Molecular epidemiology of tuberculosis in a sentinel surveillance population. (Tuberculosis Genotyping Network).We conducted a population-based study to assess demographic and risk-factor correlates for the most frequently occurring Mycobacterium tuberculosis genotypes from tuberculosis (TB) patients. The study included all incident, culture-positive TB patients from seven sentinel surveillance sites in the United States from 1996 to 2000. M. tuberculosis isolates were genotyped by IS6110-based restriction fragment length polymorphism and spoligotyping. Genotyping was available for 90% of 11,923 TB patients. Overall, 48% of cases had isolates that matched those from another patient, including 64% of U.S.-born and 35% of foreign-born patients. By logistic regression analysis, risk factors for clustering of genotypes were being male, U.S.-born, black, homeless, and infected with HIV; having pulmonary disease with cavitations on chest radiograph and a sputum smear with acid-fast bacilli; and excessive drug or alcohol use. Molecular characterization of TB isolates permitted risk correlates for clusters and specific genotypes to be described and provided information regarding cluster dynamics over time. ********** Since 1990, characterization of Mycobacterium tuberculosis isolates by molecular methods has been useful in confirming suspected laboratory contamination and as an adjunct to epidemiology-based contact investigation (1-3). Most studies used the restriction fragment length polymorphism (RFLP) technique, based on IS6110 and specific to the M. tuberculosis complex. This genetic element may be present in different positions on the chromosome, resulting in a unique genotype useful for characterizing the strain of M. tuberculosis infecting a patient. Although RFLP has disadvantages (e.g., cost, time required to culture the organism, and specialized training and laboratory equipment), IS6110-based RFLP is the established method considered most discriminatory for genetic characterization of M. tuberculosis strains worldwide (4). In 1996, the Centers for Disease Control and Prevention (CDC) established seven sentinel surveillance sites in the United States (National Tuberculosis Genotyping and Surveillance Network) to assess the utility of molecular genotyping for improving tuberculosis (TB) prevention and control. The TB genotyping network used standardized protocols for molecular characterization of M. tuberculosis isolates from patients in all sentinel sites. The network was designed to address specific epidemiologic questions regarding the natural history, transmission, and potential applicability of molecular genotyping of M. tuberculosis strains to augment TB control activities (5). Two objectives were to identify and determine the prevalence of specific M. tuberculosis genotype clustering in populations of sentinel surveillance TB patients and to describe the demographic characteristics of these populations and the genotypic characteristics of M. tuberculosis strains in clustered and nonclustered TB cases. We describe demographic and risk factor correlates for the most frequently occurring M. tuberculosis genotypes in isolates collected from sentinel TB patients. Methods This population-based sentinel study included all incident culture-positive TB patients from sentinel sites from January 1996 to December 2000. In brief, the seven sentinel surveillance sites included the states of Arkansas, Maryland, Massachusetts, Michigan, and New Jersey; Dallas, Tarrant, Cameron, and Hidalgo Counties in Texas; and Alameda, Contra Costa, Marin, San Mateo, Santa Clara, and Solano Counties in California. A detailed description of the study's design, participants, population, and laboratory and epidemiologic methods is provided elsewhere (6). All patients included in the study were reported to the CDC national TB case registry on the form Report of a Verified Case of Tuberculosis, a standardized electronic form submitted for TB surveillance to CDC by all state public health reporting areas. Data reported include patient demographics, laboratory test results, drug susceptibilities, information on chest radiographs, and treatment outcomes (7). Investigators from the sentinel surveillance sites submitted patient isolates to the corresponding regional laboratory for genotyping and conducted routine contact investigations. In addition, participants from the surveillance sites performed detailed epidemiologic investigations on groups of persons with M. tuberculosis isolates that had matching genetic patterns or clusters (see below). The regional genotyping laboratories conducted IS6110 RFLP on isolates from sentinel patients. Since low-copy numbers of IS6110 (i.e., six or fewer copies) reduce test specificity, spacer oligonucleotide typing (spoligotyping) was conducted on such isolates. A cluster, which was identified by analysis of the entire TB genotyping network database, was defined as two or more isolates with either identical RFLP patterns (at least seven copies of IS6110) or identical RFLP and spoligotype patterns for isolates with RFLP patterns that had six or fewer copies of IS6110. Differences in the proportion of TB patients from the TB genotyping network population living in cities with populations of <100,000, 100,001 to 250,000, 250,001 to 500,000, and >500,000 were compared with those of the national TB patients for the year 2000 only. Statistics were obtained from the U.S. Census Bureau (available at: URL: http://www.census.gov/ population/cen2000/phc-t6/tab04.pdf). Correlation of average TB incidence among cases at the seven sentinel sites and percentage of cases with isolates that clustered genetically were examined by year by using the Spearman rank correlation statistic. Clustering was determined by examining each year's cases independently. A Mantel-Haenszel chi-square or Fisher exact test was used, as appropriate, to ascertain whether the sentinel population was representative of TB patients in the United States in terms of demographic, clinical, behavioral, or outcome characteristics. We used multiple logistic regression to assess the importance of demographic, clinical, behavioral, or outcome variables in predicting the occurrence of a given genotype for those genetic clusters that occurred most frequently ([greater than or equal to] 20 isolates). The dependent variable was the presence or absence of a given genotype. The best-fit logistic regression model was determined by the strategy of Hosmer and Lemeshow (8). In brief, a univariate analysis of the categorical independent variables was done by using the Mantel-Haenszel chi-square or Fisher exact test, as appropriate; any variable with a significance value of [greater than or equal to] 0.20 was included in a best subset, multivariate logistic regression model. Collinearity of independent variables was assessed by using the variance/covariance matrix from PROC LOGISTIC (SAS Institute, Inc., Cary, NC) to generate condition indices and a matrix of variance decomposition proportions to detect dependencies among the variables (9). Backward elimination of independent variables was performed if the probability of the independent variable was [greater than or equal to] 0.20. Both the Wald statistic and 95% confidence interval were used on each coefficient to assess the significance of variables in each model; the log-likelihood ratio was used to assess the overall significance of the final models, and the Hosmer-Lemeshow statistic was used to evaluate the fit of each of the final models. Data were analyzed by SAS version 8.0 software (SAS Institute, Inc.) (10). Results Sentinel Population Characteristics The incidence of TB cases in the sentinel surveillance sites varied within and among sites over time (Table 1). From 1996 to 2000, the overall incidence of TB in the United States declined from 8.0 to 5.8 per 100,000 inhabitants, and similar downward trends were observed in each of the TB genotyping network sites. The California, New Jersey, Arkansas, and Texas sites had a higher incidence of TB than the overall national rates. The incidence rates in California and Texas (sites that included only six and four counties from each state) were similar to the overall incidence rates for each state (data not shown). In the surveillance area, 15,035 patients with verified TB