofilms was performed on hospital contact surfaces namely, stainless steel and polypropylene and found to be 51% and 52% for WS AQ and PC AQ, respectively. Compounds identified from the aqueous phase of WS and PC docked against AgrA protein showed good binding scores.

Methicillin-Resistant Staphylococcus aureus Membrane Vesicles Inhibit the Proliferation and Induce the Apoptosis of Epithelial Cells

Staphylococcus aureus, or methicillin-resistant Staphylococcus aureus (MRSA), is the predominant pathogen in skin and soft tissue infections (SSTIs), and MRSA membrane vesicles (MVs) play a pivotal role in bacterial pathogenesis and the modulation of the host immune response. We aimed to investigate the interaction between MRSA MVs and epithelial cells. In this study, MVs were isolated from an MRSA culture supernatant using the ELD method, comprising an electrophoretic technique used in combination with a 300 kDa cut-off dialysis bag. The proteomic analysis of the MRSA MVs via mass spectrometry showed that shared and distinct proteins exist in the MVs from clinical MRSA isolates with different genetic backgrounds, such as health-care-associated MRSA (HA-MRSA) and community-associated MRSA (CA-MRSA). These MRSA MVs were found to suppress the proliferation and increase the apoptosis of HaCaT cells. We conducted qPCR array, quantitative real-time PCR (qRT-PCR), and Western blotting (WB) analyses, and the results indicated that BCL2 antagonist/killer 1 (Bak1) may be involved in the apoptosis of HaCaT epithelial cells. Our findings suggest that MRSA MVs inhibit the proliferation and induce the apoptosis of epithelial cells.

Improving mathematical modeling of interventions to prevent healthcare-associated infections by interrupting transmission or pathogens: How common modeling assumptions about colonized individuals impact intervention effectiveness estimates

Mathematical models are used to gauge the impact of interventions for healthcare-associated infections. As with any analytic method, such models require many assumptions. Two common assumptions are that asymptomatically colonized individuals are more likely to be hospitalized and that they spend longer in the hospital per admission because of their colonization status. These assumptions have no biological basis and could impact the estimated effects of interventions in unintended ways. Therefore, we developed a model of methicillin-resistant Staphylococcus aureus transmission to explicitly evaluate the impact of these assumptions. We found that assuming that asymptomatically colonized individuals were more likely to be admitted to the hospital or spend longer in the hospital than uncolonized individuals biased results compared to a more realistic model that did not make either assumption. Results were heavily biased when estimating the impact of an intervention that directly reduced transmission in a hospital. In contrast, results were moderately biased when estimating the impact of an intervention that decolonized hospital patients. Our findings can inform choices modelers face when constructing models of healthcare-associated infection interventions and thereby improve their validity.

Clonal Distribution and Antibiotic Susceptibility of Staphylococcus aureus from Pediatric Patients: 8-Year Trends in a Children's Hospital in Colombia

Emergence of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) strains in healthcare settings has changed the hospital epidemiology of MRSA in the last few years. Despite a global increase in MRSA frequency, infections caused by methicillin-susceptible S. aureus (MSSA) have persisted in healthcare settings and the community. Staphylococcus aureus isolates were collected between 2009 and 2017 at the Children's Hospital of a Caribbean city in South America. Methicillin-resistant isolates were subjected to SCCmec typing. Representative isolates were analyzed by multilocus sequence typing (MLST) and spa typing. Antibiotic susceptibility was assessed by agar dilution method. D-zone test was performed in erythromycin-resistant isolates to determine macrolide/lincosamide/streptogramin resistance. Spa typing revealed 10 different spa types. The main epidemic clones circulating during the study period were: ST8-MRSA-IVc, ST923-MRSA-IVa and ST8-MRSA-IVa. The study found high frequencies of PVL genes and resistance to erythromycin and clindamycin in the isolates. This study provides the first description of the population structure of MRSA and MSSA causing infections attended in the participating Children's Hospital. ST8-MRSA-IVc, ST923-MRSA-IVa and ST8-MRSA-IVa were the most prevalent in the isolate population.

Microbiome-pathogen interactions drive epidemiological dynamics of antibiotic resistance: A modeling study applied to nosocomial pathogen control

The human microbiome can protect against colonization with pathogenic antibiotic-resistant bacteria (ARB), but its impacts on the spread of antibiotic resistance are poorly understood. We propose a mathematical modeling framework for ARB epidemiology formalizing within-host ARB-microbiome competition, and impacts of antibiotic consumption on microbiome function. Applied to the healthcare setting, we demonstrate a trade-off whereby antibiotics simultaneously clear bacterial pathogens and increase host susceptibility to their colonization, and compare this framework with a traditional strain-based approach. At the population level, microbiome interactions drive ARB incidence, but not resistance rates, reflecting distinct epidemiological relevance of different forces of competition. Simulating a range of public health interventions (contact precautions, antibiotic stewardship, microbiome recovery therapy) and pathogens (Clostridioides difficile, methicillin-resistant Staphylococcus aureus, multidrug-resistant Enterobacteriaceae) highlights how species-specific within-host ecological interactions drive intervention efficacy. We find limited impact of contact precautions for Enterobacteriaceae prevention, and a promising role for microbiome-targeted interventions to limit ARB spread.

Longitudinal changes and regional variation of incident infection rates at cystic fibrosis centers, United States 2010-2016

BACKGROUND

Multiple factors affect incident infection rates (IIR) for Pseudomonas aeruginosa (PA) and methicillin resistant Staphylococcus aureus (MRSA) at CF care centers. We assessed changes in IIR across CF centers temporally associated with the 2013 Infection/Prevention & Control guidelines controlling for center-specific factors.

METHODS

Using the CF Foundation Patient Registry we defined and measured changes in IIR between 2010-2012 and 2014-2016. Data were compared to non-CF rates of MRSA and resistant PA in geographically similar regions. Characteristics of each CF center (n centers: Adult 54 in 2010 to 82 in 2016. Pediatric ∼106) and their respective population were evaluated for associations with IIR and with changes in IIR between the study periods.

