1 Division of Tuberculosis Elimination, National Center for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA.
2 Independent contractor, Atlanta, GA.
3 Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.
4 Division of Bacterial and Mycotic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA.
Received for publication November 27, 2003; accepted for publication April 6, 2004.
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ABSTRACT |
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contact tracing; DNA fingerprinting; genotype; Mycobacterium tuberculosis; polymorphism, restriction fragment length; tuberculosis
Abbreviations: Abbreviations: CI, confidence interval; NTGSN, National Tuberculosis Genotyping and Surveillance Network; RFLP, restriction fragment length polymorphism.
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INTRODUCTION |
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Genotyping of M. tuberculosis isolates has proven useful in several ways. First, it can identify and confirm M. tuberculosis laboratory cross-contamination or mislabeling events (i.e., false-positive cultures) (611). Second, it can help to determine the extent and distribution of epidemic strains (1216). Third, it can be used to evaluate the performance of prevention and control programs. Since reducing recent transmission represents a major focus of tuberculosis prevention and control, the clustering of M. tuberculosis isolates may identify the proportion of incident cases due to recent transmission (3, 4), albeit with methodological caveats (1719). Genotyping can be used to detect clustered M. tuberculosis isolates, thus showing the impact of interventions aimed at reducing recent transmission (20). Fourth, genotyping offers a more informed picture of a regions epidemiologic features of tuberculosis disease transmission (21, 22) and the patterns, prevalence, and trends of M. tuberculosis strains (including multidrug-resistant M. tuberculosis strains) (23). Fifth, M. tuberculosis genotyping has value during tuberculosis outbreak investigation (24). Since tuberculosis is both common and problematic to control in difficult-to-reach high-risk groups (e.g., homeless persons), genotyping has proven valuable in investigations among these groups (2530). Finally, genotyping has been used to characterize transmission patterns in nontraditional settings and relationships and to model transmission dynamics (21, 31, 32).
Despite these documented benefits, we do not yet fully know what might be termed "the added epidemiologic value" offered to local and state tuberculosis prevention and control programs by the universal availability of M. tuberculosis genotyping. By using the term, "added epidemiologic value," we refer to the otherwise unknown, direct knowledge or predictive power that would epidemiologically link the person, time, or place variables of tuberculosis cases with ongoing chain(s) of transmission. This direct knowledge or predictive power gained from universal M. tuberculosis genotyping comes over and beyond that yielded through conventional contact investigation. The gain comes during the subsequent and additional epidemiologic investigations of tuberculosis cases having genotypically matched M. tuberculosis isolates. These additional investigationscalled cluster investigationscan yield additional person, time, or place knowledge or predictive power to help guide the investigation of tuberculosis cases that are not epidemiologically linked during conventional contact investigation, yet the molecular evidence indicates otherwise. By discovering additional epidemiologic linkages (physical (i.e., settings or relationships) and temporal connections between or among tuberculosis cases), investigators find crucial evidence for ongoing tuberculosis transmission.
The added epidemiologic value yielded through cluster investigations can help to identify, focus, and prioritize new or current tuberculosis prevention and control efforts in several ways. For instance, cluster investigations can detect previously unrecognized tuberculosis cases and illuminate unknown chains of transmission. Further, cluster investigations can improve the efficiency of resource utilization by identifying tuberculosis cases that are not part of a chain of ongoing transmission. In addition, cluster investigations can target resources directed at tuberculosis transmission among newly identified high-risk populations that might otherwise go undiscovered during conventional contact investigations. Finally, with cluster investigation, local and state tuberculosis programs can measure recent tuberculosis transmission and monitor progress toward tuberculosis elimination targets.
To provide information that would guide national tuberculosis recommendations about the universal genotyping of M. tuberculosis isolates, we quantified the added epidemiologic value of the cluster investigation and performed a case-control study to determine the predictors of discovering an epidemiologic linkage during cluster investigation that might otherwise evade conventional contact investigation.
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MATERIALS AND METHODS |
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M. tuberculosis isolates were genotyped using standard methods for the insertion sequence designated IS6110 by restriction fragment length polymorphism (RFLP) and then given a national genotype designation (23). Laboratories conducting genotyping in the four NTGSN sites included the Alabama Department of Public Health and University of Alabama at Birmingham; Central Arkansas Veterans Health Care Services; California Department of Health Services; and the New York State Health Department, Wadsworth Center.
