Bacterial resistance to penicillin G by decreased affinity of penicillin-binding proteins: a mathematical model

A systematic review to identify research gaps in studies modeling MenB vaccinations against Neisseria infections

The genus Neisseria includes two major human pathogens: N. meningitidis causing bacterial meningitis/septicemia and N. gonorrhoeae causing gonorrhoea. Mathematical models have been used to simulate their transmission and control strategies, and the recent observation of a meningococcal B (MenB) vaccine being partially effective against gonorrhoea has led to an increased modeling interest. Here we conducted a systematic review of the literature, focusing on studies that model vaccination strategies with MenB vaccines against Neisseria incidence and antimicrobial resistance. Using journal, preprint, and grey literature repositories, we identified 52 studies that we reviewed for validity, model approaches and assumptions. Most studies showed a good quality of evidence, and the variety of approaches along with their different modeling angles, was assuring especially for gonorrhoea studies. We identified options for future research, including the combination of both meningococcal and gonococcal infections in studies to have better estimates for vaccine benefits, and the spill over of gonorrhoea infections from the heterosexual to the MSM community and vice versa. Cost-effectiveness studies looking at at-risk and the wider populations can then be used to inform vaccine policies on gonorrhoea, as they have for meningococcal disease.

Affinity of cefditoren for penicillin-binding proteins in bacteria and its relationship with antibiotic sensitivity

Penicillin-binding proteins (PBPs) are the targets of β-lactam antibiotics; however, changes in the affinity of PBPs for beta-lactam antibiotics often affect the susceptibility of bacteria to antibiotics. The purpose of this study was to elucidate the mechanism by which cefditoren, an oral third-generation cephalosporin, binds PBPs. The minimal inhibitory concentration (MIC), bactericidal curves, and inhibition zone comparisons were assessed to evaluate the antibacterial activity of cefditoren. PBP1A and PBP2X proteins from Streptococcus pneumoniae were purified, and their ability to bind to cefditoren was investigated via microscale thermophoresis. The Kd of cefditoren toward PBP1A was 0.005 ± 0.004 µM, which was lower than those of other cephalosporins (cefcapene, cefixime and cefdinir). In contrast, the Kd of cefditoren toward PBP2X of S. pneumoniae was 9.70 ± 8.24 µM, which was lower than that of cefixime but higher than those of cefcapene and cefdinir. Additionally, the biotinylated ampicillin (BIO-AMP) method was employed to evaluate the affinity of cefditoren toward PBPs of Haemophilus influenzae, and the results demonstrated that cefditoren and PBP3A/B had the lowest IC50 values (0.060 ± 0.002 µM). These findings indicate that cefditoren has a strong affinity for PBP1A of H. influenzae. Cefditoren has a high affinity toward the PBP1As of S. pneumoniae and PBP1A and PBP3A/B of H. influenzae, which may contribute to the effective antibacterial effects of cefditoren against clinical strains and its low propensity for inducing resistance. The data presented in this article help elucidate the mechanism by which cefditoren, an oral third-generation cephalosporin, binds to PBPs and provide theoretical support for the wider use of cefditoren as an antibiotic therapy.

Application of MIDD to accelerate the development of anti-infectives: Current status and future perspectives

This review examines the role of model-informed drug development (MIDD) in advancing antibacterial and antiviral drug development, with an emphasis on the inclusion of host system dynamics into modeling efforts. Amidst the growing challenges of multidrug resistance and diminishing market returns, innovative methodologies are crucial for continuous drug discovery and development. The MIDD approach, with its robust capacity to integrate diverse data types, offers a promising solution. In particular, the utilization of appropriate modeling and simulation techniques for better characterization and early assessment of drug resistance are discussed. The evolution of MIDD practices across different infectious disease fields is also summarized, and compared to advancements achieved in oncology. Moving forward, the application of MIDD should expand into host system dynamics as these considerations are critical for the development of "live drugs" (e.g. chimeric antigen receptor T cells or bacteriophages) to address issues like antibiotic resistance or latent viral infections.