RESULTS

Across the years 35613 patients were included. Incident-infection rates for PA (mean 19.2±0.04% Pediatric, 21.2±0.07% Adult centers) were higher than for MRSA (mean 9.4±0.03% Pediatric, 7.8±0.03% Adult). The IIR decreased for MRSA (-1.54±0.54%, p<0.001) and PA (-4.77±0.63%, p<0.001) at Pediatric but only for PA (-3.20±1.31, p=0.02) at Adult centers. Except for Adult CF, MRSA rates (CF and non-CF) were highest in the South. In 2014-2016, private insurance and a higher proportion of LatinX patients at a center were associated with lower MRSA IIR while larger center size, higher proportion of LatinX, and lower mean center-wide lung function were associated with higher PA IIR. Higher IIR in 2010-2012, were predictive of a more pronounced decrease in IIR in 2014-2016 for MRSA and PA (p<0.001). Different factors indicative of lower social status (smoking, insurance, education) in 2010-2012 predicted decreases in MRSA or PA IIR.

CONCLUSION

Comparisons of IIR across U.S. CF centers should consider location, ethnic background and socio-economic variables of a center's population.

Modeling the effect of vaccination on selection for antibiotic resistance in Streptococcus pneumonia e

Vaccines against bacterial pathogens can protect recipients from becoming infected with potentially antibiotic-resistant pathogens. However, by altering the selective balance between antibiotic-sensitive and antibiotic-resistant bacterial strains, vaccines may also suppress-or spread-antibiotic resistance among unvaccinated individuals. Predicting the outcome of vaccination requires knowing what drives selection for drug-resistant bacterial pathogens and what maintains the circulation of both antibiotic-sensitive and antibiotic-resistant strains of bacteria. To address this question, we used mathematical modeling and data from 2007 on penicillin consumption and penicillin nonsusceptibility in Streptococcus pneumoniae (pneumococcus) invasive isolates from 27 European countries. We show that the frequency of penicillin resistance in S. pneumoniae can be explained by between-host diversity in antibiotic use, heritable diversity in pneumococcal carriage duration, or frequency-dependent selection brought about by within-host competition between antibiotic-resistant and antibiotic-sensitive S. pneumoniae strains. We used our calibrated models to predict the impact of non-serotype-specific pneumococcal vaccination upon the prevalence of S. pneumoniae carriage, incidence of disease, and frequency of S. pneumoniae antibiotic resistance. We found that the relative strength and directionality of competition between drug-resistant and drug-sensitive pneumococcal strains was the most important determinant of whether vaccination would promote, inhibit, or have little effect upon the evolution of antibiotic resistance. Last, we show that country-specific differences in pathogen transmission substantially altered the predicted impact of vaccination, highlighting that policies for managing antibiotic resistance with vaccines must be tailored to a specific pathogen and setting.

A dose response model for Staphylococcus aureus

Dose-response models (DRMs) are used to predict the probability of microbial infection when a person is exposed to a given number of pathogens. In this study, we propose a new DRM for Staphylococcus aureus (SA), which causes skin and soft-tissue infections. The current approach to SA dose-response is only partially mechanistic and assumes that individual bacteria do not interact with each other. Our proposed two-compartment (2C) model assumes that bacteria that have not adjusted to the host environment decay. After adjusting to the host, they exhibit logistic/cooperative growth, eventually causing disease. The transition between the adjusted and un-adjusted states is a stochastic process, which the 2C DRM explicitly models to predict response probabilities. By fitting the 2C model to SA pathogenesis data, we show that cooperation between individual SA bacteria is sufficient (and, within the scope of the 2C model, necessary) to characterize the dose-response. This is a departure from the classical single-hit theory of dose-response, where complete independence is assumed between individual pathogens. From a quantitative microbial risk assessment standpoint, the mechanistic basis of the 2C DRM enables transparent modeling of dose-response of antibiotic-resistant SA that has not been possible before. It also enables the modeling of scenarios having multiple/non-instantaneous exposures, with minimal assumptions.

Feline Otitis Externa Caused by Methicillin-Resistant Staphylococcus aureus with Mixed Hemolytic Phenotype and Overview of Possible Genetic Backgrounds

Methicillin-resistant Staphylococcus aureus (MRSA) is an important cause of nosocomial infections in humans, but its importance in small animal practice is increasing. Here, we present a case of feline otitis externa (OE) caused by MRSA; both hemolytic and nonhemolytic variants with a stable phenotype were recovered from the external auditory canal after infection was detected by routine otoscopy. One isolate per variant underwent antimicrobial susceptibility testing (AST) by broth microdilution method, conventional spa typing and whole-genome sequencing (WGS). The results showed that both variants were genetically related and were of sequence type (ST) 1327, SCCmec type IV and spa type t005. AST and WGS showed that both isolates were resistant to β-lactams and sensitive to all tested non-β-lactam antibiotics. Both isolates were pvl-negative, but encoded several other virulence genes (aur, hlgABC, sak, scn, seg, sei, sem, sen, seo and seu). Genetic background of the mixed hemolytic phenotype was not identified; no differences in the agr locus or other regulatory regions were detected. Three single-nucleotide polymorphisms were identified but could not be associated with hemolysis. This well-documented case of MRSA infection in companion animals adds to the reports of MRSA infections with a mixed hemolytic phenotype.

Universal admission screening: a potential game-changer in hospitals with high prevalence of MRSA

INTRODUCTION

Despite the perception that meticillin-resistant Staphylococcus aureus (MRSA) is now under control in high-income countries, global prevalence remains high, even increasing in some regions. Universal admission screening and decolonization has been instituted in some hospitals to attempt control but the practice remains controversial.

METHODS

In 2014, Mater Dei Hospital in Malta introduced a universal admission screening policy, utilizing a novel, centralized and customized approach to achieve high compliance and low cost. Admissions are screened nasally by designated staff using chromogenic media, irrespective of risk factors. Carriers are decolonized without concurrent isolation or contact precautions. In this study, longitudinal, quasi-experimental evaluation was undertaken using time series analysis to analyse the impact of the intervention on the proportion of MRSA among clinical S. aureus isolates (%MRSA) and incidence per 1000 bed-days. A cost-utility analysis was also attempted to identify approximate quality-adjusted life years (QALYs) gained.