For M. tuberculosis isolates with greater than six bands (or copies) of IS6110, the isolates were considered matched if the band pattern was identical. For M. tuberculosis isolates with six or fewer bands of IS6110, the molecular cluster was confirmed by a secondary genotyping technique (spoligotyping) (23) and considered matched if the isolates proved identical by this secondary genotyping technique.
A "cluster pair" refers to two tuberculosis cases within the same NTGSN site having M. tuberculosis isolates with matched genotypes. Cluster investigations were performed when no epidemiologic linkages were discovered during conventional contact investigation and upon learning the results of a matched genotype of the M. tuberculosis isolates between two tuberculosis cases. In other words, cluster investigations were initiated if tuberculosis cases had M. tuberculosis isolates with matched genotypes but no prior epidemiologic linkage.
Cluster investigation data were collected from multiple sources including hospital and clinic records; laboratories; International Classification of Diseases, Ninth Revision, Clinical Modification, discharge data; pharmacy records; medical examiners or coroners records; death certificates; acquired immunodeficiency syndrome surveillance reports; and case interview.
Local and state tuberculosis control personnel attempted to identify directions of transmission between tuberculosis cases. Epidemiologic linkages discovered between cases during conventional contact investigation and during cluster investigation were then recorded by site. Some cluster pairs had no reported relationship or setting in common (i.e., no epidemiologic linkage). These data were then supplemented by national data collected through the "Report of Verified Case of Tuberculosis." This report contained demographic and medical information for tuberculosis cases submitted to the Centers for Disease Control and Prevention as part of the Tuberculosis Information Management System.
We defined three types of epidemiologic linkages: most-certain linkage (having a known direction of transmission between cases); moderately certain linkage (having a known relationship and setting common to cases); and least-certain linkage (having either a known relationship or setting common to cases).
Among cluster pairs in which the directions of transmission were unknown, the source case in each cluster pair was determined using available dates gathered in the Report of Verified Case of Tuberculosis. The dates were ordered from those most accurately reflecting proximity to tuberculosis exposure to those least accurately reflecting exposure. The dates, as defined by the Report of Verified Case of Tuberculosis, included (in order) treatment start date, report date, and count date. When dates were available, the earliest treated, reported, or counted case in the cluster was considered the "source." When no temporal relation could be ascertained between the cases in the cluster pair, the case found more commonly among cluster pairs within the cluster was determined to be the source case.
We performed a case-control study by comparing cluster pairs having epidemiologic linkages discovered only during cluster investigation (cases) with cluster pairs having epidemiologic linkages discovered during conventional contact investigation (controls). Using the algorithm to predict the source case of each cluster pair when the direction of transmission was unknown, we evaluated individual-level predictors of the source case including human immunodeficiency virus positivity, smear-stain negativity, and being foreign born with less than 5 years residence in the United States. In addition, we evaluated two cluster-pair relations: nontraditional transmission settings or relationships and cluster size.
We defined nontraditional settings so as to not include home, school, workplace, or common congregate settings (i.e., correctional facilities, day-care centers, emergency shelters, group quarters, acute-care hospitals, nursing homes, and other long-term-care facilities). The "other" category included all nontraditional settings (e.g., bars, social clubs, "hang outs," churches, or temples).
We defined nontraditional relationships so as to not include household, nonhousehold and friend, and coworker contacts. Examples of nontraditional relationships included a common source (e.g.) having the same person as the source of their infection) or being in the same place at the same time (e.g., being a customer in a store with another tuberculosis case).