Increased Activity of β-Lactam Antibiotics in Combination with Carvacrol against MRSA Bacteremia and Catheter-Associated Biofilm Infections

β-Lactam antibiotics are the mainstay for the treatment of staphylococcal infections, but their utility is greatly limited by the emergence and rapid dissemination of methicillin-resistant Staphylococcus aureus (MRSA). Herein, we evaluated the ability of the plant-derived monoterpene carvacrol to act as an antibiotic adjuvant, revitalizing the anti-MRSA activity of β-lactam antibiotics. Increased susceptibility of MRSA to β-lactam antibiotics and significant synergistic activities were observed with carvacrol-based combinations. Carvacrol significantly inhibited MRSA biofilms and reduced the production of exopolysaccharide, polysaccharide intercellular adhesin, and extracellular DNA and showed synergistic biofilm inhibition in combination with β-lactams. Transcriptome analysis revealed profound downregulation in the expression of genes involved in two-component systems and S. aureus infection. Mechanistic studies indicate that carvacrol inhibits the expression of staphylococcal accessory regulator sarA and interferes with SarA-mecA promoter binding that decreases mecA-mediated β-lactam resistance. Consistently, the in vivo experiment also supported that carvacrol restored MRSA sensitivity to β-lactam antibiotic treatments in both murine models of bacteremia and biofilm-associated infection. Our results indicated that carvacrol has a potential role as a combinatorial partner with β-lactam antibiotics to address MRSA infections.

Cationic antimicrobial peptides: alternatives and/or adjuvants to antibiotics active against methicillin-resistant Staphylococcus aureus and multidrug-resistant Pseudomonas aeruginosa

BACKGROUND

Methicillin-resistant Staphylococcus aureus and multidrug-resistant Pseudomonas aeruginosa are becoming difficult to treat with antibiotics whereas Cationic Antimicrobial Peptides (CAMPs) represent promising alternatives. The effects of four CAMPs (LL-37: human cathelicidin, CAMA: cecropin(1-7)-melittin A(2-9) amide, magainin-II and nisin) were investigated against clinical and laboratory S. aureus (n = 10) and P. aeruginosa (n = 11) isolates either susceptible or resistant to antibiotics. Minimal Inhibitory Concentrations (MICs), Minimal Bactericidal Concentrations (MBCs), and bacterial survival rates (2 h post-treatment) were determined by microbroth dilution. The antipseudomonal effects of the antibiotics colistin or imipenem combined to LL-37 or CAMA were also studied. The toxicity of CAMPs used alone and in combination with antibiotics was evaluated on two human lung epithelial cell lines by determining the quantity of released cytoplasmic lactate dehydrogenase (LDH). Attempts to induce bacterial resistance to gentamicin, LL-37 or CAMA were also performed.

RESULTS

The results revealed the rapid antibacterial effect of LL-37 and CAMA against both antibiotic susceptible and resistant strains with almost a total reduction in bacterial count 2 h post-treatment. Magainin-II and nisin were less active against tested strains. When antibiotics were combined with LL-37 or CAMA, MICs of colistin decreased up to eight-fold and MICs of imipenem decreased up to four-fold. Cytotoxicity assays revealed non-significant LDH-release suggesting no cell damage in all experiments. Induction of bacterial resistance to LL-37 was transient, tardive and much lower than that to gentamicin and induction of resistance to CAMA was not observed.

CONCLUSION

This study showed the potent and rapid antibacterial activity of CAMPs on both laboratory and clinical isolates of S. aureus and P. aeruginosa either susceptible or resistant to antibiotics. Most importantly, CAMPs synergized the efficacy of antibiotics, had non toxic effects on human cells and were associated with transient and low levels of induced resistance.

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.

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.

