Investigation Of Disease Outbreaks Research Articles

Multiple-locus variable-number tandem-repeat analysis in Salmonella isolates as an effective molecular subtyping method

Due to the limitations of serotyping, to differentiate closely related microbial isolates and to investigate disease outbreaks, molecular genotyping methods including multiple loci variable number of tandem repeats (VNTR) analysis (MLVA) has been developed. The usefulness of MLVA was recently demonstrated for Salmonella Infantis and Salmonella Enteritidis isolated from human sources in Iran. In the present study. The discriminatory ability of this method was investigated in 78 Iranian Salmonella enterica isolates. Salmonella strains isolated from human urine, stool, bone marrow, blood, ascites and synovial fluid sources in Iran during the years 2012 and 2015 were analyzed. Among these 78 Salmonella isolates, 70 isolates belonging to eight serotypes/serogroups, while eight were nontypeable. Six VNTR loci were amplified from all isolates. The isolates were distributed into 67 genotypes. Two out of the 6 markers (Sal20 and Sal16) were highly discriminatory for all strains (DI > 0.80) while composition of all VNTR loci produced 67 different types with 0.995 D value. The high discrimination power of MLVA in Salmonella molecular typing via combination of VNTR loci studied here, suggesting that this method is highly valuable for molecular epidemiology of Salmonella strains.

Outbreak of Burkholderia cepacia bacteraemia in a tertiary care centre due to contaminated ultrasound probe gel

Burkholderia cepacia is an important opportunistic organism in hospitalized and immunocompromised patients, particularly in cystic fibrosis. To describe the epidemiological investigation of an outbreak of B.cepacia bacteraemia. The study examined 14 patients during their admission to three intensive care units in a tertiary care hospital between January and June 2016. The outbreak involved nine (57%) female and six (43%) male patients. All patients were adults of ages ranging from 19 to 85 years with a median age of 52 years. Patients' medical charts, laboratory cultures, exposures, and central line insertion procedures were reviewed. B.cepacia was isolated from the blood cultures of 14 patients resulting from contamination of the gel applied to the ultrasound probe used to guide the insertion of a central venous catheter. Molecular pathogen typing using pulsed-field gel electrophoresis showed 95% similarity between the B.cepacia isolates from the blood of these patients and those isolated from the ultrasound gel. Ongoing surveillance and prompt investigation of unusual disease outbreaks are vital for identifying sources of contamination of B.cepacia and protecting at-risk patients. Sound epidemiological methods are very important for identifying the source of any hospital infection outbreak.

Surveillance for foodborne disease outbreaks in China, 2003 to 2008

Knowledge of implicated food vehicles and contributing factors derived from foodborne disease outbreak (FBDO) investigations allows consumers to be educated on decreasing high-risk behavior to reduce the risk of being affected by foodborne diseases. Food safety regulatory authorities also need summary of outbreak data, as these data indicate where the existing food supply system should be improved. To obtain information on epidemiology of FBDOs in China, FBDOs reported to the China National Foodborne Diseases Surveillance Network by 12 surveillance provinces that include 43% of the Chinese population was summarized. Between 2003 and 2008, 2795 FBDOs were reported, resulting in 62559 illnesses, 31261 hospitalizations, and 330 deaths. Outbreak size ranged from 2 to 464 cases, with a median of 14 cases. The outbreak rate had decreased from 1.37 per 1 million population in 2003 to 0.46 per 1 million population in 2008. Of the 2176 outbreaks with a single known etiology, bacteria (1051 outbreaks, 48%), man-made chemical hazards (550 outbreaks, 25%), and animal and plant toxins (536 outbreaks, 25%) were the main courses. Only one outbreak was caused by virus. Of the 1930 outbreaks with a single commodity, plant-based foods were the most common reported (930 outbreaks, 48%), followed by animal-based foods (590 outbreaks, 31%). Outbreaks most frequently occurred in private residences (32%), workplace cafeterias (21%), and restaurants (17%). The most common factor reported in the 2190 outbreaks with known contributing factors were improper cooking (510 outbreaks, 23%), contaminated ingredient (503 outbreaks, 23%), cross contamination (475 outbreaks, 22%) and improper storage (295 outbreaks, 13%). It is considered that FBDOs continue to be an important public health problem in China.

