A total of 63 clinical isolates of Proteus mirabilis collected over a 19-month period were typed by the Dienes test and ribotyping. Ribotyping was performed using the fully automated RiboPrinter Microbial Characterization System (Qualicon, Wilmington, Del.). Isolates that were indistinguishable by the Dienes test and/or ribotyping were characterized further by pulsed-field gel electrophoresis (PFGE). Most of the isolates represented unique strains as judged by the Dienes test and ribotyping. Forty isolates represented 40 different ribotypes and Dienes types. The remaining 23 isolates were grouped into 13 Dienes types, 12 ribotypes, and 14 PFGE types. The index of discrimination was 0.980 for the Dienes test, 0.979 for ribotyping, and 0.992 for PFGE. Both the Dienes test and ribotyping are useful methods for identifying individual strains of P. mirabilis. The Dienes test is simple, inexpensive, and easy to perform. It can be performed in virtually any laboratory and should be used in the initial epidemiologic characterization of P. mirabilis isolates.
Shigella sonnei is a major cause of diarrheal disease in developed as well as in developing countries. Epidemiologic studies of this organism have been limited by the lack of a simple and effective method for comparing strains. In this study, we have compared different molecular typing methods, i.e., plasmid profile analysis, restriction endonuclease analysis of plasmids, rRNA gene restriction analysis (ribotyping), pulsed-field gel electrophoresis (PFGE), and enterobacterial repetitive intergenic consensus (ERIC) sequence-based PCR (ERIC-PCR) for typing 20 clinical isolates of S. sonnei collected from six incidents of infection. PFGE and ERIC-PCR fingerprintings had the highest discriminatory power for discrimination of epidemiologically related isolates from epidemiologically unrelated strains of S. sonnei, and both gave seven distinct strain types among these isolates and the type strain of the species. Plasmid study and ribotyping produced only six and typing techniques demonstrated two distinct patterns, respectively, among these strains. All of these molecular an identical fingerprint for eight temporally related sporadic isolates. It is possible that these temporally related isolates belonged to a single bacterial clone and circulated obscurely through the community. Our results indicate that the ERIC-PCR technique represents a rapid and simple means for typing S. sonnei with a level of discrimination equivalent to that of PFGE but greater than those of plasmid profile analysis...
Representative isolates of the 10 serogroups of Clostridium difficile and 39 clinical isolates (30 toxigenic and 9 nontoxigenic), including 5 isolates from a confirmed nosocomial outbreak, were analyzed by using two previously described arbitrary-primer PCR (AP-PCR) molecular typing methodologies (AP-PG05 and AP-ARB11) and PCR ribotyping. The two AP-PCR methods investigated gave comparable results; AP-PG05 and AP-ARB11 identified 8 and 7 groups among the serogroup isolates and classified the clinical isolates into 21 and 20 distinct groups, respectively. PCR ribotyping also identified 8 unique groups among the serogroup isolates but classified the clinical isolates into 23 groups. In addition, when results obtained by the PCR methods were compared with typing data generated by pulsed-field gel electrophoresis (PFGE), PCR ribotyping and PFGE were found to be in agreement for 83% (29 of 35) of isolates typeable by both techniques while AP-PG05 was in agreement with PFGE for 60% (20 of 33) and AP-ARB11 was in agreement with PFGE for only 44% (17 of 36). These results indicate that PCR ribotyping is a more discriminatory approach than AP-PCR for typing C. difficile and, furthermore, that this technique generates results that are in higher concordance with those obtained by using an established method for differentiating isolates of this organism on a molecular level than are results generated by using AP-PCR.
Respiratory specimens from 160 geriatric patients with suspected influenza illness were used to evaluate the abilities of two enzyme immunoassays (EIAs; Directigen FLU-A [Becton Dickinson Microbiology Systems, Cockeysville, Md.] and Prima EIA [Baxter/Bartels Diagnostics, Inc., Issaquah, Wash.]) and direct immunofluorescence testing (immunofluorescence assay [IFA]) to identify influenza A virus. In comparison with culture isolation, the sensitivities and specificities of the IFA, Directigen FLU-A, and Prima EIA were 92.5 and 97.2%, 86.8 and 99.1%, and 92.5 and 98.1%, respectively. In contrast to EIA, IFA was labor intensive and required a high degree of technical expertise, and the results of IFA were difficult to interpret. These factors may preclude the use of IFA for testing large numbers of specimens. A retrospective epidemiologic survey of influenza infection was done in six geriatric institutions which had used either rapid and culture testing or culture alone. Preventable cases of influenza A virus infection ranged from 9 to 38% of all cases in facilities which used culture testing only and which had not instituted amantadine prophylaxis. The use of direct specimen testing is recommended as an adjunct to culture isolation for the identification of influenza A virus. Use of a combination of these methods permits the timely administration of appropriate antiviral therapy and infection control measures...