Genomic analysis of the original Elberg Brucella melitensis Rev.1 vaccine strain reveals insights into virulence attenuation

The live attenuated Brucella melitensis Rev.1 Elberg-originated vaccine strain has been widely used to control brucellosis in small ruminants. However, despite extensive research, the molecular mechanisms underlying the attenuation of this strain are still unknown. In the current study, we conducted a comprehensive comparative analysis of the whole-genome sequence of Rev.1 against that of the virulent reference strain, B. melitensis 16M. This analysis revealed five regions of insertion and three regions of deletion within the Rev.1 genome, among which, one large region of insertion, comprising 3,951 bp, was detected in the Rev.1 genome. In addition, we found several missense mutations within important virulence-related genes, which may be used to determine the mechanism underlying virulence attenuation. Collectively, our findings provide new insights into the Brucella virulence mechanisms and, therefore, may serve as a basis for the rational design of new Brucella vaccines.

Metal Resistance and Its Association With Antibiotic Resistance

Antibiotic resistance is recognised as a major global threat to public health by the World Health Organization. Currently, several hundred thousand deaths yearly can be attributed to infections with antibiotic-resistant bacteria. The major driver for the development of antibiotic resistance is considered to be the use, misuse and overuse of antibiotics in humans and animals. Nonantibiotic compounds, such as antibacterial biocides and metals, may also contribute to the promotion of antibiotic resistance through co-selection. This may occur when resistance genes to both antibiotics and metals/biocides are co-located together in the same cell (co-resistance), or a single resistance mechanism (e.g. an efflux pump) confers resistance to both antibiotics and biocides/metals (cross-resistance), leading to co-selection of bacterial strains, or mobile genetic elements that they carry. Here, we review antimicrobial metal resistance in the context of the antibiotic resistance problem, discuss co-selection, and highlight critical knowledge gaps in our understanding.

A unified inter-host and in-host model of antibiotic resistance and infection spread in a hospital ward

As the battle continues against hospital-acquired infections and the concurrent rise in antibiotic resistance among many of the major causative pathogens, there is a dire need to conduct controlled experiments, in order to compare proposed control strategies. However, cost, time, and ethical considerations make this evaluation strategy either impractical or impossible to implement with living patients. This paper presents a multi-scale model that offers promise as the basis for a tool to simulate these (and other) controlled experiments. This is a "unified" model in two important ways: (i) It combines inter-host and in-host dynamics into a single model, and (ii) it links two very different modeling approaches - agent-based modeling and differential equations - into a single model. The potential of this model as an instrument to combat antibiotic resistance in hospitals is demonstrated with numerical examples.

Resistance to antibiotics: limit theorems for a stochastic SIS model structured by level of resistance

The rise of bacterial resistance to antibiotics is a major Public Health concern. It is the result of two interacting processes: the selection of resistant bacterial strains under exposure to antibiotics and the dissemination of bacterial strains throughout the population by contact between colonized and uncolonized individuals. To investigate the resulting time evolution of bacterial resistance, Temime et al. (Emerg Infect Dis 9:411-417, 2003) developed a stochastic SIS model, which was structured by the level of resistance of bacterial strains. Here we study the asymptotic properties of this model when the population size is large. To this end, we cast the model within the framework of measure valued processes, using point measures to represent the pattern of bacterial resistance in the compartments of colonized individuals. We first show that the suitably normalized model tends in probability to the solution of a deterministic differential system. Then we prove that the process of fluctuations around this limit tends in law to a Gaussian process in a space of distributions. These results, which generalize those of Kurtz (CBMS-NSF regional conference series in applied mathematics, vol 36. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 1981, chap. 8) on SIR models, support the validity of the deterministic approximation and quantify the rate of convergence.

A modeling framework for the evolution and spread of antibiotic resistance: literature review and model categorization

Antibiotic-resistant infections complicate treatment and increase morbidity and mortality. Mathematical modeling has played an integral role in improving our understanding of antibiotic resistance. In these models, parameter sensitivity is often assessed, while model structure sensitivity is not. To examine the implications of this, we first reviewed the literature on antibiotic-resistance modeling published between 1993 and 2011. We then classified each article's model structure into one or more of 6 categories based on the assumptions made in those articles regarding within-host and population-level competition between antibiotic-sensitive and antibiotic-resistant strains. Each model category has different dynamic implications with respect to how antibiotic use affects resistance prevalence, and therefore each may produce different conclusions about optimal treatment protocols that minimize resistance. Thus, even if all parameter values are correctly estimated, inferences may be incorrect because of the incorrect selection of model structure. Our framework provides insight into model selection.