Right-Sizing Technology in the Era of Consumer-Driven Health Care

Technology for modern clinical and public health microbiology laboratories has evolved at an impressive rate over the last two decades. Contemporary diagnostics can rapidly provide powerful data that can impact patient lives and support infectious disease outbreak investigations. At the same time, dramatic changes to health care delivery are putting new pressures on a system that is now focusing on patient-centric, value-driven, convenient care. For laboratories, balancing all these demands in a cost-contained environment remains a challenge. This article explores the current and future directions of diagnostics in our dynamic health care environment.

Whole genome sequence analysis; an improved technology that identifies underlying genotypic differences between closely related Listeria monocytogenes strains

As the new technology of whole genome sequencing (WGS) has been shown to have greater discriminatory power in differentiating strains than the much-used pulsed-field gel electrophoresis (PFGE), there is currently a transition from using PFGE to WGS for disease outbreak investigation. Therefore, there is a need for comparison of bacterial isolates using both PFGE and WGS. In this study, two pairs of L. monocytogenes strains with geographically diverse sources of isolation but which had indistinguishable or closely related PFGE profiles, were subjected to WGS analysis. Comparative analysis of their genomes showed that one pair of strains which had closely related PFGE profiles in fact differed significantly from one another in terms of their antibiotic and heavy metal stress resistance determinants, and mobile genetic elements. Therefore, this research demonstrated the ability of WGS analysis to differentiate very closely related strains and that WGS analysis represents the most effective tool available for subtyping L. monocytogenes isolates.

QUENTIN: reconstruction of disease transmissions from viral quasispecies genomic data.

Genomic analysis has become one of the major tools for disease outbreak investigations. However, existing computational frameworks for inference of transmission history from viral genomic data often do not consider intra-host diversity of pathogens and heavily rely on additional epidemiological data, such as sampling times and exposure intervals. This impedes genomic analysis of outbreaks of highly mutable viruses associated with chronic infections, such as human immunodeficiency virus and hepatitis C virus, whose transmissions are often carried out through minor intra-host variants, while the additional epidemiological information often is either unavailable or has a limited use. The proposed framework QUasispecies Evolution, Network-based Transmission INference (QUENTIN) addresses the above challenges by evolutionary analysis of intra-host viral populations sampled by deep sequencing and Bayesian inference using general properties of social networks relevant to infection dissemination. This method allows inference of transmission direction even without the supporting case-specific epidemiological information, identify transmission clusters and reconstruct transmission history. QUENTIN was validated on experimental and simulated data, and applied to investigate HCV transmission within a community of hosts with high-risk behavior. It is available at https://github.com/skumsp/QUENTIN. pskums@gsu.edu or alexz@cs.gsu.edu or rahul@sfsu.edu or yek0@cdc.gov. Supplementary data are available at Bioinformatics online.

SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology.

The recent widespread application of whole-genome sequencing (WGS) for microbial disease investigations has spurred the development of new bioinformatics tools, including a notable proliferation of phylogenomics pipelines designed for infectious disease surveillance and outbreak investigation. Transitioning the use of WGS data out of the research laboratory and into the front lines of surveillance and outbreak response requires user-friendly, reproducible and scalable pipelines that have been well validated. Single Nucleotide Variant Phylogenomics (SNVPhyl) is a bioinformatics pipeline for identifying high-quality single-nucleotide variants (SNVs) and constructing a whole-genome phylogeny from a collection of WGS reads and a reference genome. Individual pipeline components are integrated into the Galaxy bioinformatics framework, enabling data analysis in a user-friendly, reproducible and scalable environment. We show that SNVPhyl can detect SNVs with high sensitivity and specificity, and identify and remove regions of high SNV density (indicative of recombination). SNVPhyl is able to correctly distinguish outbreak from non-outbreak isolates across a range of variant-calling settings, sequencing-coverage thresholds or in the presence of contamination. SNVPhyl is available as a Galaxy workflow, Docker and virtual machine images, and a Unix-based command-line application. SNVPhyl is released under the Apache 2.0 license and available at http://snvphyl.readthedocs.io/ or at https://github.com/phac-nml/snvphyl-galaxy.

Applications of optical DNA mapping in microbiology.

Optical mapping (OM) has been used in microbiology for the past 20 years, initially as a technique to facilitate DNA sequence-based studies; however, with decreases in DNA sequencing costs and increases in sequence output from automated sequencing platforms, OM has grown into an important auxiliary tool for genome assembly and comparison. Currently, there are a number of new and exciting applications for OM in the field of microbiology, including investigation of disease outbreaks, identification of specific genes of clinical and/or epidemiological relevance, and the possibility of single-cell analysis when combined with cell-sorting approaches. In addition, designing lab-on-a-chip systems based on OM is now feasible and will allow the integrated and automated microbiological analysis of biological fluids. Here, we review the basic technology of OM, detail the current state of the art of the field, and look ahead to possible future developments in OM technology for microbiological applications.