represented 16% of the TB patients in the United States during the 5-year study period (Table 2). Overall, 11,923 TB patients were culture-positive (721 from Arkansas, 2,842 from California, 1,192 from Maryland, 1,022 from Massachusetts, 1,481 from Michigan, 2,599 from New Jersey, and 2,066 from Texas). Of TB patients in the surveillance areas, 79.3% (11,923) were culture positive, and RFLP results were available for 91.2% (10,883). However, spoligotyping results were not available for 131 of the isolates that had six or fewer copies of IS6110 (5%; n=2,638); thus, these patients were excluded from our analysis. Of 1,171 isolates not genotyped by RFLP or spoligotyping, 12 (1%) were from Michigan, 35 (3%) from Maryland, 40 (3%) from Massachusetts, 110 (9%) from Arkansas, 156 (13%) from Texas, 327 (28%) from California, and 491 (42%) from New Jersey. Primary reasons for lack of genotyping results included inability to obtain cultures from private health-care providers, contamination of cultures, or poorly growing or nonviable cultures. Characteristics of the TB patient population from the genotyping network sentinel sites were comparable with those from the entire United States, with some exceptions (Table 2). Sentinel surveillance populations had higher proportions of women (42% for the genotyping network vs. 37% for the United States overall) and patients in the 15- to 44-year age category, and were more often homeless or lived in correctional or long-term care facilities. Higher proportions of genotyping network patients used intravenous drugs, but fewer patients used noninjecting drugs or alcohol excessively. Of the study population, about 4% reported previous episodes of TB (652 of 15,035; Table 2). Of persons with a previous recent history of TB, 28 had TB after completing >1 year of therapy within the. study period; genotyping data on isolates from both episodes were available for 22 of these persons. A higher number of persons from the TB genotyping network study population lived within city limits (97% vs. 87%). However, when compared with national averages, genotyping network populations were generally from smaller towns and cities: 1,446 (69%) of 2,099 genotyping network patients were from cities and towns with <250,000 inhabitants, compared with 10,093 (62%) of 16,377 TB patients nationwide (Mantel-Haenszel chi square=41.8; p<0.0001). The proportion of foreign-born patients was higher in genotyping network populations compared with the overall national average (50% for genotyping network vs. 41% for the United States). Numbers of foreign-born TB patients increased over time at about the same rate for both genotyping network populations and national TB patients. From 1996 to 2000, national proportions of foreign-born TB patients increased from 37% (7,725/21,045) to 47% (7,593/16,281); in the genotyping network populations, the proportions of foreign-born TB patients increased from 44% (1,153/2,642) to 58% (1,222/ 2,092). Characteristics of the genotyping network population between sites were similar, as were culture-positive genotyping network populations compared with the overall genotyping network case population. Analysis of Genotyping Data The distribution and diversity of RFLP and spoligotyping pattern results from the genotyping network have been discussed in detail (11). In contrast to that analysis, we used both RFLP and spoligotyping results to define genetic clusters. Overall, 6,609 distinct patterns were identified, including 1,029 that contained [greater than or equal to] 2 isolates per cluster. When analyzed by site, 1,018 clusters were identified: 71 clusters were from Arkansas (611 cases genotyped, 2-16 cases per cluster), 233 from California (2,511 cases, 2-128 cases per cluster), 104 from Maryland (1,157 cases, 2-36 cases per cluster), 85 from Massachusetts (982 cases, 2-16 cases per cluster), 125 from Michigan (1,469 cases, 2-102 cases per cluster), 196 from New Jersey (2,112 cases, 2-40 cases per cluster), and 204 from Texas (1,910 cases, 2-96 cases per cluster). Overall, 970 distinct genotypes, including 235 representing clusters, had [less than or equal to] 6 copies (2,507 cases, 24% clustered, 2-93 cases per cluster). In contrast, 794 clusters from 5,639 distinct genotypes had [greater than or equal to] 7 IS6110 copies (8,245 cases, 14% clustered, 2-105 cases per cluster). Most clusters included seven or fewer persons (85%; 900/1,029). Longitudinal Analysis Most clusters occurred in only a single site (66%; 680/ 1,029). However, 260 (25%) were found in two sites, 55 (5%) in three sites, 19 (2%) in four, 8 (1%) in five, and 7 (1%) in six sites. As expected, clusters that spanned multiple sites were larger. Clusters found at a single site averaged four persons per cluster (mean=3.65; standard error [SE] [+ or -] 0.22; n=680), in contrast to 61 persons per cluster for the genotypes found at six sites (mean=61.14; SE [+ or -] 23.6; n=7; Kruskal-Wallis test, p<0.0001). Most (62%) of the 34 clusters that occurred in at least four sites occurred in all 5 years of the study; 26% in 4 years; and 6% each in 3 and 2 years of the study. Changes in proportions of patients with isolates that clustered were observed over time. In the first 2 years of the study, the percentage of the cumulative total number of cases that clustered increased from 28% to 45%; smaller increases occurred thereafter (Figure 1). Overall, the proportion of clustered cases was 48% (5,171/10,752). The percentages of clustered cases by sites were 28% (276/982) for Massachusetts; 34% (393/1,157) for Maryland; 41% (873/2,112) for New Jersey; 42% (1,046/2,511) for California; 44% (266/611) for Arkansas; 49% (720/1,469) for Michigan; and 57% (1,093/ 1,910) for Texas. Maximum cluster size and absolute numbers of cases with isolates that clustered continued to increase through the end of the study. [FIGURE 1 OMITTED] Overall, cases with isolates that clustered showed a concomitant decline with average incidence of TB over the 5-year period (Figure 2). A significant positive association was observed between the percentage of cases with clustered genotypes and TB incidence over time (Spearman rho=0.90; p=0.037). [FIGURE 2 OMITTED] Risk Factor Analyses of Genetic Clusters Compared with persons whose isolates had unique genotypes, persons with isolates that clustered were more likely to be non-Hispanic, black men born in the United States. They were more likely to have pulmonary disease and abnormal chest radiographs with cavities; in addition, they more often had positive sputum smears; were HIV-positive, homeless, or residents of a correctional facility; and used drugs or alcohol excessively (Table 3). Patients with unclustered isolates were 5 years older on the average than those with isolates that clustered (44.8 years vs. 49.4 years, respectively; Table 3). Multiple logistic regression efforts resulted in models that were not robust (data not shown). Except for 4 genotypes, all 34 clusters with [greater than or equal to] 20 isolates per cluster had significant demographic, clinical, and behavioral risk factors (Table 4). Race, ethnicity, and place of birth were frequently significant predictors for a given genotype. Other predictors included gender, age, site of disease, resistance to first-line drugs, and alcohol or drug abuse (Table 4). Twelve (40%) of 30 of these larger clusters were observed in four or more sites over a 5-year period. Lower percentages of foreign-born patients than U.S.