Contribution of mathematical modeling to the fight against bacterial antibiotic resistance

PURPOSE OF REVIEW

Modeling of antibiotic resistance in pathogenic bacteria responsible for human disease has developed considerably over the last decade. Herein, we summarize the main published studies to illustrate the contribution of models for understanding both within-host and population-based phenomena. We then suggest possible topics for future studies.

RECENT FINDINGS

Model building of bacterial resistance has involved epidemiologists, biologists and modelers with two different objectives. First, modeling has helped largely in identifying and understanding the factors and biological phenomena responsible for the emergence and spread of resistant strains. Second, these models have become important decision support tools for medicine and public health.

SUMMARY

Major improvements of models in the coming years should take into account specific pathogen characteristics (resistance mechanisms, multiple colonization phenomena, cooperation and competition among species) and better description of the contacts associated with transmission risk within populations.

A model of drug resistance with infection by health care workers

Antibiotic resistant organisms (ARO) pose an increasing serious threat in hospitals. One of the most life threatening ARO is methicillin-resistant staphylococcus aureus (MRSA). In this paper, we introduced a new mathematical model which focuses on the evolution of two bacterial strains, drug-resistant and non-drug resistant, residing within the population of patients and health care workers in a hospital. The model predicts that as soon as drug is administered, the average load of the non-resistant bacteria will decrease and eventually (after 6 weeks of the model's simulation) reach a very low level. However, the average load of drug-resistant bacteria will initially decrease, after treatment, but will later bounce back and remain at a high level. This level can be made lower if larger amount of drug is given or if the contact between health care workers and patients is reduced.

Antibiotic dose impact on resistance selection in the community: a mathematical model of beta-lactams and Streptococcus pneumoniae dynamics

Streptococcus pneumoniae is a major pathogen in the community and presents high rates of resistance to the available antibiotics. To prevent antibiotic treatment failure caused by highly resistant bacteria, increasing the prescribed antibiotic dose has recently been suggested. The aim of the present study was to assess the influence of beta-lactam prescribed doses on the emergence of resistance and selection in the community. A mathematical model was constructed by combining S. pneumoniae pharmacodynamic and population-dynamic approaches. The received-dose heterogeneity in the population was specifically modeled. Simulations over a 50-year period were run to test the effects of dose distribution and antibiotic exposure frequency changes on community resistance patterns, as well as the accuracy of the defined daily dose as a predictor of resistance. When the frequency of antibiotic exposure per year was kept constant, dose levels had a strong impact on the levels of resistance after a 50-year simulation. The lowest doses resulted in a high prevalence of nonsusceptible strains (> or =70%) with MICs that were still low (1 mg/liter), whereas high doses resulted in a lower prevalence of nonsusceptible strains (<40%) and higher MICs (2 mg/liter). Furthermore, by keeping the volume of antibiotics constant in the population, different patterns of use (low antibiotic dose and high antibiotic exposure frequency versus high dose and low frequency) could lead to markedly different rates of resistance distribution and prevalence (from 10 to 100%). Our results suggest that pneumococcal resistance patterns in the community are strongly related to the individual beta-lactam doses received: limiting beta-lactam use while increasing the doses could help reduce the prevalence of resistance, although it should select for higher levels of resistance. Surveillance networks are therefore encouraged to collect both daily antibiotic exposure frequencies and individual prescribed doses.