RESULTS

A transfer function model approach concluded that the intervention had a significant effect on both %MRSA and incidence. Six years following its introduction, the screening programme had led to an overall 43% long-term reduction in %MRSA from pre-screening levels [R²=0.687; Bayesian information criterion (BIC)=4.063], translating to a decrease in incidence of approximately 0.56 cases/1000 bed-days (R²=0.633, BIC=-3.063). No correlation was identified with consumption of antibiotics or alcohol hand rub. The annual cost-benefit of the programme was calculated at €1058 per QALY gain per year.

CONCLUSION

The universal admission screening and decolonization intervention was successful and cost-effective in this high-endemicity setting. It facilitated improvement in the prevalence of MRSA, achieving reduction levels rarely reported by Mediterranean hospitals.

Constellation of methicillin-resistant genomic islands (SCCmec) among nasal meticillin-resistant Staphylococcus aureus isolates

The apprehensiveness for the knowledge vacuum on existential threat of nasal carriage of pvl+ healthcare-acquired meticillin-resistant Staphylococcus aureus (HA-MRSA) strains amongst subjects in hospitals have led us to pursue a grasp on the constellation of staphylococcal cassette chromosome mec (SCCmec) types and pvl gene among mecA positive MRSA nasal strains. This was accomplished by phenotypic (catalase, coagulase, Microgen staph ID, ORSAB) and genotypic (polymerase chain reaction) biotyping techniques. All the mecA+ strains harboured the SCCmec gene; SCCmec type I prevailed in 43.75% and pvl was found in 42.1% of the isolates. Dual carriage of mecA and pvl genes occurred in six (37.5%, n = 6/16) strains. Overall, majority of the mecA+ MRSA strains documented in this study carried SCCmec elements of the HA genotype with a hint of community-acquired (CA)genotype suggesting a possible coexistence of both HA-MRSA and community-acquiredhealthcare-acquired meticillin-resistant Staphylococcus aureus (CA-MRSA) strains. Consequently, the implementation of methodical surveillance is needed for the evaluation of potential shifts in directionality of (HA-MRSA/CA-MRSA) pvl+ MRSA clones in our hospitals for effective and prudent antimicrobial stewardship.

Population structure across scales facilitates coexistence and spatial heterogeneity of antibiotic-resistant infections

Antibiotic-resistant infections are a growing threat to human health, but basic features of the eco-evolutionary dynamics remain unexplained. Most prominently, there is no clear mechanism for the long-term coexistence of both drug-sensitive and resistant strains at intermediate levels, a ubiquitous pattern seen in surveillance data. Here we show that accounting for structured or spatially-heterogeneous host populations and variability in antibiotic consumption can lead to persistent coexistence over a wide range of treatment coverages, drug efficacies, costs of resistance, and mixing patterns. Moreover, this mechanism can explain other puzzling spatiotemporal features of drug-resistance epidemiology that have received less attention, such as large differences in the prevalence of resistance between geographical regions with similar antibiotic consumption or that neighbor one another. We find that the same amount of antibiotic use can lead to very different levels of resistance depending on how treatment is distributed in a transmission network. We also identify parameter regimes in which population structure alone cannot support coexistence, suggesting the need for other mechanisms to explain the epidemiology of antibiotic resistance. Our analysis identifies key features of host population structure that can be used to assess resistance risk and highlights the need to include spatial or demographic heterogeneity in models to guide resistance management.

Dynamic contact networks of patients and MRSA spread in hospitals

Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult-to-treat infection. Increasing efforts have been taken to mitigate the epidemics and to avoid potential outbreaks in low endemic settings. Understanding the population dynamics of MRSA is essential to identify the causal mechanisms driving the epidemics and to generalise conclusions to different contexts. Previous studies neglected the temporal structure of contacts between patients and assumed homogeneous behaviour. We developed a high-resolution data-driven contact network model of interactions between 743,182 patients in 485 hospitals during 3,059 days to reproduce the exact contact sequences of the hospital population. Our model captures the exact spatial and temporal human contact behaviour and the dynamics of referrals within and between wards and hospitals at a large scale, revealing highly heterogeneous contact and mobility patterns of individual patients. A simulation exercise of epidemic spread shows that heterogeneous contacts cause the emergence of super-spreader patients, slower than exponential polynomial growth of the prevalence, and fast epidemic spread between wards and hospitals. In our simulated scenarios, screening upon hospital admittance is potentially more effective than reducing infection probability to reduce the final outbreak size. Our findings are useful to understand not only MRSA spread but also other hospital-acquired infections.

Rationally designed curcumin based ruthenium(ii) antimicrobials effective against drug-resistant Staphylococcus aureus

Two new curcumin containing octahedral ruthenium(ii) polypyridyl complexes, viz. [Ru(NN)2(cur)](PF6) [NN = bpy (1), phen (2)], were designed to explore the antimicrobial activity against ESKAPE pathogens, especially with the Gram-positive drug resistant S. aureus. Solid-state structural characterization by single-crystal X-ray crystallography shows the RuII-center in a distorted octahedral {RuN4O2} geometry. The tested compounds showed significant inhibitory activity and high selectivity (MIC = 1 μg mL-1, SI = 80) against a wide variety of methicillin and vancomycin-resistant S. aureus strains. Compound 1 exhibited strong anti-biofilm activity (48% reduction of biofilm) at 10× MIC compared to the other approved drugs. The murine model of Staphylococcus infection significantly reduced the mean bacterial counts when treated with complex 1 compared to vancomycin, demonstrating its antimicrobial potential in vivo.

Systematic comparison of coexistence in models of drug-sensitive and drug-resistant pathogen strains

A number of mathematical models have recently been proposed to explain empirical trends of pathogen diversity. In particular, long-term coexistence of both drug-sensitive and drug-resistant variants of a single pathogen is something of a mystery, given that simple models of pathogens competing for the same ecological niche predict competitive exclusion, and more complex models admitting coexistence require assumptions that may not be justified. Coinfection is among the candidate mechanisms to generate coexistence, as it occurs in many pathogens and provides the opportunity for strains to interact directly. Recently, coinfection and competitive release have been described as creating a form of negative frequency-dependent selection that promotes coexistence, and a range of models containing coinfection have been proposed as having generic stable coexistence of multiple strains. This abundance of new models presents the challenge of comparison and interpretation. To this end, we describe a dimensionless quantity that can be used to compare the amount of coexistence generated by different models. We focus on models that include coinfection, although this framework could be generalized to a larger class of structured models.