A large-scale stochastic spatiotemporal model for Aedes albopictus-borne chikungunya epidemiology.

Chikungunya is a viral disease transmitted to humans primarily via the bites of infected Aedes mosquitoes. The virus caused a major epidemic in the Indian Ocean in 2004, affecting millions of inhabitants, while cases have also been observed in Europe since 2007. We developed a stochastic spatiotemporal model of Aedes albopictus-borne chikungunya transmission based on our recently developed environmentally-driven vector population dynamics model. We designed an integrated modelling framework incorporating large-scale gridded climate datasets to investigate disease outbreaks on Reunion Island and in Italy. We performed Bayesian parameter inference on the surveillance data, and investigated the validity and applicability of the underlying biological assumptions. The model successfully represents the outbreak and measures of containment in Italy, suggesting wider applicability in Europe. In its current configuration, the model implies two different viral strains, thus two different outbreaks, for the two-stage Reunion Island epidemic. Characterisation of the posterior distributions indicates a possible relationship between the second larger outbreak on Reunion Island and the Italian outbreak. The model suggests that vector control measures, with different modes of operation, are most effective when applied in combination: adult vector intervention has a high impact but is short-lived, larval intervention has a low impact but is long-lasting, and quarantining infected territories, if applied strictly, is effective in preventing large epidemics. We present a novel approach in analysing chikungunya outbreaks globally using a single environmentally-driven mathematical model. Our study represents a significant step towards developing a globally applicable Ae. albopictus-borne chikungunya transmission model, and introduces a guideline for extending such models to other vector-borne diseases.

Following the Yellow Brick Road.

Charles Calisher was fascinated by microorganisms from the time he was in high school. He attended Stuyvesant High School in New York City, Philadelphia College of Pharmacy and Science (now University of the Sciences) (BS), then University of Notre Dame in South Bend, Indiana (MS), and finally Georgetown University, in Washington, DC (PhD), the latter while employed at a commercial biological house. He was hired by the US Communicable Disease Center (now the Centers for Disease Control and Prevention) in Atlanta, Georgia, was transferred to its Fort Collins laboratories in 1973, and retired from there in 1992. After traveling the world a bit, Calisher joined the faculty of Colorado State University in 1993, then semiretired as professor emeritus in 2010. During all those years, he developed from a would-be virologist to an arbovirologist-epidemiologist, identifying scores of newly recognized viruses from throughout the world and helping to investigate disease outbreaks and epidemics. His interests (always primarily arboviruses but now also rodent-borne viruses and bat-borne viruses) continue to expand, and he continues to be involved in various aspects of virology and to assist and annoy journal editors and others in regard to viral taxonomy.

Analysis of enteric disease outbreak metrics, British Columbia Centre for Disease Control, 2005-2014.

For enteric disease outbreaks, effective control depends on timely intervention. Routine collection of metrics related to outbreak identification, investigation and control can help evaluate and improve interventions and inform further analyses and modelling of intervention effectiveness. To analyze data from enteric disease outbreaks in British Columbia, generate outbreak metrics and assess their use in evaluating the impact of outbreak interventions. This descriptive study analyzed data from 57 provincial and national enteric disease outbreak investigations involving the British Columbia Centre for Disease Control from 2005 to 2014. Data were extracted from internal files and the Canadian Network for Public Health Intelligence. Outbreak metrics analyzed included days to initiate investigation, days to intervention, number and type of interventions, duration of investigation, duration of outbreak and the total number of cases. The median time to initiate an outbreak investigation was 36 days and the median duration of investigations was 39 days. The median duration of outbreaks was 40 days and the median time to intervene was 10 days. Identification of the source was associated with use of one or more interventions (P<0.0001). The duration of outbreaks was correlated with the number of days to initiate an investigation (rs =0.72, P<0.0001) and number of days to intervene (rs =0.51, P=0.025). Identification and analysis of outbreak metrics establishes benchmarks that can be compared to other jurisdictions. This may support continuous quality improvement and enhance understanding of the impact of public health activities. Date information for public health actions is essential for evaluating the timing and effectiveness of outbreak interventions.