-born patients clustered, regardless of the number of IS6110 copies (Figure 3). More than 50% (1,025/1,825) of the foreign-born patients whose isolates clustered had been in the United States for [greater than or equal to] 5 years. Clustering of isolates from foreign-born patients ranged from 15% (49/316) in Michigan to 38% (309/816) in Texas. [FIGURE 3 OMITTED] Discussion This population-based study is the largest that has been conducted in the United States to assess risk factors related to specific M. tuberculosis genotypes. Generally, clustered isolates have been considered recently acquired infections (12). However, this assumption may not always be correct. Clustering does not prove that transmission occurred, and its demonstration depends on adequate sampling of the population, incidence of TB, and characteristics of the study population (e.g., age structure, population mobility, duration of residence, and immune status) (1,13). Only 25%-42% of patients in genetic clusters were shown to have epidemiologic connections with another member of the cluster (14-16). Conventional epidemiologic investigation of these TB patients (including interviews) was conducted, but inclusion in this analysis was outside the scope of this article. Thus, results that indicate clustered genotypes are representative of recent transmission should be interpreted with caution. Given this caveat, our results nevertheless demonstrate several consistent patterns. Differences in demographic and other risk factors for persons with isolates that clustered corroborated those from smaller studies conducted in the United States and larger surveys in Europe. Extensive surveys from the Netherlands (17) also demonstrated that persons with isolates that clustered genetically were younger than those with unique genotypes. Other risk factors for clustering included being male, born in the United States, non-Hispanic black, or homeless; using drags and alcohol excessively; and having pulmonary disease and cavitations on chest radiograph, a sputum smear with acid-fast bacilli, and HIV infection. These risk factors have been observed for TB patients in different communities (12,18,19). The heterogeneity and diversity of the study population may account for our failure to produce a multivariate logistic model to predict clustering. A third of the foreign-born cases were recent immigrants to the United States, and overall, the percentage of clustered isolates from foreign-born persons was lower than the percent age from nonimmigrants (Figure 3), indicating that at least a portion of these cases resulted from reactivation of latent disease or recent infection in the country of origin. In addition, for foreign-born persons, clustering of M. tuberculosis increased with the duration of residence in the United States. These results suggest that recently imported strains of M. tuberculosis from foreign-born persons may not commonly spread to U.S. residents or that transmission may be occurring after a lag time before the imported strains manifest as disease in contacts. Similar observations have been published in studies from San Francisco, New York, Switzerland, and Norway (20-24). These data may also reflect gaps in our knowledge of M. tuberculosis genotypes in circulation; a comparison of the U.S. TB genotyping network results with other databases worldwide may be warranted. Logistic regression analysis of the most commonly occurring strains demonstrated that different risk factors were associated with specific genotypes. Several genotypes were associated with ethnic origin (e.g., Asian or Pacific Islander and Hispanic patients with six and three genotypes, respectively; Table 4). A recent study in Norway showed that several clusters consisted of patients of the same ethnic origin (23). An association has also been observed between the patient's ethnic origin and IS6110 copy number (25). These results, in conjunction with additional epidemiologic data, may be useful in tracking the geographic origin and spread of M. tuberculosis strains of public health importance (26). A small proportion of clustered isolates were from persons from more than four sites spanning 5 years of study (Table 4). Although an in-depth analysis of epidemiologic links was not possible in this study, we found no evidence of recent transmission between patients with identical genotypes from the different states (data not shown); this lack of transmission was also noted in a smaller study in the United States (27). Since TB transmission is generally considered a local event, these ubiquitous genotypes may be widespread because of social factors (e.g., homelessness or alcohol or drug abuse; Table 4). In addition, these genotypes may represent older, endemic domestic strains that have been in the United States for centuries and have dispersed more widely throughout the United States than the more recently imported strains. Further molecular characterization of these genotypes may show additional differences not detected by RFLP. Nonetheless, the effect of M. tuberculosis virulence or host factors on the distribution of these genotypes cannot be ascertained. The proportion of strains that were classified into clusters of identical genotypes (48%) was comparable with proportions in the Netherlands and Denmark (50%) (2,28), but the proportion was considerably higher than in two other countries (17% in Switzerland [29]; 20% in Norway [23]). The cumulative percentage of clustered strains reached a plateau by the end of the study's second year (Figure 1), a finding consistent with other molecular epidemiologic TB studies (2). Increases in maximum cluster size were anticipated because, as sample sizes increase with time, the number of isolates in each cluster indicate that the low-copy IS6110 patterns are not specific, even with the addition of spoligotyping. [FIGURE 1 OMITTED] The sensitivity and specificity of IS6110 RFLP in molecular epidemiologic studies have not been quantified and represent a potential limitation of this study. Although the stability of IS6110 is relatively high, the half-life of IS6110 RFLP is estimated to be 3-10 years (29-31) based on typing of serial isolates from individual patients. A study of isolates from patients in confirmed chains of transmission showed little change in IS6110 patterns (32). Calculation of these rates may be influenced by the duration between time of disease onset and time of sampling and may be proportional to the effectiveness of the TB control program (30). Because genotyping results were not available for 10% of TB cases in this study, estimates of the degree of clustering and the size of clusters are conservative. Some unique isolates might have clustered if some of the missing isolates had been available or if other cases with the same strain were present outside the study area (33). Sentinel surveillance sites defined by artificial boundaries (i.e., state lines) not entirely representative of TB patients from the United States were included in this study. More than 90% of the isolates from patients from the surveillance areas were genotyped, and these isolates were representative of those culture-positive patients from the sentinel surveillance areas. However, 16% of all TB case-patients reported in the United States were included in these sentinel surveillance sites during the 5-year study period. In addition, the sentinel surveillance population had higher proportions of foreign-born persons than the national average. Because of the propensity of foreign-born persons to have isolates with unique genotypes, the actual rate of clustering may have been underestimated. Nonetheless, sentinel surveillance of TB cases has provided a useful method for documenting genotypes in circulation in the United States and for identifying risk factor correlates of common genotypes. Annual declines in TB incidence were paralleled by similar declines in the proportion of cases with genotypes in clusters (Figure 2), a finding consistent with the hypothesis that decreased clustering is expected with declining incidence (20). Since effort was similar each year, this association is not likely to be an artifact related to sample size (i.e., as sample size or number of cases becomes smaller, the probability of detecting clusters decreases). These findings underscore the importance of long-term longitudinal molecular studies and the potential usefulness of these methods in evaluating program effectiveness and improving program management. [FIGURE 2 OMITTED]
Table 1. Incidence of tuberculosis cases in the United States and in
the sentinel surveillance areas of the National Tuberculosis
Genotyping Surveillance Network, 1996-2000 (a)
Sentinel surveillance site 1996 1997 1998 1999
Arkansas 9.0 7.9 6.7 7.1
California (b) 16.3 13.9 13.9 12.9
Maryland 6.3 6.7 6.3 5.7
Massachusetts 4.3 4.4 4.6 4.4
Michigan 4.6 3.8 3.9 3.6
New Jersey 10.3 8.9 7.9 7.0
Texas (b) 12.7 12.8 12.5 10.9
United States 8.0 7.4 6.8 6.4
Sentinel surveillance site 2000 Mean
Arkansas 7.4 7.6
California (b) 11.6 13.7
Maryland 5.3 6.1
Massachusetts 4.5 4.4
Michigan 2.9 3.8
New Jersey 6.7 8.2
Texas (b) 9.6 11.7
United States 5.8 6.9
(a) Number per 100,000 inhabitants.