Actual p values calculated for frequency comparisons were determined using Epi Info, version 6.04d (33), with the chi-square test for significance. All other statistical analyses were conducted using SAS software, version 8.2 (34). We performed univariate analyses to calculate the crude exposure odds ratios with a 95 percent confidence interval using a generalized estimating equation regression model to control for intracluster dependence. This model, which addressed certain aspects of dependence among cluster pairs, was also applied in conducting the multivariate analyses and in calculating the adjusted odds ratios. In the model (data shown in table 3), the categorization of cluster size into three categories of 1) less than or equal to three, 2) greater than three to less than or equal to five, and 3) greater than five was determined by the distribution of the cluster size. Over 75 percent of clusters had two or three cases per cluster. The likelihood ratio test statistic and corresponding p values were used to determine if the interaction terms added significantly to the model. The final model was determined using the hierarchical backward elimination strategy; the overall fit of the model was evaluated using a mean deviance near one.
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RESULTS |
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Among the 2,141 reported culture-positive NTGSN tuberculosis cases, 2,055 (96 percent) M. tuberculosis isolates were genotyped (figure 1). This resulted in 555 (27 percent) M. tuberculosis isolates contained in 165 molecular clusters ranging from 2 to 20 isolates per cluster. The mean cluster size was 3.7 cases for those with six or fewer bands by RFLP plus matching spoligotype and 3.1 cases for those with greater than six bands by RFLP.
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The most commonly reported types of relationship and setting discovered by only cluster investigation using the most-certain epidemiologic linkage definition were "nonhousehold or friend" relationships (15 of 43 pairs) and "other" settings (22 of 43 pairs) (table 1). Using the moderately certain epidemiologic linkage definition (i.e., direction of transmission was unknown between the two tuberculosis cases in the cluster pair, but both the relationship and the setting were known), we found 115 epidemiologic linkages by conventional contact investigation and 123 by only cluster investigation. By itself, cluster investigation added 123 (52 percent) of the 238 total epidemiologic linkages discovered. The most commonly reported types of relationship and setting discovered by only cluster investigation, using the moderately certain epidemiologic linkage definition, were "common source" (87 of 123 pairs) and "other" (e.g., bars, churches, car pools, social clubs) (72 of 123 pairs). Using the least-certain epidemiologic linkage definition (i.e., direction of transmission was unknown between the two tuberculosis cases in the cluster pair, but either the relationship or the setting was known and within the appropriate temporal framework), we found 117 epidemiologic linkages by conventional contact investigation and 155 by only cluster investigation. By itself, cluster investigation added 155 (57 percent) of the 272 total epidemiologic linkages discovered. The most commonly reported types of relationship and setting discovered by only cluster investigation, using the least-certain epidemiologic linkage definition, were "common source" (90 of 155 pairs) and "other" (99 of 155 pairs).
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DISCUSSION |
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We chose the unit of analyses of this study to be a tuberculosis cluster pair, defined as two cases having genotypically matched M. tuberculosis isolates. We performed a case-control study by comparing cluster pairs having epidemiologic linkages discovered only during cluster investigation (cases) with cluster pairs having epidemiologic linkages discovered during conventional contact investigation (controls). By design, the additional investigational effort required of the cluster investigation undoubtedly increased the number of epidemiologic linkages found among cluster pairs, because cluster pairs who were not previously epidemiologically linked by conventional contact investigation were reexamined.
So, there existed a detection bias, in that those cluster pairs "negative" at first, in terms of initially finding epidemiologic linkages during conventional contact investigation, were reexamined with the specific focus of attempting to find an epidemiologic linkage that might be missed during the conventional contact investigation. However, the additional effort required by cluster investigations, while adding a detection bias, could not be assumed to be a confounder, defined as having influence on both the outcome and exposure. This is because the additional effort required to perform cluster investigations did not preferentially seek out a specific type of epidemiologic linkage (e.g., nontraditional settings or relationships). Therefore, the additional effort, while influencing the outcome, would not necessarily influence the exposure.
For the moderately and least-certain definitions of an epidemiologic linkage, in some instances, the four NTGSN sites might have coded an identical setting or relationship for all cluster pairs investigated. This might be especially true when investigating larger clusters. If this happened, all cluster pairs identified could not be true instances of tuberculosis transmission, as the actual number of epidemiologic linkages must be some subset of this total. If this situation occurred, it would cause an overestimation of the number of reported epidemiologic linkages, especially among cluster pairs in larger clusters. However, the same situation would hold true for conventional contact investigations, albeit potentially less dramatic, because the four NTGSN sites coded epidemiologic linkages similarly for both conventional contact and cluster investigations.