A set of 103 epidemiologically well-defined Acinetobacter baumannii isolates obtained from nine hospital outbreaks and 21 unrelated strains were characterized by pulsed-field gel electrophoresis (PFGE) of total genomic DNA digested with ApaI. Among outbreak strains, eight different patterns and five possible variants were identified by PFGE. Results were compared with those from traditional typing methods such as plasmid profile analysis, antimicrobial susceptibility, and biotyping. Plasmid analysis revealed six different and two related patterns; one outbreak strain lacked plasmids. A total of 16 of the 21 unrelated strains harbored plasmids and exhibited unique patterns. Epidemiologically unrelated strains were placed into only two biotypes and had similar antimicrobial susceptibility patterns but were clearly distinguished by PFGE. PFGE of A. baumannii chromosomal DNA yielded reproducible and easily readable results and showed excellent discriminatory power. However, plasmid profile analysis may provide a cost-effective first step in epidemiological typing of A. baumannii isolates obtained from well-defined hospital outbreaks.
We compared two Campylobacter serotyping systems by using 1,405 isolates of Campylobacter collected from human, animal, and environmental sources during epidemiologic investigations and special studies. We found 96.1% of isolates to be typable by the Penner method for heat-stable antigens, which involved the use of an indirect hemagglutination technique, and 92.1% of isolates to be typable by the Lior method for heat-labile antigens, which involved the use of a slide agglutination technique and absorbed antisera. Absorbed antisera were not required for the Penner method, making that method less difficult to implement. The Lior method was simpler to perform and gave more rapid results than did the Penner method. Cultures frequently reacted in multiple antisera with the Penner method, whereas multiple reactions were rare with the Lior method. Thus, results were easier to interpret with the Lior system. Strains of a single serotype in one system were sometimes found to be multiple serotypes in the other system; hence, the two methods have the potential to be complementary. Both systems were comparable in serotyping isolates from human and nonhuman sources and for evaluating the relationship of strains collected during outbreak investigations.
Because of concern for heat-related mortality in vulnerable populations, particularly the elderly, practical epidemiologic methods are needed for the assessment of ambient heat exposure on individuals. We used a personal monitor to measure body temperature, ambient temperature, heart rate, and activity level of 42 elderly residents of Baltimore, Maryland, in the summer months of 2000. Each participant was monitored for approximately 48 hr to examine the association between ambient temperature and body temperature, using regression methods that account for highly correlated data within individuals. We also examined the associations of Baltimore temperature data with personal ambient temperature and body temperature. An average 0.15 degrees F [95% confidence interval (CI), 0.05-0.25] increase in median body temperature was found for each 1 degrees F increase in median ambient temperature. Heart rate and activity level were not found to be related to body temperature or ambient temperature, although heart rate was associated with activity level. Median heart rate increased an average of 0.17 (95% CI, 0.13-0.21) beats per minute for every unit increase in median activity level. Personal ambient temperature was slightly lower than Baltimore temperatures...
OBJECTIVES: This study examined whether data routinely available in emergency departments could be used to improve isolation decisions for tuberculosis patients. METHODS: In a large emergency department in New York City, we compared the exposure histories of tuberculosis culture-positive and culture-negative patients and used these data to develop a rapid decision instrument to predict culture-positive tuberculosis. The screen used only data that are routinely available to emergency physicians. RESULTS: The method had high sensitivity (.96) and moderate specificity (.54). CONCLUSIONS: The method is easily adaptable for a broad range of settings and illustrates the potential benefits of applying basic epidemiologic methods in a clinical setting.
More than 30 different methods have been used to assess physical activity. These methods can be grouped into seven major categories: calorimetry, job classification, survey procedures, physiological markers, behavioral observation, mechanical and electronic monitors, and dietary measures. No single instrument fulfills the criteria of being valid, reliable, and practical while not affecting behavior. The instruments that are very precise tend to be impractical on a population basis. Surveys are the most practical approach in large-scale studies, although little is known about their reliability and validity. Studies employing objective monitoring through heart rate, movement sensors, and doubly labeled water procedures appear promising, but are still experimental and costly. Despite the difficulty of measurement, relatively strong association has been found between physical activity and health, suggesting that, with improvements in assessment techniques, even stronger associations should be seen.