(b) Sentinel surveillance areas for California and Texas did not
include the entire states.
Table 2. Demographic and risk behavior factors and clinical,
laboratory, and treatment outcomes for the sentinel surveillance
patients (National Tuberculosis Genotyping and Surveillance Network)
compared with factors and outcomes of all tuberculosis patients, United
States, 1996-2000 (a,b)
All U.S. TB cases
Variable Category (n=93,097) (%)
Gender Male 58,356 (62.7)
Female 34,734 (37.3)
Unknown 7 (0.0)
Age (yrs) [less than or equal to] 4 3,289 (3.5)
5-14 2,397 (2.6)
15-24 7,988 (8.6)
25-44 32,433 (34.8)
45-64 25,319 (27.2)
>64 21,662 (23.3)
Unknown 9 (0.0)
Race/ethnicity White, non-Hispanic 22,655 (24.3)
Black, non-Hispanic 30,201 (32.4)
Hispanic 20,475 (22.0)
American Indian/Native 1,280 (1.4)
Asian/Pacific Islander 18,346 (19.7)
Unknown 140 (0.2)
Place of birth U.S.-born 54,341 (58.4)
Foreign-born 38,252 (41.1)
Unknown 504 (0.5)
Years in United
States (foreign-
born only) <1 7,425 (19.4)
1 2,612 (6.8)
2 2,073 (5.4)
3 1,827 (4.8)
4 1,676 (4.4)
[greater than or equal to] 5 19,396 (50.7)
Unknown 3,243 (8.5)
Country of
origin (d) Philippines 4,862 (12.7)
Mexico 8,795 (23.0)
Vietnam 3,824 (10.0)
India 2,527 (6.6)
China 1,930 (5.0)
Haiti 1,470 (3.8)
Peru 636 (1.7)
Republic of Korea 1,176 (3.1)
Ethiopia 578 (1.5)
Ecuador 627 (1.6)
Other 11,827 (30.9)
Status at
diagnosis Alive 90,141 (96.8)
Dead 2,925 (3.1)
Unknown 31 (0.0)
Site of disease Pulmonary 68,611 (73.7)
Extrapulmonary 17,406 (18.7)
Pulmonary and Extrapulmonary 7,046 (7.6)
Unknown 34 (0.0)
Primary disease
site Pulmonary 73,157 (78.6)
Lymph: cervical 4,312 (4.6)
Pleural 3,842 (4.1)
Primary disease
site Miliary 1,407 (1.5)
All other 10,345 (11.1)
Unknown 34 (0.0)
Sputum smear for
acid-fast
organisms Negative 36,912 (39.6)
Positive 33,235 (35.7)
Not done/unknown 22,950 (24.6)
TST at diagnosis Negative 13,215 (14.2)
Positive 54,113 (58.1)
Not done/unknown 25,769 (27.6)
Case verification
criteria Positive culture 74,940 (80.5)
Positive smear 765 (0.8)
Clinical case 11,286 (12.1)
Provider diagnosis 6,106 (6.6)
Chest radio-
graph (e) Cavitary 18,742 (24.8)
Noncavitary 50,652 (66.9)
Normal 2,495 (3.3)
Not done/unknown 3,802 (5.0)
Total 75,691
HIV status (f) Positive 6,062 (18.8)
Negative 16,525 (51.2)
Indeterminate 47 (0.1)
Refused 1,959 (6.1)
Not offered 4,130 (12.8)
Test done, unknown 714 (2.2)
Unknown 2,812 (8.7)
Total 32,249
Homeless within
past year Yes 5,789 (6.2)
No 84,873 (91.2)
Unknown 2,435 (2.6)
Resident of
correctional
facility at
diagnosis Yes 3,352 (3.6)
No 89,479 (96.1)
Unknown 266 (0.3)
Correctional
facility type Federal prison 164 (4.9)
State prison 1,036 (30.9)
Total 3,352
Local jail 1,905 (56.8)
Juvenile facility 33 (1.0)
Other 161 (4.8)
Unknown 53 (1.6)
Yes 3,157 (3.4)
Resident, long-
term care faci-
lity at
diagnosis Unknown 284 (0.3)
Long-term care
facility type Nursing home 1,794 (56.8)
Hospital-based 44l (14.0)
Residential 356 (11.3)
All other 504 (16.0)
Unknown 62 (2.0)
Total 3,157
Injecting drug
use (g) Yes 2,569 (2.8)
No 83,141 (89.3)
Unknown 7,387 (7.9)
Noninjecting drug
use (g) Yes 6,557 (7.0)
No 78,622 (84.5)
Unknown 7,918 (8.5)
Excessive alcohol
use (h) Yes 13,646 (14.7)
No 71,924 (77.3)
Unknown 7,527 (8.1)
Drug resis-
tance (i)
First-line drugs Yes 8,456 (11.7)
No 57,029 (79.0)
Not tested/unknown 6,703 (9.3)
Total 72,188
Second-line drugs Yes 1,341 (1.9)
No 175 (0.2)
Not tested/unknown 70,672 (97.9)
Total 72,188
DOT Yes--total DOT 40,511 (43.5)
Yes--both DOT and self-
administered 20,555 (22.1)
No 23,337 (25.1)
Unknown 8,694 (9.3)
Within city limits Yes 80,775 (86.8)
No 10,916 (11.7)
Unknown 1,406 (1.5)
Previous diagnosis
of TB Yes 4,794 (5.1)
No 87,567 (94.1)
Unknown 736 (0.8)
Duration of
therapy (days) Mean 246
Median 217
Std. dev. 135
No. 65,344
All NTGSN cases
Variable Category (n=15,035) (%)
Gender Male 8,767 (58.3)
Female 6,266 (41.7)
Unknown 2 (0.0)
Age (yrs) [less than or equal to] 4 518 (3.4)
5-14 393 (2.6)
15-24 1,462 (9.7)
25-44 5,413 (36.0)
45-64 3,850 (25.6)
>64 3,397 (22.6)
Unknown 2 (0.0)
Race/ethnicity White, non-Hispanic 3,087 (20.5)
Black, non-Hispanic 4,775 (31.8)
Hispanic 2,923 (19.4)
American Indian/Native 38 (0.3)
Asian/Pacific Islander 4,195 (27.9)
Unknown 17 (0.1)
Place of birth U.S.-born 7,530 (50.1)
Foreign-born 7,468 (49.7)
Unknown 37 (0.2)
Years in United
States (foreign-