OzFoodNet into the future: the rapid evolution of foodborne disease surveillance in Australia

OzFoodNet is Australia's national enhanced foodborne disease surveillance network. OzFoodNet is currently evolving in order to meet the most significant challenges faced since it commenced in 2000: the transition to culture independent diagnostic tests and the introduction of whole genome sequencing for typing of enteric pathogens. This has changed the nature of foodborne disease surveillance and outbreak investigation in Australia.

An epidemic of spastic paraparesis of unknown aetiology in Northern Mozambique.

This case study is based on a real-life outbreak investigation undertaken in Mozambique in 1981. This case study describes and promotes one particular approach to unknown disease outbreak investigation. Investigational procedures, however, may vary depending on location and outbreak. It is anticipated that the epidemiologist investigating an unknown disease outbreak will work within the framework of a “multidisciplinary investigation team”. It is through the collaborative efforts of this team, with each member playing a critical role, that outbreak investigations are successfully completed. Some aspects of the original outbreak and investigation have, however, been altered to assist in meeting the desired teaching objectives and to allow completion of the case study in less than 3 hours.

Developing a framework to assess the costeffectiveness of COMPARE - a global platform for the exchange of sequence-based pathogen data.

Analysing the genomic data of pathogens with the help of next-generation sequencing (NGS) is an increasingly important part of disease outbreak investigations and helps guide responses. While this technology has already been successfully employed to elucidate and control disease outbreaks, wider implementation of NGS also depends on its cost-effectiveness. COMPARE - short for 'Collaborative Management Platform for detection and Analyses of (Re-) emerging and foodborne outbreaks' - is a major project, funded by the European Union, to develop a global platform for sharing and analysing NGS data and thereby improve the rapid identification, containment and mitigation of emerging infectious diseases and foodborne outbreaks. This article introduces the project and presents the results of a review of the literature, composed of previous relevant cost-benefit and cost-effectiveness analyses. The authors also outline the implications for a methodological framework to assess the costeffectiveness of COMPARE and similar systems.

A brief primer on genomic epidemiology: lessons learned fromMycobacterium tuberculosis

Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis. In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission-informative variation and resistance-associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.

Construction of a Pan-Genome Allele Database of Salmonella enterica Serovar Enteritidis for Molecular Subtyping and Disease Cluster Identification.

We built a pan-genome allele database with 395 genomes of Salmonella enterica serovar Enteritidis and developed computer tools for analysis of whole genome sequencing (WGS) data of bacterial isolates for disease cluster identification. A web server (http://wgmlst.imst.nsysu.edu.tw) was set up with the database and the tools, allowing users to upload WGS data to generate whole genome multilocus sequence typing (wgMLST) profiles and to perform cluster analysis of wgMLST profiles. The usefulness of the database in disease cluster identification was demonstrated by analyzing a panel of genomes from 55 epidemiologically well-defined S. Enteritidis isolates provided by the Minnesota Department of Health. The wgMLST-based cluster analysis revealed distinct clades that were concordant with the epidemiologically defined outbreaks. Thus, using a common pan-genome allele database, wgMLST can be a promising WGS-based subtyping approach for disease surveillance and outbreak investigation across laboratories.

PGAdb-builder: A web service tool for creating pan-genome allele database for molecular fine typing.

With the advance of next generation sequencing techniques, whole genome sequencing (WGS) is expected to become the optimal method for molecular subtyping of bacterial isolates. To use WGS as a general subtyping method for disease outbreak investigation and surveillance, the layout of WGS-based typing must be comparable among laboratories. Whole genome multilocus sequence typing (wgMLST) is an approach that achieves this requirement. To apply wgMLST as a standard subtyping approach, a pan-genome allele database (PGAdb) for the population of a bacterial organism must first be established. We present a free web service tool, PGAdb-builder (http://wgmlstdb.imst.nsysu.edu.tw), for the construction of bacterial PGAdb. The effectiveness of PGAdb-builder was tested by constructing a pan-genome allele database for Salmonella enterica serovar Typhimurium, with the database being applied to create a wgMLST tree for a panel of epidemiologically well-characterized S. Typhimurium isolates. The performance of the wgMLST-based approach was as high as that of the SNP-based approach in Leekitcharoenphon’s study used for discerning among epidemiologically related and non-related isolates.