The evolution of antibiotic resistance in a structured host population

The evolution of antibiotic resistance in opportunistic pathogens such as Streptococcus pneumoniae, Escherichia coli or Staphylococcus aureus is a major public health problem, as infection with resistant strains leads to prolonged hospital stay and increased risk of death. Here, we develop a new model of the evolution of antibiotic resistance in a commensal bacterial population adapting to a heterogeneous host population composed of untreated and treated hosts, and structured in different host classes with different antibiotic use. Examples of host classes include age groups and geographic locations. Explicitly modelling the antibiotic treatment reveals that the emergence of a resistant strain is favoured by more frequent but shorter antibiotic courses, and by higher transmission rates. In addition, in a structured host population, localized transmission in host classes promotes both local adaptation of the bacterial population and the global maintenance of coexistence between sensitive and resistant strains. When transmission rates are heterogeneous across host classes, resistant strains evolve more readily in core groups of transmission. These findings have implications for the better management of antibiotic resistance: reducing the rate at which individuals receive antibiotics is more effective to reduce resistance than reducing the duration of treatment. Reducing the rate of treatment in a targeted class of the host population allows greater reduction in resistance, but determining which class to target is difficult in practice.

CA-MRSA and HA-MRSA coexist in community and hospital settings in Uganda

Background

Methicillin resistant Staphylococcus aureus (MRSA) strains were once confined to hospitals however, in the last 20 years MRSA infections have emerged in the community in people with no prior exposure to hospitals. Strains causing such infections were novel and referred to as community-associated MRSA (CA-MRSA). The aim of this study was to determine the MRSA carriage rate in children in eastern Uganda, and to investigate coexistence between CA-MRSA and hospital-associated (HA-MRSA).

Methods

Between February and October 2011, nasopharyngeal samples (one per child) from 742 healthy children under 5 years in rural eastern Uganda were processed for isolation of MRSA, which was identified based on inhibition zone diameter of ≤19 mm on 30 μg cefoxitin disk. SCCmec and spa typing were performed for MRSA isolates.

Results

A total of 140 S. aureus isolates (18.9%, 140/742) were recovered from the children of which 5.7% (42/742) were MRSA. Almost all (95.2%, 40/42) MRSA isolates were multidrug resistant (MDR). The most prevalent SCCmec elements were types IV (40.5%, 17/42) and I (38.1%, 16/42). The overall frequency of SCCmec types IV and V combined, hence CA-MRSA, was 50% (21/42). Likewise, the overall frequency of SCCmec types I, II and III combined, hence HA-MRSA, was 50% (21/42). Spa types t002, t037, t064, t4353 and t12939 were detected and the most frequent were t064 (19%, 8/42) and t037 (12%, 5/42).

Conclusion

The MRSA carriage rate in children in eastern Uganda is high (5.7%) and comparable to estimates for Mulago Hospital in Kampala city. Importantly, HA-MRSA (mainly of spa type t037) and CA-MRSA (mainly of spa type t064) coexist in children in the community in eastern Uganda, and due to high proportion of MDR detected, outpatient treatment of MRSA infection in eastern Uganda might be difficult.

Host contact dynamics shapes richness and dominance of pathogen strains

The interaction among multiple microbial strains affects the spread of infectious diseases and the efficacy of interventions. Genomic tools have made it increasingly easy to observe pathogenic strains diversity, but the best interpretation of such diversity has remained difficult because of relationships with host and environmental factors. Here, we focus on host-to-host contact behavior and study how it changes populations of pathogens in a minimal model of multi-strain interaction. We simulated a population of identical strains competing by mutual exclusion and spreading on a dynamical network of hosts according to a stochastic susceptible-infectious-susceptible model. We computed ecological indicators of diversity and dominance in strain populations for a collection of networks illustrating various properties found in real-world examples. Heterogeneities in the number of contacts among hosts were found to reduce diversity and increase dominance by making the repartition of strains among infected hosts more uneven, while strong community structure among hosts increased strain diversity. We found that the introduction of strains associated with hosts entering and leaving the system led to the highest pathogenic richness at intermediate turnover levels. These results were finally illustrated using the spread of Staphylococcus aureus in a long-term health-care facility where close proximity interactions and strain carriage were collected simultaneously. We found that network structural and temporal properties could account for a large part of the variability observed in strain diversity. These results show how stochasticity and network structure affect the population ecology of pathogens and warn against interpreting observations as unambiguous evidence of epidemiological differences between strains.

On the evolutionary ecology of multidrug resistance in bacteria

Resistance against different antibiotics appears on the same bacterial strains more often than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics and/or bacterial species, whereas the trend is pervasive. Here, we consider the question in terms of strain ecology: explaining why resistance to different antibiotics is often seen on the same strain requires an understanding of the competition between strains with different resistance profiles. This work builds on models originally proposed to explain another aspect of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance between these sub-populations, thus creating niches for sensitivity and resistance. We then generalise this unified underlying model to multidrug resistance and show that models with this structure predict high levels of association between resistance to different drugs and high multidrug resistance frequencies. We test predictions from this model in six bacterial datasets and find them to be qualitatively consistent with observed trends. The higher than expected frequencies of multidrug resistance are often interpreted as evidence that these strains are out-competing strains with lower resistance multiplicity. Our work provides an alternative explanation that is compatible with long-term stability in resistance frequencies.

Population-level mathematical modeling of antimicrobial resistance: a systematic review

BACKGROUND

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006-2016) to gauge the state of research and identify gaps warranting further work.

METHODS

We performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.

RESULTS

We identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.

CONCLUSIONS

The AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

Evolutionary epidemiology models to predict the dynamics of antibiotic resistance

The evolution of resistance to antibiotics is a major public health problem and an example of rapid adaptation under natural selection by antibiotics. The dynamics of antibiotic resistance within and between hosts can be understood in the light of mathematical models that describe the epidemiology and evolution of the bacterial population. "Between-host" models describe the spread of resistance in the host community, and in more specific settings such as hospitalized hosts (treated by antibiotics at a high rate), or farm animals. These models make predictions on the best strategies to limit the spread of resistance, such as reducing transmission or adapting the prescription of several antibiotics. Models can be fitted to epidemiological data in the context of intensive care units or hospitals to predict the impact of interventions on resistance. It has proven harder to explain the dynamics of resistance in the community at large, in particular because models often do not reproduce the observed coexistence of drug-sensitive and drug-resistant strains. "Within-host" models describe the evolution of resistance within the treated host. They show that the risk of resistance emergence is maximal at an intermediate antibiotic dose, and some models successfully explain experimental data. New models that include the complex host population structure, the interaction between resistance-determining loci and other loci, or integrating the within- and between-host levels will allow better interpretation of epidemiological and genomic data from common pathogens and better prediction of the evolution of resistance.

Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) is a continued threat to human health in both community and healthcare settings. In hospitals, control efforts would benefit from accurate estimation of asymptomatic colonization and infection importation rates from the community. However, developing such estimates remains challenging due to limited observation of colonization and complicated transmission dynamics within hospitals and the community. Here, we develop an inference framework that can estimate these key quantities by combining statistical filtering techniques, an agent-based model, and real-world patient-to-patient contact networks, and use this framework to infer nosocomial transmission and infection importation over an outbreak spanning 6 years in 66 Swedish hospitals. In particular, we identify a small number of patients with disproportionately high risk of colonization. In retrospective control experiments, interventions targeted to these individuals yield a substantial improvement over heuristic strategies informed by number of contacts, length of stay and contact tracing.

Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

Potential impact of introducing the pneumococcal conjugate vaccine into national immunisation programmes: an economic-epidemiological analysis using data from India

Pneumococcal pneumonia causes an estimated 105 000 child deaths in India annually. The planned introduction of the serotype-based pneumococcal conjugate vaccine (PCV) is expected to avert child deaths, but the high cost of PCV relative to current vaccines provided under the Universal Immunization Programme has been a concern. Cost-effectiveness studies from high-income countries are not readily comparable because of differences in the distribution of prevalent serotypes, population and health systems. We extended IndiaSim, our agent-based simulation model representative of the Indian population and health system, to model the dynamics of Streptococcus pneumoniae. This enabled us to evaluate serotype and overall disease dynamics in the context of the local population and health system, an aspect that is missing in prospective evaluations of the vaccine. We estimate that PCV13 introduction would cost approximately US$240 million and avert US$48.7 million in out-of-pocket expenditures and 34 800 (95% CI 29 600 to 40 800) deaths annually assuming coverage levels and distribution similar to DPT (diphtheria, pertussis and tetanus) vaccination (~77%). Introducing the vaccine protects the population, especially the poorest wealth quintile, from potentially catastrophic expenditure. The net-present value of predicted money-metric value of insurance for 20 years of vaccination is US$160 000 (95% CI US$151 000 to US$168 000) per 100 000 under-fives, and almost half of this protection is for the bottom wealth quintile (US$78 000; 95% CI 70 800 to 84 400). Extending vaccination to 90% coverage averts additional lives and provides additional financial risk protection. Our estimates are sensitive to immunity parameters in our model; however, our assumptions are conservative, and if willingness to pay per years of life lost averted is US$228 or greater, then introducing the vaccine is more cost-effective than our baseline (no vaccination) in more than 95% of simulations.

Host population structure and treatment frequency maintain balancing selection on drug resistance

It is a truism that antimicrobial drugs select for resistance, but explaining pathogen- and population-specific variation in patterns of resistance remains an open problem. Like other common commensals, Streptococcus pneumoniae has demonstrated persistent coexistence of drug-sensitive and drug-resistant strains. Theoretically, this outcome is unlikely. We modelled the dynamics of competing strains of S. pneumoniae to investigate the impact of transmission dynamics and treatment-induced selective pressures on the probability of stable coexistence. We find that the outcome of competition is extremely sensitive to structure in the host population, although coexistence can arise from age-assortative transmission models with age-varying rates of antibiotic use. Moreover, we find that the selective pressure from antibiotics arises not so much from the rate of antibiotic use per se but from the frequency of treatment: frequent antibiotic therapy disproportionately impacts the fitness of sensitive strains. This same phenomenon explains why serotypes with longer durations of carriage tend to be more resistant. These dynamics may apply to other potentially pathogenic, microbial commensals and highlight how population structure, which is often omitted from models, can have a large impact.

An evolutionary model to predict the frequency of antibiotic resistance under seasonal antibiotic use, and an application to Streptococcus pneumoniae

The frequency of resistance to antibiotics in Streptococcus pneumoniae has been stable over recent decades. For example, penicillin non-susceptibility in Europe has fluctuated between 12% and 16% without any major time trend. In spite of long-term stability, resistance fluctuates over short time scales, presumably in part due to seasonal fluctuations in antibiotic prescriptions. Here, we develop a model that describes the evolution of antibiotic resistance under selection by multiple antibiotics prescribed at seasonally changing rates. This model was inspired by, and fitted to, published data on monthly antibiotics prescriptions and frequency of resistance in two communities in Israel over 5 years. Seasonal fluctuations in antibiotic usage translate into small fluctuations of the frequency of resistance around the average value. We describe these dynamics using a perturbation approach that encapsulates all ecological and evolutionary forces into a generic model, whose parameters quantify a force stabilizing the frequency of resistance around the equilibrium and the sensitivity of the population to antibiotic selection. Fitting the model to the data revealed a strong stabilizing force, typically two to five times stronger than direct selection due to antibiotics. The strong stabilizing force explains that resistance fluctuates in phase with usage, as antibiotic selection alone would result in resistance fluctuating behind usage with a lag of three months when antibiotic use is seasonal. While most antibiotics selected for increased resistance, intriguingly, cephalosporins selected for decreased resistance to penicillins and macrolides, an effect consistent in the two communities. One extra monthly prescription of cephalosporins per 1000 children decreased the frequency of penicillin-resistant strains by 1.7%. This model emerges under minimal assumptions, quantifies the forces acting on resistance and explains up to 43% of the temporal variation in resistance.

Trends in the Genetic Background of Methicillin-Resistant Staphylococcus Aureus Clinical Isolates in a South African Hospital: An Institutional-Based Observational Study

Background:

This study sought to understand the epidemio-ecological dynamics of MRSA isolates associated with a South African hospital over a period spanning year 2007-8 (a previous study reported in 2009) and year 2010-11 (this study).