born only) <1 1,494 (20.0)
1 567 (7.6)
2 477 (6.4)
3 406 (5.4)
4 361 (4.8)
[greater than or equal to] 5 3,688 (49.4)
Unknown 475 (6.4)
Country of
origin (d) Philippines 1,113 (14.9)
Mexico 1,100 (14.7)
Vietnam 968 (13.0)
India 883 (11.8)
China 370 (5.0)
Haiti 225 (3.0)
Peru 207 (2.8)
Republic of Korea 202 (2.7)
Ethiopia 153 (2.0)
Ecuador 115 (1.5)
Other 2,132 (28.5)
Status at
diagnosis Alive 14,611 (97.2)
Dead 422 (2.8)
Unknown 2 (0.0)
Site of disease Pulmonary 10,576 (70.3)
Extrapulmonary 3,210 (21.4)
Pulmonary and Extrapulmonary 1,241 (8.3)
Unknown 8 (0.1)
Primary disease
site Pulmonary 11,365 (75.6)
Lymph: cervical 1,020 (6.8)
Pleural 674 (4.5)
Primary disease
site Miliary 241 (1.6)
All other 1,727 (11.5)
Unknown 8 (0.0)
Sputum smear for
acid-fast
organisms Negative 5,995 (39.9)
Positive 4,735 (31.5)
Not done/unknown 4,305 (28.7)
TST at diagnosis Negative 1,947 (12.9)
Positive 8,799 (58.5)
Not done/unknown 4,289 (28.6)
Case verification
criteria Positive culture 11,967 (79.6)
Positive smear 136 (0.9)
Clinical case 1,858 (12.4)
Provider diagnosis 1,074 (7.1)
Chest radio-
graph (e) Cavitary 2,990 (25.3)
Noncavitary 7,897 (66.8)
Normal 360 (3.0)
Not done/unknown 578 (4.9)
Total 11,825
HIV status (f) Positive 884 (16.7)
Negative 2,406 (45.5)
Indeterminate 6 (0.1)
Refused 325 (6.1)
Not offered 899 (17.0)
Test done, unknown 115 (2.2)
Unknown 658 (12.4)
Total 5,293
Homeless within
past year Yes 646 (4.3)
No 14,185 (94.3)
Unknown 204 (1.4)
Resident of
correctional
facility at
diagnosis Yes 377 (2.5)
No 14,617 (97.2)
Unknown 41 (0.3)
Correctional
facility type Federal prison 6 (1.6)
State prison 97 (25.7)
Total 377
Local jail 231 (61.3)
Juvenile facility 8 (2.1)
Other 34 (9.0)
Unknown 1 (0.3)
Yes 441 (2.9)
Resident, long-
term care faci-
lity at
diagnosis Unknown 42 (0.3)
Long-term care
facility type Nursing home 279 (63.3)
Hospital-based 66 (15.0)
Residential 34 (7.7)
All other 55 (12.5)
Unknown 7 (1.6)
Total 441
Injecting drug
use (g) Yes 515 (3.4)
No 13,771 (91.6)
Unknown 749 (5.0)
Noninjecting drug
use (g) Yes 811 (5.4)
No 13,367 (88.9)
Unknown 857 (5.7)
Excessive alcohol
use (h) Yes 1,661 (11.0)
No 12,552 (83.5)
Unknown 822 (5.5)
Drug resis-
tance (i)
First-line drugs Yes 1,482 (12.6)
No 8,886 (75.5)
Not tested/unknown 1,399 (11.9)
Total 11,767
Second-line drugs Yes 208 (1.8)
No 78 (0.7)
Not tested/unknown 11,481 (97.6)
Total 11,767
DOT Yes--total DOT 4,936 (32.8)
Yes--both DOT and self-
administered 3,648 (24.3)
No 5,326 (35.4)
Unknown 1,125 (7.5)
Within city limits Yes 14,603 (97.1)
No 374 (2.5)
Unknown 58 (0.4)
Previous diagnosis
of TB Yes 652 (4.3)
No 14,336 (95.4)
Unknown 47 (0.3
Duration of
therapy (days) Mean 245
Median 214
Std. dev. 130
No. 10,822
Variable Category Probability (c)
Gender Male <0.001
Female
Unknown
Age (yrs) [less than or equal to] 4 NS
5-14 NS
15-24 <0.001
25-44 0.05
45-64 <0.001
>64 NS
Unknown
Race/ethnicity White, non-Hispanic <0.001
Black, non-Hispanic NS
Hispanic <0.001
American Indian/Native <0.001
Asian/Pacific Islander <0.001
Unknown
Place of birth U.S.-born <0.001
Foreign-born
Unknown
Years in United
States (foreign-
born only) <1 NS
1 NS
2 <0.005
3 <0.05
4 NS
[greater than or equal to] 5 <0.001
Unknown
Country of
origin (d) Philippines <0.0001
Mexico <0.0001
Vietnam <0.0001
India <0.0001
China NS
Haiti <0.0005
Peru <0.0001
Republic of Korea NS
Ethiopia <0.001
Ecuador NS
Other <0.0001
Status at
diagnosis Alive 0.02
Dead
Unknown
Site of disease Pulmonary <0.001
Extrapulmonary <0.001
Pulmonary and Extrapulmonary 0.003
Unknown
Primary disease
site Pulmonary <0.0001
Lymph: cervical <0.0001
Pleural <0.05
Primary disease
site Miliary NS
All other NS
Unknown
Sputum smear for
acid-fast
organisms Negative <0.0001
Positive
Not done/unknown
TST at diagnosis Negative <0.001
Positive
Not done/unknown
Case verification
criteria Positive culture <0.01
Positive smear NS
Clinical case NS
Provider diagnosis <0.01
Chest radio-
graph (e) Cavitary NS
Noncavitary NS
Normal NS
Not done/unknown
Total
HIV status (f) Positive NS
Negative
Indeterminate
Refused
Not offered
Test done, unknown
Unknown
Total
Homeless within
past year Yes <0.001
No
Unknown
Resident of
correctional
facility at
diagnosis Yes <0.001
No
Unknown
Correctional
facility type Federal prison <0.005
State prison <0.05
Total
Local jail NS
Juvenile facility NS
Other <0.001
Unknown
Yes 0.004
Resident, long-