However, this limitation does not affect our calculation of the minimum added epidemiologic value of cluster investigations, because cluster pairs were defined as having known directions of transmission. Therefore, 38 percent should be an accurate minimum measure of added epidemiologic value, while 52 percent and 57 percent for moderately certain and least-certain epidemiologic linkages, respectively, might be overestimated. The estimation of the exposure odds ratios might also be overstated.
Using data from all seven NTGSN sites, Bennett et al. (35) reported that 29 percent of cluster pairs epidemiologically linked during conventional contact investigation did not have genotypically matched M. tuberculosis isolates. In the present study, we found similar results using a subset of these data. Possible reasons for these unconfirmed epidemiologic linkages found during conventional contact investigation might include 1) incorrect identification of the source case, 2) lack of laboratory specificity, or 3) changes in the M. tuberculosis genotype patterns over time.
In this study, the individual characteristics (e.g., age, foreign birth, human immunodeficiency virus status) of the source cases within the cluster pairs were not associated with discovering epidemiologic linkages only during cluster investigation. Combined with the finding of discovering more nontraditional epidemiologic linkages by cluster investigation, this might suggest that, as the United States moves closer toward tuberculosis elimination, the "where" (i.e., the setting) of the interaction of tuberculosis cases and contacts might become more important to public health intervention efforts than the "who" (i.e., the identifiable personal characteristics, such as foreign birth or household or work relationship).
Genotyping technology has scientific and field-application limitations. The lack of reproducibility and the difficulty in comparing patterns in an RFLP genotyping database remain important factors in developing strategies for universal implementation. The other important factor is the time required for obtaining the results of RFLP genotyping. For genotyping to provide added epidemiologic value to conventional contact investigation, these molecular data must be available in real time, so that public health intervention specialists can use them to initiate cluster investigation. To address these limitations and to make genotyping data readily available for field application, the Centers for Disease Control and Prevention plans to provide universal access to polymerase chain reaction genotyping that is digital, reproducible, and rapid (36, 37).
The precision of these data is evolving. Clustering does not always represent recent transmission (3842). However, a portion of it does. The limitations of the interpretation of clustering must be scientifically established, especially if it is used as a marker for public health practice performance and as an indication of progress toward tuberculosis elimination. It has been documented that both the population under study and the length of observation play significant roles in interpreting this measure (17, 18). Data from the NTGSN indicated a fairly stable (48 percent) clustering rate after 5 years of observation (43).
We demonstrate here that added epidemiologic value is yielded through cluster investigations. Cluster investigations can identify, focus, and prioritize tuberculosis prevention and control efforts by detecting previously unrecognized tuberculosis cases, as well as illuminate unknown chains of transmission, thus opening new possibilities for prevention and treatment of both tuberculosis cases and persons with latent tuberculosis infection. Further, cluster investigations can improve the efficiency of resource utilization by identifying tuberculosis cases that are not part of a chain of ongoing transmission and target resources directed at tuberculosis transmission among newly identified high-risk populations that might otherwise go undiscovered during conventional contact investigations. Cluster investigations can also help local and state tuberculosis programs in monitoring recent tuberculosis transmission and measurement of progress toward tuberculosis elimination targets.
We recommend that universal M. tuberculosis genotyping be made available in the United States. Progress toward this goal is being made (37). More importantly, the information gained from the genotyping of M. tuberculosis isolates should be used to initiate cluster investigations of those tuberculosis cases not previously discovered as epidemiologically linked during conventional contact investigation. Further, additional information gained from the cluster investigation should be translated into appropriate questions used to conduct conventional contact investigations. Additionally, we recommend the development of better ways to calculate recent tuberculosis transmission in the United States using genotyping data. These efforts could not only help monitor recent tuberculosis transmission for outbreak investigation purposes but also serve as surrogate indicators of tuberculosis elimination and program performance. The expansion of the universal genotyping of M. tuberculosis isolates will improve our understanding of transmission dynamics. Genotyping and cluster investigations will also undoubtedly play a crucial role in measuring tuberculosis elimination in the United States, especially as we gain additional insight and begin to predict recent tuberculosis transmission more accurately.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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