Methods:

One hundred and ninety three isolates were characterised by molecular fingerprinting methods including pulsed field gel electrophoresis (PFGE), spa typing, agr-typing, SCCmec-typing, and multilocus sequence typing (MLST). The Vitek-2 automated antibiogram of representative isolates was also performed.

Results:

Our data shows that the distribution of MRSA strains among the different clinical conditions was rarely dependent on the genetic backbone or genotype. Compared to the previous survey in 2009, CA-MRSA isolates increased by 31% while HA-MRSA isolates decreased by 17%. An increase in genetic diversity was also revealed including the detection of three pandemic clonal complexes (spa type t012-ST36/CC30, spa type t037-ST239/CC8, spa type t891-ST22/CC22 and spa type t1257-ST612/CC8). Majority of the genotypes were classified as Spa Cluster B-SCCmec I-agr I 19.2%; (37/193) Spa Cluster A-SCCmercury-agr I 14.5%; (28/193)

Conclusion:

This study reveals that increased diversity in MRSA genetic background was associated with resistance to frontline antibiotics. Also, an increase was recorded in the CA-MRSA/HA-MRSA ratio within a 5-year period despite the continuous dominance of the HA-MRSA genotype.

Antimicrobial Resistance and Molecular Characteristics of Nasal Staphylococcus aureus Isolates From Newly Admitted Inpatients

Staphylococcus aureus, or methicillin-resistant S. aureus (MRSA), is a significant pathogen in both nosocomial and community infections. Community-associated MRSA (CA-MRSA) strains tend to be multi-drug resistant and to invade hospital settings. This study aimed to assess the antimicrobial resistance and molecular characteristicsof nasal S. aureus among newlyadmitted inpatients.In the present study, 66 S. aureus isolates, including 10 healthcare-associated MRSA (HA-MRSA), 8 CA-MRSA, and 48 methicillin-sensitive S. aureus (MSSA) strains, were found in the nasal cavities of 62 patients by screening 292 newlyadmitted patients. Antimicrobial resistance and molecular characteristics of these isolates, including spa-type, sequence type (ST) and SCCmec type, were investigated. All isolates were sensitive to linezolid, teicoplanin, and quinupristin/dalfopristin, but high levels of resistance to penicillin and erythromycin were detected. According to D-test and erm gene detection results, the cMLS_B and iMLS_B phenotypes were detected in 24 and 16 isolates, respectively. All 10 HA-MRSA strains displayed the cMLS_B phenotypemediated by ermA or ermA/ermC, while the cMLS_B CA-MRSA and MSSA strains carried the ermB gene. Molecular characterization revealedall 10 HA-MRSA strains were derived from the ST239-SCCmec III clone, and four out of eight CA-MRSA strains were t437-ST59-SCCmec V. The results suggest that patients play an indispensable role in transmitting epidemic CA-MRSA and HA-MRSA strains.

Protective Efficacy and Mechanism of Passive Immunization with Polyclonal Antibodies in a Sepsis Model of Staphylococcus aureus Infection

Staphylococcus aureus (S. aureus) is an opportunistic bacterial pathogen responsible for a diverse spectrum of human diseases, resulting in considerable yearly mortality rates. Due to its rapid acquisition of antibiotic resistance, it becomes increasingly difficult to cure S. aureus infections with conventional antibiotics. Immunotherapy represents a promising alternative strategy to prevent and/or treat the infection. In the present study, passive immunization with polyclonal antibodies targeting three possible S. aureus antigens, Hla, SEB and MntC (termed "SAvac-pcAb") after challenge with lethal dose of S. aureus resulted in reduced bacterial loads, inflammatory cell infiltration and decreased pathology, and was able to provide nearly complete protection in a murine sepsis model. In vitro studies confirmed the direct interaction of SAvac-pcAb with S. aureus bacteria. Additional studies validated that SAvac-pcAb contained both opsonic and neutralizing antibodies that contributed to its protective efficacy. The former mediated opsonophagocytosis in a neutrophil-dependent manner, while the later inhibited the biological functions of Hla and SEB, two major virulence factors secreted by S. aureus. Critically, we demonstrated that SAvac-pcAb was cross-reactive with different clinical strains of S. aureus. These results confirmed the efficacy for treatment of S. aureus infection by passive immunization as an important therapeutic option.

How direct competition shapes coexistence and vaccine effects in multi-strain pathogen systems

We describe an integrated modeling framework for understanding strain coexistence in polymorphic pathogen systems. Previous studies have debated the utility of neutral formulations and focused on cross-immunity between strains as a major stabilizing mechanism. Here we convey that direct competition for colonization mediates stable coexistence only when competitive abilities amongst pathogen clones satisfy certain pairwise asymmetries. We illustrate our ideas with nested SIS models of single and dual colonization, applied to polymorphic pneumococcal bacteria. By fitting the models to cross-sectional prevalence data from Portugal (before and after the introduction of a seven-valent pneumococcal conjugate vaccine), we are able to not only statistically compare neutral and non-neutral epidemiological formulations, but also estimate vaccine efficacy, transmission and competition parameters simultaneously. Our study highlights that the response of polymorphic pathogen populations to interventions holds crucial information about strain interactions, which can be extracted by suitable nested modeling.

Impact of mupirocin resistance on the transmission and control of healthcare-associated MRSA

Objectives

The objectives of this study were to estimate the relative transmissibility of mupirocin-resistant (MupR) and mupirocin-susceptible (MupS) MRSA strains and evaluate the long-term impact of MupR on MRSA control policies.

Methods

Parameters describing MupR and MupS strains were estimated using Markov chain Monte Carlo methods applied to data from two London teaching hospitals. These estimates parameterized a model used to evaluate the long-term impact of MupR on three mupirocin usage policies: ‘clinical cases’, ‘screen and treat’ and ‘universal’. Strategies were assessed in terms of colonized and infected patient days and scenario and sensitivity analyses were performed.

Results

The transmission probability of a MupS strain was 2.16 (95% CI 1.38–2.94) times that of a MupR strain in the absence of mupirocin usage. The total prevalence of MupR in colonized and infected MRSA patients after 5 years of simulation was 9.1% (95% CI 8.7%–9.6%) with the ‘screen and treat’ mupirocin policy, increasing to 21.3% (95% CI 20.9%–21.7%) with ‘universal’ mupirocin use. The prevalence of MupR increased in 50%–75% of simulations with ‘universal’ usage and >10% of simulations with ‘screen and treat’ usage in scenarios where MupS had a higher transmission probability than MupR.