term care faci-
lity at
diagnosis Unknown
Long-term care
facility type Nursing home <0.01
Hospital-based NS
Residential <0.05
All other NS
Unknown
Total
Injecting drug
use (g) Yes <0.001
No
Unknown
Noninjecting drug
use (g) Yes <0.001
No
Unknown
Excessive alcohol
use (h) Yes <0.001
No
Unknown
Drug resis-
tance (i)
First-line drugs Yes <0.001
No
Not tested/unknown
Total
Second-line drugs Yes <0.00l
No
Not tested/unknown
Total
DOT Yes--total DOT <0.001
Yes--both DOT and self-
administered <0.001
No <0.001
Unknown
Within city limits Yes <0.001
No
Unknown
Previous diagnosis
of TB Yes <0.001
No
Unknown
Duration of
therapy (days) Mean NS
Median
Std. dev.
No.
(a) NTGSN, National Tuberculosis Genotyping Surveillance Network;TB,
tuberculosis; DOT, directly observed therapy; TST, tuberculin skin
test; Std. dev., standard deviation; NS, not significant (p>0.05).
(b) Subtotals for each category are listed if different from the total
case numbers.
(c) Probability of significant differences between U.S. TB patients and
all NTGSN surveillance patients (chi-square test; t-test for duration
of therapy); referent group is all other groups combined, excluding not
done or unknown categories, unless otherwise noted.
(d) Top 10 countries for foreign-born patients only.
(e) Excludes cases with extrapulmonary TB only.
(f) HIV cases from California are excluded because this site does not
report HIV results on Report of a Verified Case of Tuberculosis forms;
ages 15-44 years only.
(g) Injecting or noninjecting drug use within last year; includes use
of licensed, prescription, or illegal drugs (not prescribed by a
physician).
(h) Excessive use of alcohol within the past year as indicated by
participation in alcohol treatment programs, diagnosis of alcoholism,
or observation of intoxication during visits to health-care facilities.
(i) Drug resistance on initial testing of isolate. First-line drug
resistance is resistance to at least one of the following: isoniazid,
rifampin, ethambutol, or streptomycin. Second-line drug resistance is
resistance to one or more of the following: ethionamide, kanamycin,
cycloserine, capreomycin, para-amino salicylic acid, amikacin,
rifabutin, ciprofloxacin, ofloxacin, or other drugs. Testing results
for one or more of the drugs could have been missing.
Table 3. Comparison of demographic and behavioral risk factors and
clinical and treatment outcomes of tuberculosis (TB) case-patients who
have genetically clustered genotypes with factors and outcomes of
patients who had unique genotype patterns (a)
Variable (b) Clustered (%)
Total cases (n=10,752) 5.171 (48.1)
Gender Male 3,289 (63.6)
Female 1,881 (36.4)
Unknown 1 (0.0)
Mean age (yrs;
[+ or -] S.E.) 44.8 ([+ or -] 0.26)
Race/ethnicity White, non-Hispanic 1,018 (19.7)
Black, non-Hispanic 2,254 (43.6)
Hispanic 914 (17.7)
American Indian/
Native 17 (0.3)
Asian/Pacific
Islander 961 (18.6)
Unknown 7 (0.1)
Place of birth U.S.-born 3,331 (64.4)
Foreign-born 1,825 (35.3)
Unknown 15 (0.3)
Recent arrival in
United States (d) Yes 535 (29.3)
No 1,181 (64.7)
Unknown 109 (6.0)
Site of disease Pulmonary 3,902 (75.5)
Extrapulmonary 788 (15.2)
Pulmonary and
extrapulmonary 476 (9.2)
Unknown 5 (0.1)
Sputum smear Positive 2,270 (43.9)
Negative 1,802 (34.8)
Not done/unknown 1,099 (21.3)
Chest radiograph (e) Cavitary 1,345 (30.7)
Noncavitary 2,639 (60.2)
Normal 146 (3.3)
Not done/unknown 253 (5.8)
Total 4,383
HIV status (f) Positive 458 (22.2)
Negative 978 (47.4)
Indeterminate 0
Refused 106 (5.1)
Not offered 252 (12.2)
Unknown 270 (13.0)
Total 2,064
Homeless within past
year Yes 370 (7.2)
No 4,724 (91.4)
Unknown 77 (1.5)
Resident of correc-
tional facility at
diagnosis Yes 190 (3.7)
No 4,966 (96.0)
Unknown 15 (0.3)
Injecting drug use (g) Yes 312 (6.0)
No 4,540 (87.8)
Unknown 319 (6.2)
Noninjecting drug
use (g) Yes 460 (8.9)
No 4,335 (83.8)
Unknown 376 (7.3)
Excessive alcohol
use (g) Yes 948 (18.3)
No 3,897 (75.4)
Unknown 326 (6.3)
First-line drugs (h) Yes 622 (12.1)
No 2,718 (53.0)
Not done 1,748 (34.1)
Unknown 45 (0.9
Total 5,133
Variable (b) Unclustered (%)
Total cases (n=10,752) 5,581(51.9)
Gender Male 3,107 (55.7)
Female 2,473 (44.3)
Unknown 1 (0.0)
Mean age (yrs;
[+ or -] S.E.) 49.4 ([+ or -] 0.28)
Race/ethnicity White, non-Hispanic 1,201 (21.5)
Black, non-Hispanic 1,237 (22.2)
Hispanic 1,112 (19.9)
American Indian/
Native 10 (0.2)