Antibiotic innovation may contribute to slowing the dissemination of multiresistant Streptococcus pneumoniae: the example of ketolides

BACKGROUND

Despite increasingly frequent bacterial resistance to antibiotics, antibacterial innovation is rare. Ketolides constitute one of the very few new antibiotic classes active against Streptococcus pneumoniae developed during the last 25 years. Their mechanism of action resembles that of macrolides, but they are unaffected by common resistance mechanisms. However, cross-resistance to ketolides has been observed in some macrolide-resistant strains. We examined how new antibiotic exposure may affect overall pneumococcal resistance patterns in the population. The aims of this study were to assess the potential dissemination of newly emerged resistances and to control the selection of strains already multiresistant to existing antimicrobials.

METHODOLOGY/PRINCIPAL FINDINGS

We developed an age-structured population model for S. pneumoniae transmission in a human community exposed to heptavalent vaccine, and beta-lactams, macrolides and ketolides. The dynamics of intra-individual selection of resistant strains under antibiotic exposure and interindividual transmission were simulated, with antibiotic-specific resistance mechanisms defining the path to co-resistances and cross-resistances, and parameters concerning the French situation. Results of this simulation study suggest that new antibiotic consumption could markedly slow the diffusion of multiresistant strains. Wider use was associated with slower progression of multiresistance. When ketolides were prescribed to all ages, resistance to them reached 10% after >15 years, while it took >40 years when they were prescribed only to adults. In the scenario according to which new antibiotics totally replaced former antimicrobials, the beta-lactam resistance rate was limited at 70%.

CONCLUSIONS

In a context of widespread vaccination and rational use of antibiotics, innovative antibiotic, prescribed to all age groups, may have an added impact on multiresistant-strain dissemination in the population.

Modeling antibiotic resistance in hospitals: the impact of minimizing treatment duration

Infections caused by antibiotic-resistant pathogens are a global public health problem. Numerous individual- and population-level factors contribute to the emergence and spread of these pathogens. An individual-based model (IBM), formulated as a system of stochastically determined events, was developed to describe the complexities of the transmission dynamics of antibiotic-resistant bacteria. To simplify the interpretation and application of the model's conclusions, a corresponding deterministic model was created, which describes the average behavior of the IBM over a large number of simulations. The integration of these two model systems provides a quantitative analysis of the emergence and spread of antibiotic-resistant bacteria, and demonstrates that early initiation of treatment and minimization of its duration mitigates antibiotic resistance epidemics in hospitals.

The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study

Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. Moreover, modelling articles are, on average, among the most frequently cited third of articles from the journal in which they were published. The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance.

S. pneumoniae transmission according to inclusion in conjugate vaccines: Bayesian analysis of a longitudinal follow-up in schools

BACKGROUND

Recent trends of pneumococcal colonization in the United States, following the introduction of conjugate vaccination, indicate that non-vaccine serotypes tend to replace vaccine serotypes. The eventual extent of this replacement is however unknown and depends on serotype-specific carriage and transmission characteristics.

METHODS

Here, some of these characteristics were estimated for vaccine and non-vaccine serotypes from the follow-up of 4,488 schoolchildren in France in 2000. A Bayesian approach using Markov chain Monte Carlo data augmentation techniques was used for estimation.

RESULTS

Vaccine and non-vaccine serotypes were found to have similar characteristics: the mean duration of carriage was 23 days (95% credible interval (CI): 21, 25 days) for vaccine serotypes and 22 days (95% CI: 20, 24 days) for non-vaccine serotypes; within a school of size 100, the Secondary Attack Rate was 1.1% (95% CI: 1.0%, 1.2%) for both vaccine and non-vaccine serotypes.

CONCLUSION

This study supports that, in 3-6 years old children, no competitive advantage exists for vaccine serotypes compared to non-vaccine serotypes. This is an argument in favour of important serotype replacement. It would be important to validate the result for infants, who are known to be the main reservoir in maintaining transmission. Overall reduction in pathogenicity should also be taken into account in forecasting the future burden of pneumococcal colonization in vaccinated populations.