Molecular diagnostic and epidemiology studies require appreciable amounts of high-quality DNA. Molecular epidemiologic methods have not been routinely applied to the obligate intracellular organism Mycobacterium leprae because of the difficulty of obtaining a genomic DNA template from clinical material. Accordingly, we have developed a method based on isothermic multiple-displacement amplification to allow access to a high-quality DNA template. In the study described in this report, we evaluated the usefulness of this method for error-sensitive, multiple-feature molecular analyses. Using test samples isolated from lepromatous tissue, we also evaluated amplification fidelity, genome coverage, and regional amplification bias. The fidelity of amplified genomic material was unaltered; and while regional differences in global amplification efficiency were seen by using comparative microarray analysis, a high degree of concordance of amplified genomic DNA was observed. This method was also applied directly to archived tissue specimens from leprosy patients for the purpose of molecular typing by using short tandem repeats; the success rate was increased from 25% to 92% without the introduction of errors. This is the first study to demonstrate that serial whole-genome amplification can be coupled with error-sensitive molecular typing methods with low-copy-number sequences from tissues containing an obligate intracellular pathogen.
OBJECTIVES. A geographic information system was used to identify and locate residential environmental risk factors for Lyme disease. METHODS. Data were obtained for 53 environmental variables at the residences of Lyme disease case patients in Baltimore County from 1989 through 1990 and compared with data for randomly selected addresses. A risk model was generated combining the geographic information system with logistic regression analysis. The model was validated by comparing the distribution of cases in 1991 with another group of randomly selected addresses. RESULTS. In crude analyses, 11 environmental variables were associated with Lyme disease. In adjusted analyses, residence in forested areas (odds ratio [OR] = 3.7, 95% confidence interval [CI] = 1.2, 11.8), on specific soils (OR = 2.1, 95% CI = 1.0, 4.4), and in two regions of the county (OR = 3.5, 95% CI = 1.6, 7.4) (OR = 2.8, 95% CI = 1.0, 7.7) was associated with elevated risk of getting Lyme disease. Residence in highly developed regions was protective (OR = 0.3, 95% CI = 0.1, 1.0). The risk of Lyme disease in 1991 increased with risk categories defined from the 1989 through 1990 data. CONCLUSIONS. Combining a geographic information system with epidemiologic methods can be used to rapidly identify risk factors of zoonotic disease over large areas.
Methods of statistical analysis of censored survival times are briefly reviewed and illustrated by application to clinical trials data. These include estimation of the survival curce, nonparametric tests to compare several survival curves, tests for trend, and regression analysis. Extensions of the methodology are made for application to epidemiologic case-control studies. These are used to estimate relative risks for leukemia associated with radiation exposures. A final section provides some annotated references to the recent literature.
Public health is paying increasing attention to elusive urban populations such as the homeless, street drug users, and illegal immigrants. Yet, valid data on the health of these populations remain scarce; longitudinal research, in particular, has been hampered by poor follow-up rates. This paper reports on the follow-up methods used in two randomized clinical trials among one such population, namely, homeless men with mental illness. Each of the two trials achieved virtually complete follow-up over 18 months. The authors describe the ethnographic approach to follow-up used in these trials and elaborate its application to four components of the follow-up: training interviewers, tracking participants, administering the research office, and conducting assessments. The ethnographic follow-up method is adaptable to other studies and other settings, and may provide a replicable model for achieving high follow-up rates in urban epidemiologic studies.
Causal inference methods allow estimation of the effects of potential public health interventions on the population burden of disease. Motivated by calls for epidemiologic research to be presented in ways that are more informative for intervention, the authors present a didactic discussion of the steps required to estimate the population effect of a potential intervention using an imputation-based causal inference method and discuss the assumptions of and limitations to its use. An analysis of neighborhood smoking norms and individual smoking behavior is used as an illustration. The implementation steps include the following: 1) modeling the adjusted exposure and outcome association, 2) imputing the outcome probability for each individual while manipulating the exposure by “setting” it to different values, 3) averaging these probabilities across the population, and 4) bootstrapping confidence intervals. Imputed probabilities represent counterfactual estimates of the population smoking prevalence if neighborhood smoking norms could be manipulated through intervention. The degree to which temporal ordering, randomization, stability, and experimental treatment assignment assumptions are met in the illustrative example is discussed...
