John Stelling

Ability of Laboratories To Detect Emerging Antimicrobial Resistance: Proficiency Testing and Quality Control Results from the World Health Organization's External Quality Assurance System for Antimicrobial Susceptibility Testing

ABSTRACT The accuracy of antimicrobial susceptibility data submitted by microbiology laboratories to national and international surveillance systems has been debated for a number of years. To assess the accuracy of data submitted to the World Health Organization by users of the WHONET software, the Centers for Disease Control and Prevention distributed six bacterial isolates representing key antimicrobial-resistance phenotypes to approximately 130 laboratories, all but one of which were outside of the United States, for antimicrobial susceptibility testing as part of the World Health Organizations External Quality Assurance System for Antimicrobial Susceptibility Testing. Each laboratory also was asked to submit 10 consecutive quality control values for several key organism-drug combinations. Most laboratories were able to detect methicillin (oxacillin) resistance in Staphylococcus aureus, high-level vancomycin resistance in Enterococcus faecium, and resistance to extended-spectrum cephalosporins in Klebsiella pneumoniae. Many laboratories, particularly those using disk diffusion tests, had difficulty in recognizing reduced susceptibility to penicillin in an isolate of Streptococcus pneumoniae. The most difficult phenotype for laboratories to detect was reduced susceptibility to vancomycin in an isolate of Staphylococcus epidermidis. The proficiency testing challenge also included a request for biochemical identification of a gram-negative bacillus, which most laboratories recognized as Enterobacter cloacae. Although only a small subset of laboratories have submitted their quality control data, it is clear that many of these laboratories generate disk diffusion results for oxacillin when testing S. aureus ATCC 25923 and S. pneumoniae ATCC 49619 that are outside of the acceptable quality control range. The narrow quality control range for vancomycin also proved to be a challenge for many of the laboratories submitting data; approximately 27% of results were out of range. Thus, it is important to establish the proficiency of laboratories submitting data to surveillance systems in which the organisms are tested locally, particularly for penicillin resistance in pneumococci and glycopeptide resistance in staphylococci.

A framework for global surveillance of antibiotic resistance

The foreseen decline in antibiotic effectiveness explains the needs for data to inform the global public health agenda about the magnitude and evolution of antibiotic resistance as a serious threat to human health and development. Opportunistic bacterial pathogens are the cause of the majority of community and hospital-acquired infections worldwide. We provide an inventory of pre-existing regional surveillance programs in the six WHO regions which should form the underpinning for the consolidation of a global network infrastructure and we outline the structural components such as an international network of reference laboratories that need to be put in place to address the void of these crucial data. In addition we suggest to make use of existing Health and Demographic Surveillance Sites (HDSS) to obtain crucial information from communities in resource limited settings at household level in low- and middle-income countries in Asia and Africa. For optimising the use of surveillance data for public health action i.e. priority setting for new drug development, comparative quantification of antibiotic effectiveness at local, national, regional and global level and identification of the action gaps can be helpful.

Integrated Multilevel Surveillance of the World's Infecting Microbes and Their Resistance to Antimicrobial Agents

SUMMARY Microbial surveillance systems have varied in their source of support; type of laboratory reporting (patient care or reference); inclusiveness of reports filed; extent of microbial typing; whether single hospital, multihospital, or multicountry; proportion of total medical centers participating; and types, levels, integration across levels, and automation of analyses performed. These surveillance systems variably support the diagnosis and treatment of patients, local or regional infection control, local or national policies and guidelines, laboratory capacity building, sentinel surveillance, and patient safety. Overall, however, only a small fraction of available data are under any surveillance, and very few data are fully integrated and analyzed. Advancing informatics and genomics can make microbial surveillance far more efficient and effective at preventing infections and improving their outcomes. The worlds microbiology laboratories should upload their reports each day to programs that detect events, trends, and epidemics in communities, hospitals, countries, and the world.