Asian/Pacific
Islander 2,014 (36.1)
Unknown 7 (0.1)
Place of birth U.S.-born 2,023 (36.2)
Foreign-born 3,552 (63.6)
Unknown 6 (0.1)
Recent arrival in
United States (d) Yes 1,225 (34.5)
No 2,111 (59.4)
Unknown 216 (6.1)
Site of disease Pulmonary 3,835 (68.7)
Extrapulmonary 1,254 (22.5)
Pulmonary and
extrapulmonary 492 (8.8)
Unknown 0
Sputum smear Positive 2,011 (36.0)
Negative 1,943 (34.8)
Not done/unknown 1,627 (29.1)
Chest radiograph (e) Cavitary 1,172 (27.1)
Noncavitary 2,826 (65.3)
Normal 118 (2.73)
Not done/unknown 211 (4.9)
Total 4,327
HIV status (f) Positive 223 (11.8)
Negative 847 (44.8)
Indeterminate 4 (0.2)
Refused 138 (7.3)
Not offered 354 (18.7)
Unknown 323 (17.1)
Total 1,889
Homeless within past
year Yes 139 (2.5)
No 5,370 (96.2)
Unknown 72 (1.3)
Resident of correc-
tional facility at
diagnosis Yes 69 (1.2)
No 5,503 (98.6)
Unknown 9 (0.2)
Injecting drug use (g) Yes 72 (1.3)
No 5,231 (93.7)
Unknown 278 (5.0)
Noninjecting drug
use (g) Yes 140 (2.5)
No 5,140 (92.1)
Unknown 301 (5.4)
Excessive alcohol
use (g) Yes 371 (6.6)
No 4,893 (87.7)
Unknown 317 (5.7)
First-line drugs (h) Yes 755 (13.7)
No 3,337 (60.5)
Not done 1,356 (24.6)
Unknown 66 (1.2)
Total 5,514
Variable (b) Relative risk (95% CI)
Total cases (n=10,752)
Gender Male 1.19 (1.14% to 1.24%)
Female
Unknown
Mean age (yrs;
[+ or -] S.E.)
Race/ethnicity White, non-Hispanic 0.94 (0.90% to 0.99%)
Black, non-Hispanic 1.61 (1.55% to 1.67%)
Hispanic 0.92 (0.88% to 0.97%)
American Indian/
Native
Asian/Pacific
Islander 0.60 (0.56% to 0.63%)
Unknown
Place of birth U.S.-born 1.83 (1.75% to 1.90%)
Foreign-born
Unknown
Recent arrival in
United States (d) Yes 0.59 (0.55% to 0.63%)
No
Unknown
Site of disease Pulmonary 1.20 (1.14% to 1.26%)
Extrapulmonary 0.77 (0.72% to 0.81%)
Pulmonary and
extrapulmonary
Unknown
Sputum smear Positive 1.22 (1.11% to 1.33%)
Negative
Not done/unknown
Chest radiograph (e) Cavitary 1.09 (1.04% to 1.14%)
Noncavitary
Normal
Not done/unknown
Total
HIV status (f) Positive 1.37 (1.29% to 1.46%)
Negative
Indeterminate
Refused
Not offered
Unknown
Total
Homeless within past
year Yes 1.55 (1.46% to 1.64%)
No
Unknown
Resident of correc-
tional facility at
diagnosis Yes 1.55 (1.43% to 1.67%)
No
Unknown
Injecting drug use (g) Yes 1.73 (1.65% to 1.83%)
No
Unknown
Noninjecting drug
use (g) Yes 1.65 (l.57% to 1.73%)
No
Unknown
Excessive alcohol
use (g) Yes 1.61 (1.54% to 1.67%)
No
Unknown
First-line drugs (h) Yes 0.93 (0.87% to 0.99%)
No
Not done
Unknown
Total
Variable (b) Probability (c)
Total cases (n=10,752)
Gender Male <0.001
Female
Unknown
Mean age (yrs;
[+ or -] S.E.) <0.0001
Race/ethnicity White, non-Hispanic 0.02
Black, non-Hispanic <0.001
Hispanic 0.003
American Indian/
Native
Asian/Pacific
Islander <0.001
Unknown
Place of birth U.S.-born <0.001
Foreign-born
Unknown
Recent arrival in
United States (d) Yes <0.001
No
Unknown
Site of disease Pulmonary <0.001
Extrapulmonary <0.001
Pulmonary and
extrapulmonary NS
Unknown
Sputum smear Positive <0.001
Negative
Not done/unknown
Chest radiograph (e) Cavitary <0.001
Noncavitary
Normal
Not done/unknown
Total
HIV status (f) Positive <0.001
Negative NS
Indeterminate
Refused
Not offered
Unknown
Total
Homeless within past
year Yes <0.001
No
Unknown
Resident of correc-
tional facility at
diagnosis Yes <0.001
No
Unknown
Injecting drug use (g) Yes <0.001
No
Unknown
Noninjecting drug
use (g) Yes <0.001
No
Unknown
Excessive alcohol
use (g) Yes <0.001
No
Unknown
First-line drugs (h) Yes 0.016
No
Not done
Unknown
Total
(a) CI, confidence interval; S.E., standard error.
(b) Only factors that had significant differences are shown.
(c) Probability of chi-square statistic is shown, except for t-test
results from analysis of age from each group.
(d) Foreign-born only; arrived in the United States within 2 years.
(e) Excludes cases with extrapulmonary TB only.
(f) California TB cases not included; ages 15-44 years only.
(g) Excessive drug or alcohol use within last year.
(h) First-line drug resistance is resistance to at least one of the
following: isoniazid, rifampin, ethambutol, or streptomycin.
Second-line drug resistance is resistance to one or more of the
following: ethionamide, kanamycin, cycloserine, capreomycin, para-amino
salicylic acid, amikacin, rifabutin, ciprofloxacin, ofloxacin, or other
drugs. Testing results for one or more of the drugs could have been
missing.