Conclusions

Our results provide evidence from a clinical setting of a fitness cost associated with MupR in MRSA strains. This provides a plausible explanation for the low levels of mupirocin resistance seen following ‘screen and treat’ mupirocin usage. From our simulations, even under conservative estimates of relative transmissibility, we see long-term increases in the prevalence of MupR given ‘universal’ use.

Turning the tide or riding the waves? Impacts of antibiotic stewardship and infection control on MRSA strain dynamics in a Scottish region over 16 years: non-linear time series analysis

OBJECTIVES

To explore temporal associations between planned antibiotic stewardship and infection control interventions and the molecular epidemiology of methicillin-resistant Staphylococcus aureus (MRSA).

DESIGN

Retrospective ecological study and time-series analysis integrating typing data from the Scottish MRSA reference laboratory.

SETTING

Regional hospital and primary care in a Scottish Health Board.

PARTICIPANTS

General adult (N=1,051,993) or intensive care (18,235) admissions and primary care registrations (460,000 inhabitants) between January 1997 and December 2012.

INTERVENTIONS

Hand-hygiene campaign; MRSA admission screening; antibiotic stewardship limiting use of macrolides and '4Cs' (cephalosporins, coamoxiclav, clindamycin and fluoroquinolones).

OUTCOME MEASURES

Prevalence density of MRSA clonal complexes CC22, CC30 and CC5/Other in hospital (isolates/1000 occupied bed days, OBDs) and community (isolates/10,000 inhabitant-days).

RESULTS

67% of all clinical MRSA isolates (10,707/15,947) were typed. Regional MRSA population structure was dominated by hospital epidemic strains CC30, CC22 and CC45. Following declines in overall MRSA prevalence density, CC5 and other strains of community origin became increasingly important. Reductions in use of '4Cs' and macrolides anticipated declines in sublineages with higher levels of associated resistances. In multivariate time-series models (R(2)=0.63-0.94) introduction of the hand-hygiene campaign, reductions in mean length of stay (when >4 days) and bed occupancy (when >74 to 78%) predicted declines in CC22 and CC30, but not CC5/other strains. Lower importation pressures, expanded MRSA admission screening, and reductions in macrolide and third generation cephalosporin use (thresholds for association: 135-141, and 48-81 defined daily doses/1000 OBDs, respectively) were followed by declines in all clonal complexes. Strain-specific associations with fluoroquinolones and clindamycin reflected resistance phenotypes of clonal complexes.

CONCLUSIONS

Infection control measures and changes in population antibiotic use were important predictors of MRSA strain dynamics in our region. Strategies to control MRSA should consider thresholds for effects and strain-specific impacts.

Community-associated methicillin-resistant Staphylococcus aureus in non-outbreak skin infections

The aim of this study was to determine the prevalence of Staphylococcus aureus and risk factors for the acquisition of MRSA (Methicillin Resistant Staphylococcus aureus) as the main cause of skin and soft tissue infections. S. aureus were characterized for the presence of PVL, TSST-1 and mecA genes. SCCmec typing was carried out in mecA positive strains and PFGE was performed only in these strains. During the study period, 127 outpatients attending a dermatology clinical the Botucatu Medical School, a regional tertiary hospital in Botucatu, Sao Paulo, Brazil, were diagnosed with active skin infections. A total 66 (56.9%) S. aureus strains were isolated. The methicillin resistance gene mecA was detected in seven (10.6%) S. aureus strains. The SCCmec types detected in the seven mecA-positive S. aureus strains were type Ia in one, type II in three, and type IV in three. The PVL gene was detected in 10 (15.1%) in sensitive strains. Pulsed field gel electrophoresis revealed non-clonal diversity among the isolates. The risk factors associated with MRSA acquisition in this study were previous ciprofloxacin use and working in a healthcare environment. The risk factors indicate plausible routes of CA-MRSA transmission among the subjects studied.

Transition metal diamine complexes with antimicrobial activity against Staphylococcus aureus and methicillin-resistant S. aureus (MRSA)

Curves showing two different trials of killing a MRSA strain with [Cp*IrCl(cis-1,2-diaminocyclohexane)]Cl.

Synthesis and pharmacological evaluations of 4-hydroxycoumarin derivatives as a new class of anti-Staphylococcus aureus agents

OBJECTIVES

Due to the increasing prevalence of drug-resistant Staphylococcus aureus infection, we develop novel 4-hydroxycoumarin derivatives as antimicrobials.

METHODS

The antibacterial activity of 4-hydroxycoumarin derivatives against drug-susceptive S. aureus (ATCC 29213) and methicillin-resistant S. aureus (MRSA) were evaluated using minimal inhibitory concentration (MIC) assay; the activity of favourable compound was further observed using bacterial growth curves assay and in the MRSA infection mice.

KEY FINDINGS

Compared with dihydropyran derivatives, compound 1 as one of biscoumarins showed most potent activity with MIC values of 4-8 μg/ml and apparently inhibited the growth rate of S. aureus ATCC 29213 and USA300 strain in concentrations of both 16 and 32 mg/ml. In the mice infected with MRSA USA300, administration of 5 mg/kg compound 1 improved the animal survival rate to 66.7%, and improved the pathological change in lung tissue compared with the infection model animals. No significant cytotoxicity of compound 1 was observed on the umbilical vein endothelial cells (HUVECs) under the concentration of 800 μg/ml.

CONCLUSION

Compared with the dihydropyran derivatives, biscoumarins exhibited more promising activity against both drug-sensitive and drug-resistant S. aureus, and it is efficacious in treating MRSA infections in mouse models with a favourable safety in human cells.