We conducted a population-based molecular typing of all Mycobacterium tuberculosis isolates obtained in Alabama since 1994. Of 2,452 isolates, 1,013 (41%) had fewer than 6 bands of IS6110; 348 (14%) had a single two-band pattern (JH2). With conventional epidemiologic methods, we identified three groups of related patients with JH2 isolates. Spoligotyping and pattern of variable number of tandem repeats identified 10 molecular groups; two found by conventional methods were subdivided.
Length-biased time-to-event data are commonly encountered in applications ranging from epidemiologic cohort studies or cancer prevention trials to studies of labor economy. A longstanding statistical problem is how to assess the association of risk factors with survival in the target population given the observed length-biased data. In this paper, we demonstrate how to estimate these effects under the semiparametric Cox proportional hazards model. The structure of the Cox model is changed under length-biased sampling in general. Although the existing partial likelihood approach for left-truncated data can be used to estimate covariate effects, it may not be efficient for analyzing length-biased data. We propose two estimating equation approaches for estimating the covariate coefficients under the Cox model. We use the modern stochastic process and martingale theory to develop the asymptotic properties of the estimators. We evaluate the empirical performance and efficiency of the two methods through extensive simulation studies. We use data from a dementia study to illustrate the proposed methodology, and demonstrate the computational algorithms for point estimates, which can be directly linked to the existing functions in S-PLUS or R.
Salmonella enterica subsp. enterica is the leading cause of bacterial food-borne disease in the United States. Molecular subtyping methods are powerful tools for tracking the farm-to-fork spread of food-borne pathogens during outbreaks. In order to develop a novel multilocus sequence typing (MLST) scheme for subtyping the major serovars of S. enterica subsp. enterica, the virulence genes sseL and fimH and clustered regularly interspaced short palindromic repeat (CRISPR) loci were sequenced from 171 clinical isolates from nine Salmonella serovars, Salmonella serovars Typhimurium, Enteritidis, Newport, Heidelberg, Javiana, I 4,,12:i:−, Montevideo, Muenchen, and Saintpaul. The MLST scheme using only virulence genes was congruent with serotyping and identified epidemic clones but could not differentiate outbreaks. The addition of CRISPR sequences dramatically improved discriminatory power by differentiating individual outbreak strains/clones. Of particular note, the present MLST scheme provided better discrimination of Salmonella serovar Enteritidis strains than pulsed-field gel electrophoresis (PFGE). This method showed high epidemiologic concordance for all serovars screened except for Salmonella serovar Muenchen. In conclusion...
Kotloff, Karen L.; Blackwelder, William C.; Nasrin, Dilruba; Nataro, James P.; Farag, Tamer H.; van Eijk, Annemieke; Adegbola, Richard A.; Alonso, Pedro L.; Breiman, Robert F.; Golam Faruque, Abu Syed; Saha, Debasish; Sow, Samba O.; Sur, Dipika; Zaidi, An
Fonte: Oxford University PressPublicador: Oxford University Press
Background. Diarrhea is a leading cause of illness and death among children aged <5 years in developing countries. This paper describes the clinical and epidemiological methods used to conduct the Global Enteric Multicenter Study (GEMS), a 3-year, prospective, age-stratified, case/control study to estimate the population-based burden, microbiologic etiology, and adverse clinical consequences of acute moderate-to-severe diarrhea (MSD) among a censused population of children aged 0–59 months seeking care at health centers in sub-Saharan Africa and South Asia.
The need for resource-intensive laboratory assays to assess exposures in many epidemiologic studies provides ample motivation to consider study designs that incorporate pooled samples. In this paper, we consider the case in which specimens are combined for the purpose of determining the presence or absence of a pool-wise exposure, in lieu of assessing the actual binary exposure status for each member of the pool. We presume a primary logistic regression model for an observed binary outcome, together with a secondary regression model for exposure. We facilitate maximum likelihood analysis by complete enumeration of the possible implications of a positive pool, and we discuss the applicability of this approach under both cross-sectional and case-control sampling. We also provide a maximum likelihood approach for longitudinal or repeated measures studies where the binary outcome and exposure are assessed on multiple occasions and within-subject pooling is conducted for exposure assessment. Simulation studies illustrate the performance of the proposed approaches along with their computational feasibility using widely available software. We apply the methods to investigate gene–disease association in a population-based case-control study of colorectal cancer.