Integrating Escherichia coli Antimicrobial Susceptibility Data from Multiple Surveillance Programs

Collaboration between networks presents opportunities to increase analytical power and cross-validate findings. Multivariate analyses of 2 large, international datasets (MYSTIC and SENTRY) from the Global Advisory on Antibiotic Resistance Data program explored temporal, geographic, and demographic trends in Escherichia coli resistance from 1997 to 2001. Elevated rates of nonsusceptibility were seen in Latin America, southern Europe, and the western Pacific, and lower rates were seen in North America. For most antimicrobial drugs considered, nonsusceptibility was higher in isolates from men, older patients, and intensive care unit patients. Nonsusceptibility to ciprofloxacin was higher in younger patients, rose with time, and was not associated with intensive care unit status. In univariate analyses, estimates of nonsusceptibility from MYSTIC were consistently higher than those from SENTRY, but these differences disappeared in multivariate analyses, which supports the epidemiologic relevance of findings from the 2 programs, despite differences in surveillance strategies.

Automated detection of infectious disease outbreaks in hospitals: a retrospective cohort study.

Susan Huang and colleagues describe an automated statistical software, WHONET-SaTScan, its application in a hospital, and the potential it has to identify hospital infection clusters that had escaped routine detection.

World Health Organization Ranking of Antimicrobials According to Their Importance in Human Medicine: A Critical Step for Developing Risk Management Strategies to Control Antimicrobial Resistance From Food Animal Production

Antimicrobial use in food animals selects for antimicrobial resistance in bacteria, which can spread to people. Reducing use of antimicrobials-particularly those deemed to be critically important for human medicine-in food production animals continues to be an important step for preserving the benefits of these antimicrobials for people. The World Health Organization ranking of antimicrobials according to their relative importance in human medicine was recently updated. Antimicrobials considered the highest priority among the critically important antimicrobials were quinolones, third- and fourth-generation cephalosporins, macrolides and ketolides, and glycopeptides. The updated ranking allows stakeholders in the agriculture sector and regulatory agencies to focus risk management efforts on drugs used in food animals that are the most important to human medicine. In particular, the current large-scale use of fluoroquinolones, macrolides, and third-generation cephalosporins and any potential use of glycopeptides and carbapenems need to be addressed urgently.

WHONET: Removing obstacles to the full use of information about antimicrobial resistance

A rich store of detailed information about antimicrobial resistance is at each medical center in paper files inaccessible to analysis or in electronic files too diverse to support a common analytical software. WHONET puts that information on a personal computer at each center in a file code and format that is the same at all centers, so that one software can then fully analyze the files at any center or those merged from many centers. The software monitors the complex matrix of interrelationships between all the measurements of resistance to antimicrobials of tested isolates of each species and of control strains. Differences at a center over time or between centers reflect differences in test performance or in the prevalence of specific resistant strains, which may be tracked. The software helps workers who are knowledgeable about resistance, infection control and clinical use of antimicrobials at any center to control test quality and integrate the management of resistance there. Their ongoing monitoring and experience locally also builds the quality and interpretation of the files merged from many centers.

Use of Binary Cumulative Sums and Moving Averages in Nosocomial Infection Cluster Detection1

Clusters of nosocomial infection often occur undetected, at substantial cost to the medical system and individual patients. We evaluated binary cumulative sum (CUSUM) and moving average (MA) control charts for automated detection of nosocomial clusters. We selected two outbreaks with genotyped strains and used resistance as inputs to the control charts. We identified design parameters for the CUSUM and MA (window size, k, α, β, p0, p1) that detected both outbreaks, then calculated an associated positive predictive value (PPV) and time until detection (TUD) for sensitive charts. For CUSUM, optimal performance (high PPV, low TUD, fully sensitive) was for 0.1 <α ≤0.25 and 0.2 <β <0.25, with p0 = 0.05, with a mean TUD of 20 (range 8–43) isolates. Mean PPV was 96.5% (relaxed criteria) to 82.6% (strict criteria). MAs had a mean PPV of 88.5% (relaxed criteria) to 46.1% (strict criteria). CUSUM and MA may be useful techniques for automated surveillance of resistant infections.