New patterns of methicillin-resistant Staphylococcus aureus (MRSA) clones, community-associated MRSA genotypes behave like healthcare-associated MRSA genotypes within hospitals, Argentina

Methicillin-resistant Staphylococcus aureus (MRSA) burden is increasing worldwide in hospitals [healthcare-associated (HA)-MRSA] and in communities [community-associated (CA)-MRSA]. However, the impact of CA-MRSA within hospitals remains limited, particularly in Latin America. A countrywide representative survey of S. aureus infections was performed in Argentina by analyzing 591 clinical isolates from 66 hospitals in a prospective cross-sectional, multicenter study (Nov-2009). This work involved healthcare-onset infections-(HAHO, >48 hospitalization hours) and community-onset (CO) infections [including both, infections (HACO) in patients with healthcare-associated risk-factors (HRFs) and infections (CACO) in those without HRFs]. MRSA strains were genetically typed as CA-MRSA and HA-MRSA genotypes (CA-MRSAG and HA-MRSAG) by SCCmec- and spa-typing, PFGE, MLST and virulence genes profile by PCR. Considering all isolates, 63% were from CO-infections and 55% were MRSA [39% CA-MRSAG and 16% HA-MRSAG]. A significantly higher MRSA proportion among CO- than HAHO-S. aureus infections was detected (58% vs 49%); mainly in children (62% vs 43%). The CA-MRSAG/HA-MRSAG have accounted for 16%/33% of HAHO-, 39%/13% of HACO- and 60.5%/0% of CACO-infections. Regarding the epidemiological associations identified in multivariate models for patients with healthcare-onset CA-MRSAG infections, CA-MRSAG behave like HA-MRSAG within hospitals but children were the highest risk group for healthcare-onset CA-MRSAG infections. Most CA-MRSAG belonged to two major clones: PFGE-type N-ST30-SCCmecIVc-t019-PVL(+) and PFGE-type I-ST5-IV-SCCmecIVa-t311-PVL(+) (45% each). The ST5-IV-PVL(+)/ST30-IV-PVL(+) clones have caused 31%/33% of all infections, 20%/4% of HAHO-, 43%/23% of HACO- and 35%/60% of CACO- infections, with significant differences by age groups (children/adults) and geographical regions. Importantly, an isolate belonging to USA300-0114-(ST8-SCCmecIVa-spat008-PVL(+)-ACME(+)) was detected for the first time in Argentina. Most of HA-MRSAG (66%) were related to the Cordobes/Chilean clone-(PFGE-type A-ST5-SCCmecI-t149) causing 18% of all infections (47% of HAHO- and 13% of HACO-infections). Results strongly suggest that the CA-MRSA clone ST5-IV-PVL(+) has begun to spread within hospitals, replacing the traditional Cordobes/Chilean-HA-MRSA clone ST5-I-PVL(-), mainly in children. Importantly, a growing MRSA reservoir in the community was associated with spreading of two CA-MRSA clones: ST5-IV-PVL(+), mainly in children with HRFs, and ST30-IV-PVL(+) in adults without HRFs. This is the first nationwide study in Argentina providing information about the molecular and clinical epidemiology of CA-MRSA, particularly within hospitals, which is essential for designing effective control measures in this country and worldwide.

Continued emergence of USA300 methicillin-resistant Staphylococcus aureus in the United States: results from a nationwide surveillance study

BACKGROUND

The epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) is changing, with USA300 emerging first in community and then in healthcare settings. We performed nationwide surveillance to assess recent trends in the molecular epidemiology of MRSA.

METHODS

One hundred consecutive unique clinically significant S. aureus isolates were recovered from patients at each of 43 US centers between July 1, 2011, and December 31, 2011. Susceptibility testing, pulsed-field gel electrophoresis (PFGE), staphylococcal protein A gene (spa) and staphylococcal cassette chromosome mec typing, and Panton-Valentine leukocidin detection were performed on all MRSA isolates.

RESULTS

Of 4,131 isolates collected, 2,093 (51%) were MRSA. Specimen sources of MRSA isolates included wound or abscess (54%), blood (24%), lower respiratory tract (11%), and other sterile site (10%). Thirty percent were isolated more than 48 hours after hospital admission (ie, were associated with nosocomial acquisition of infection). USA300 was the most common PFGE type (1,269 isolates; 61%), overall and in all regions, followed by USA100 (368 isolates; 18%). Among 173 spa types found, the most common were t008 (51%) and t002 (18%); no other spa type accounted for more than 2% of isolates. One strain type (USA300/t008/IV) constituted almost half of all MRSA isolates (1,005 isolates; 48%) and was the most common at all body sites, causing 37% of MRSA bloodstream infections (BSIs) and 38% of nosocomial MRSA infections. Multidrug-resistant phenotypes were found among 34 USA300 isolates (3%) from 18 states.

CONCLUSIONS

The USA300 PFGE type continues to advance nationwide. A single strain type (USA300/t008/IV) predominates in all regions and infection sites and is now more common than USA100 as a cause of MRSA BSI and nosocomial infections. Although most USA300 retain typical susceptibility profiles, multidrug-resistant phenotypes are emerging.

Synthesis, antibacterial activities, and theoretical studies of dicoumarols

In this work, we report the synthesis, evaluation of antibacterial activity and theoretical study of dicoumarols including DC, 2-PyDC, 3-PyDC and 4-PyDC.

A data-driven mathematical model of CA-MRSA transmission among age groups: evaluating the effect of control interventions

Community associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has become a major cause of skin and soft tissue infections (SSTIs) in the US. We developed an age-structured compartmental model to study the spread of CA-MRSA at the population level and assess the effect of control intervention strategies. We used Monte-Carlo Markov Chain (MCMC) techniques to parameterize our model using monthly time series data on SSTIs incidence in children (≤ 19 years) during January 2004 -December 2006 in Maricopa County, Arizona. Our model-based forecast for the period January 2007-December 2008 also provided a good fit to data. We also carried out an uncertainty and sensitivity analysis on the control reproduction number, Rc which we estimated at 1.3 (95% CI [1.2,1.4]) based on the model fit to data. Using our calibrated model, we evaluated the effect of typical intervention strategies namely reducing the contact rate of infected individuals owing to awareness of infection and decolonization strategies targeting symptomatic infected individuals on both [Formula: see text] and the long-term disease dynamics. We also evaluated the impact of hypothetical decolonization strategies targeting asymptomatic colonized individuals. We found that strategies focused on infected individuals were not capable of achieving disease control when implemented alone or in combination. In contrast, our results suggest that decolonization strategies targeting the pediatric population colonized with CA-MRSA have the potential of achieving disease elimination.