Reduction of Antibiotic Use in the Community Reduces the Rate of Colonization with Penicillin G--Nonsusceptible Streptococcus pneumoniae

BACKGROUND

There is a lack of evidence documenting the impact of optimized antibiotic use on the rates of colonization with penicillin G-nonsusceptible Streptococcus pneumoniae (PNSP) in children. This study evaluates the effect of community-based intervention strategies on the prevalence of pnsp colonization.

METHODS

A controlled, population-based pharmacoepidemiological trial was conducted from January through May 2000. Three French geographic areas were selected on the basis of demographic similarities. Two intervention strategies were implemented: (1) reduced antibiotic use, which was achieved by not prescribing antibiotics for presumed viral respiratory tract infections (the prescription-reduction group); and (2) better adaptation of dose and duration (the dose/duration group). A control group received no intervention. The target population was children aged 3-6 years who were attending kindergarten. Oropharyngeal pneumococcus colonization and antibiotic use were monitored throughout the 5-month study.

RESULTS

The prescription-reduction, dose/duration, and control groups included 601, 483, and 405 children, respectively. The interventions induced significantly larger decreases in antibiotic use in the prescription-reduction group (-18.8%) and dose/duration group (-17.1%) than in the control group (-3.8%), and the rates of PNSP colonization were initially similar for the 3 groups (52.5%, 55.1%, and 50.0%, respectively). At the end of the 5-month study, the rates of PNSP colonization were 34.5% for the prescription-reduction group (P=.05) and 44.3% for the dose/duration group (P=.8), compared with 46.2% for the control group.

CONCLUSIONS

Intensive educational strategies aimed at optimizing antibiotic use can significantly reduce the rate of PNSP colonization in areas with high resistance rates.

Quinolones in 2005: an update

Quinolones are one of the largest classes of antimicrobial agents used worldwide. This review considers the quinolones that are available currently and used widely in Europe (norfoxacin, ciprofloxacin, ofloxacin, levofloxacin and moxifloxacin) within their historical perspective, while trying to position them in the context of recent and possible future advances based on an understanding of: (1) their chemical structures and how these impact on activity and toxicity; (2) resistance mechanisms (mutations in target genes, efflux pumps); (3) their pharmacodynamic properties (AUC/MIC and Cmax/MIC ratios; mutant prevention concentration and mutant selection window); and (4) epidemiological considerations (risk of emergence of resistance, clonal spread). Their main indications are examined in relation to their advantages and drawbacks. Overall, it is concluded that these important agents should be used in an educated fashion, based on a careful balance between their ease of use and efficacy vs. the risk of emerging resistance and toxicity. However, there is now substantial evidence to support use of the most potent drug at the appropriate dose whenever this is required.

Short- and long-term effects of pneumococcal conjugate vaccination of children on penicillin resistance

Recent observations have shown that wide-scale vaccination with pneumococcal conjugate vaccines was associated with a reduction in invasive disease, supporting the expectation that vaccination could help reduce carriage of Streptococcus pneumoniae and control the spread of resistant strains. However, it is too early to assess whether these effects can be sustained in the long term. Here, we used mathematical modeling to investigate time changes in pneumococcal colonization and resistance induced by conjugate vaccination in an environment where antibiotic exposure is high and resistance is widespread. According to model predictions, vaccination induced a decrease in carriage of vaccine-type pneumococci to very low levels, typically in 10 to 15 years under epidemiologically realistic conditions. Almost simultaneously, non-vaccine-type pneumococci spread in the community. Consequently, while there was a short-term decrease in the overall carriage rate, it was followed after a few years by a renewed, although limited, increase. Vaccination with a heptavalent vaccine did not affect the extent to which antibiotic resistance was selected: in all cases, the distribution of resistance levels peaked at high levels (MIC > 2 microg/ml) after 20 years. With a vaccine optimally designed to include all serotypes currently exhibiting decreased susceptibility to penicillin G, the selection of resistance was slowed down, although not prevented. These results suggest that because of serotype replacement, the effects of vaccination observed today may not be sustained in the long term. As a consequence, vaccination alone may not be successful in controlling selection for resistance in S. pneumoniae.