A Review on Nano-Antimicrobials: Metal Nanoparticles, Methods and Mechanisms

Nanotechnology is a scientific and engineering technology conducted at the nano-scale, such as in the fields of compound fabric manufacturing, food processing, agricultural processing, and engineering, as well as in medical and medicinal applications. In recent decade, nanomaterial applications for antimicrobial works have of prime interest of by many researchers. Available reports show that some of the metal oxide nanoparticles (NPs) including Al2O3, TiO2, ZnO, CuO, Co3O4, In2O3, MgO, SiO2, ZrO2, Cr2O3, Ni2O3, Mn2O3, CoO, and Nickel oxide have toxicity toward several microorganisms and they could successfully kill numerous bacteria. Based on our literature review there are some effective factors that can influence the ability of nanomaterials in reducing or killing the cells, and there are mechanisms for nanomaterial against bacteria, which are briefly listed as follows: surface charge of the metal nanomaterial, shape, type and material, concentration of nanomaterial, dispersion and contact of nanomaterial to the bacterial cell, presence of active oxygen, liberation of antimicrobial ions, medium components and pH, physicochemical properties, specific surface-area-to-volume ratios, size, role of growth rate, role of biofilm formation, cell wall of bacteria, and effect of UV illumination. It can be considered that in the use of nanomaterials as antimicrobial agents, consideration of many factors remain principal. Antibacterial resistance to common chemical antibacterial agents can be due to long production-consumption cycle, thereby reducing their efficiency, and use of poor quality or fake medicines in undeveloped and developing countries. NPs as antimicrobial agents have become an emerging approach against this challenge, which can establish an effective nanostructure to deliver the antimicrobial agents for targeting the bacterial community efficiently. In addition, they are so potent that microbial pathogens cannot develop resistance to wards them. On the other hand, most of the metal oxide NPs have no toxicity toward humans at effective concentrations used to kill bacterial cells, which thus becomes an advantage for using them in a full scale. However, over the present decade, several studies have suggested that NPs are excellent antibacterial agents, at least at the research level.

Laboratory-Based Prospective Surveillance for Community Outbreaks of Shigella spp. in Argentina

Background To implement effective control measures, timely outbreak detection is essential. Shigella is the most common cause of bacterial diarrhea in Argentina. Highly resistant clones of Shigella have emerged, and outbreaks have been recognized in closed settings and in whole communities. We hereby report our experience with an evolving, integrated, laboratory-based, near real-time surveillance system operating in six contiguous provinces of Argentina during April 2009 to March 2012. Methodology To detect localized shigellosis outbreaks timely, we used the prospective space-time permutation scan statistic algorithm of SaTScan, embedded in WHONET software. Twenty three laboratories sent updated Shigella data on a weekly basis to the National Reference Laboratory. Cluster detection analysis was performed at several taxonomic levels: for all Shigella spp., for serotypes within species and for antimicrobial resistance phenotypes within species. Shigella isolates associated with statistically significant signals (clusters in time/space with recurrence interval ≥365 days) were subtyped by pulsed field gel electrophoresis (PFGE) using PulseNet protocols. Principal Findings In three years of active surveillance, our system detected 32 statistically significant events, 26 of them identified before hospital staff was aware of any unexpected increase in the number of Shigella isolates. Twenty-six signals were investigated by PFGE, which confirmed a close relationship among the isolates for 22 events (84.6%). Seven events were investigated epidemiologically, which revealed links among the patients. Seventeen events were found at the resistance profile level. The system detected events of public health importance: infrequent resistance profiles, long-lasting and/or re-emergent clusters and events important for their duration or size, which were reported to local public health authorities. Conclusions/Significance The WHONET-SaTScan system may serve as a model for surveillance and can be applied to other pathogens, implemented by other networks, and scaled up to national and international levels for early detection and control of outbreaks.