Vital Signs: Deficiencies in Environmental Control Identified in Outbreaks of Legionnaires’ Disease—North America, 2000–2014

Background The number of reported cases of Legionnaires’ disease, a severe pneumonia caused by the bacterium Legionella, is increasing in the United States. During 2000–2014, the rate of reported legionellosis cases increased from 0.42 to 1.62 per 100 000 persons; 4% of reported cases were outbreak-associated. Legionella is transmitted through aerosolization of contaminated water. A new industry standard for prevention of Legionella growth and transmission in water systems in buildings was published in 2015. CDC investigated outbreaks of Legionnaires’ disease to identify gaps in building water system maintenance and guide prevention efforts. Methods Information from summaries of CDC Legionnaires’ disease outbreak investigations during 2000–2014 was systematically abstracted, and water system maintenance deficiencies from land-based investigations were categorized as process failures, human errors, equipment failures, or unmanaged external changes. Results During 2000–2014, CDC participated in 38 field investigations of Legionnaires’ disease. Among 27 land-based outbreaks, the median number of cases was 10 (range = 3–82) and median outbreak case fatality rate was 7% (range = 0–80%). Sufficient information to evaluate maintenance deficiencies was available for 23 (85%) investigations. Of these, all had at least one deficiency; 11 (48%) had deficiencies in ≥2 categories. Fifteen cases (65%) were linked to process failures, 12 (52%) to human errors, eight (35%) to equipment failures, and eight (35%) to unmanaged external changes. Conclusions and Implications for Public Health Practice Multiple common preventable maintenance deficiencies were identified in association with disease outbreaks, highlighting the importance of comprehensive water management programs for water systems in buildings. Properly implemented programs, as described in the new industry standard, could reduce Legionella growth and transmission, preventing Legionnaires’ disease outbreaks and reducing disease.

Pathogen metadata platform: software for accessing and analyzing pathogen strain information.

BackgroundPathogen metadata includes information about where and when a pathogen was collected and the type of environment it came from. Along with genomic nucleotide sequence data, this metadata is growing rapidly and becoming a valuable resource not only for research but for biosurveillance and public health. However, current freely available tools for analyzing this data are geared towards bioinformaticians and/or do not provide summaries and visualizations needed to readily interpret results.ResultsWe designed a platform to easily access and summarize data about pathogen samples. The software includes a PostgreSQL database that captures metadata useful for disease outbreak investigations, and scripts for downloading and parsing data from NCBI BioSample and BioProject into the database. The software provides a user interface to query metadata and obtain standardized results in an exportable, tab-delimited format. To visually summarize results, the user interface provides a 2D histogram for user-selected metadata types and mapping of geolocated entries. The software is built on the LabKey data platform, an open-source data management platform, which enables developers to add functionalities. We demonstrate the use of the software in querying for a pathogen serovar and for genome sequence identifiers.ConclusionsThis software enables users to create a local database for pathogen metadata, populate it with data from NCBI, easily query the data, and obtain visual summaries. Some of the components, such as the database, are modular and can be incorporated into other data platforms. The source code is freely available for download at https://github.com/wchangmitre/bioattribution.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1231-2) contains supplementary material, which is available to authorized users.

Vital Signs: Deficiencies in Environmental Control Identified in Outbreaks of Legionnaires' Disease - North America, 2000-2014.

The number of reported cases of Legionnaires' disease, a severe pneumonia caused by the bacterium Legionella, is increasing in the United States. During 2000-2014, the rate of reported legionellosis cases increased from 0.42 to 1.62 per 100,000 persons; 4% of reported cases were outbreak-associated. Legionella is transmitted through aerosolization of contaminated water. A new industry standard for prevention of Legionella growth and transmission in water systems in buildings was published in 2015. CDC investigated outbreaks of Legionnaires' disease to identify gaps in building water system maintenance and guide prevention efforts. Information from summaries of CDC Legionnaires' disease outbreak investigations during 2000-2014 was systematically abstracted, and water system maintenance deficiencies from land-based investigations were categorized as process failures, human errors, equipment failures, or unmanaged external changes. During 2000-2014, CDC participated in 38 field investigations of Legionnaires' disease. Among 27 land-based outbreaks, the median number of cases was 10 (range = 3-82) and median outbreak case fatality rate was 7% (range = 0%-80%). Sufficient information to evaluate maintenance deficiencies was available for 23 (85%) investigations. Of these, all had at least one deficiency; 11 (48%) had deficiencies in ≥2 categories. Fifteen cases (65%) were linked to process failures, 12 (52%) to human errors, eight (35%) to equipment failures, and eight (35%) to unmanaged external changes. Multiple common preventable maintenance deficiencies were identified in association with disease outbreaks, highlighting the importance of comprehensive water management programs for water systems in buildings. Properly implemented programs, as described in the new industry standard, could reduce Legionella growth and transmission, preventing Legionnaires' disease outbreaks and reducing disease.