Table 4 Odds ratios from best-fit logistic regression analyses of the
presence or absence of a specific genetic cluster of Mycobacterium
tuberculosis on demographic, clinical, behavioral, or treatment outcome
variables (a)
Designation (c) IS61110 copies Spoligotype (c) N
00003 (c) 1 777777777760771 40
00129 (d) 1 777777777413771 25
00129 (d) 1 777777774413771 83
00129 (d) 1 477777777413071 23
00129 (d) 1 777777777413731 13
00129 1 777776407760601 40
00016 2 701776777760601 129
00016 (c) 2 777776777760771 82
00016 2 037776777760601 30
00016 (d) 2 777776777760601 175
00370 3 700036777760731 13
00017 (d) 4 700076777760771 25
00017 (d) 4 777776777760771 64
01285 4 777776777760771 20
00015 7 28
00768 9 19
00242 (d) 10 95
00028 11 70
00159 11 24
00325 11 20
00673 11 25
00757 11 16
00019 (c) 12 27
00372 12 20
00035 13 33
00867 14 20
01284 17 46
00237 (c) 21 98
01693 21 29
00027 22 78
Odds ratio estimates
Designation (c) Main effect (95% CI) (b)
00003 (c) Asian/Pacific Islander 3.70 (1.51% to 9.02%)
Age 0.98 (0.96% to 0.99%)
Foreign-born 12.4 (3.83% to 39.9%)
00129 (d) Asian/Pacific Islander 73.3 (17.0% to 315.6%)
Extrapulmonary
infection 2.57 (1.10% to 6.03%)
00129 (d) Asian/Pacific Islander 282.8 (88.06% to 908.11%)
00129 (d) Asian/Pacific Islander 6.34 (1.52% to 26.44%)
Foreign-born 10.4 (1.55% to 70.12%)
00129 (d) Asian/Pacific Islander 13.88 (3.71% to 51.92%)
Resistance to first-
line drugs (d) 3.80 (1.22% to 11.86%)
00129 Female 2.73 (1.43% to 5.23%)
Black, non-Hispanic 3.57 (1.47% to 8.68%)
Injecting drug use 3.81 (1.81% to 8.03%)
00016 Male 0.58 (0.40% to 0.84%)
Black, non-Hispanic 10.88 (5.48% to 21.6%)
00016 (c) Hispanic 16.36 (10.15% to 26.37%)
00016 Age 1.03 (1.01% to 1.05%)
Black, non-Hispanic 7.13 (2.36% to 21.53%)
Resident, long-term
care facility 3.67 (1.17% to 11.70%)
00016 (d) U.S.-born 3.12 (1.85% to 5.26%)
Excessive alcohol use 0.55 (0.37% to 0.83%)
00370 White, non-Hispanic 5.20 (1.52% to 17.79%)
HIV positive 5.87 (1.69% to 20.41%)
Noninjecting drug use 3.74 (1.17% to 12.01%)
00017 (d) Hispanic 4.97 (2.16% to 11.44%)
00017 (d) Hispanic 15.7 (9.24% to 26.71%)
01285 Resident, correctional
facility 8.23 (3.08% to 22.01%)
00015 Black, non-Hispanic 7.04 (1.64% to 30.3%)
Injecting drug use 4.84 (2.11% to 11.09%)
Excessive alcohol use 2.28 (1.02% to 5.13%)
00768 Black, non-Hispanic 11.68 (1.54% to 88.87%)
Noninjecting drug use 2.77 (1.11% to 6.92%)
00242 (d) Male 2.12 (1.27% to 3.56%)
Age 0.97 (0.96% to 0.98%)
U.S.-born 8.44 (2.63% to 27.09%)
Homeless 3.60 (2.16% to 5.98%)
Noninjecting drug use 0.46 (0.24% to 0.90%)
00028 Black, non-Hispanic 17.57 (5.50% to 56.12%)
00159 Excessive alcohol use 2.76 (1.23% to 6.22%)
00325 Age 1.03 (1.01% to 1.06%)
Excessive alcohol use 3.08 (1.22% to 7.70%)
00673 Asian/Pacific Islander 84.6 (19.85 to 361.9%)
00757 Age 0.90 (0.85% to 0.94%)
HIV positive 4.86 (1.60% to 14.79%)
00019 (c) Male 3.68 (1.10% to 12.39%)
White, non-Hispanic 5.4 (2.35% to 11.08%)
00372 Homeless 6.09 (2.43% to 15.20%)
Resident, long-term
care facility 5.52 (1.535 to 20.0%)
00035 Black, non-Hispanic 6.96 (2.3% to 21.0%)
Resistance to second-
line drugs (e) 40.59 (16.5% to 99.85%)
00867 Black, non-Hispanic 11.68 (1.54% to 88.87%)
Noninjecting drug use 2.77 (1.11% to 6.92%)
01284 Black, non-Hispanic 2.40 (1.22% to 3.57%)
Pulmonary disease 0.92 (-0.01% to 1.86%)
00237 (c) White, non-Hispanic 2.80 (1.81% to 4.33%)
Excessive alcohol use 2.09 (1.36% to 3.22%)
01693 HIV positive 3.16 (1.39% to 7.18%)
Injecting drug use 3.08 (1.26% to 7.56%)
Extrapulmonary disease 3.99 (1.69, 9.42)
00027 Black, non-Hispanic 1.74 (1.05% to 2.90%)
Sputum-smear positive 3.07 (1.75% to 5.39%)
Designation (c) Wald p (b)
00003 (c) 0.004
0.017
<0.0001
00129 (d) <0.0001
0.03
00129 (d) <0.0001
00129 (d) 0.01
0.02
00129 (d) <0.0001
0.02
00129 0.0025
0.005
0.0004
00016 0.004
0.006
00016 (c) <0.0001
00016 0.006
0.0005
0.026
00016 (d) <0.0001
0.0048
00370 0.0087
0.005
0.03
00017 (d) 0.0002
00017 (d) <0.0001
01285 <0.0001
00015 0.0087
0.0002
0.05
00768 0.02
0.03
00242 (d) 0.004
<0.0001
0.0003
<0.0001
0.02
00028 <0.0001
00159 0.01
00325 0.01
0.02
00673 <0.0001
00757 <0.0001
0.005
00019 (c) 0.03
<0.0001
00372 0.0001
0.009
00035 0.0006
<0.0001
00867 0.02
0.03
01284 <0.0001
0.054
00237 (c) <0.0001
0.0007
01693 0.006
0.014
0.002
00027 0.03
<0.0001
(a) CI, confidence interval.
(b) Only genetic clusters that had [greater than or equal to] 20
isolates were included in the analysis; some samples sizes are <20
because of missing data among independent variables (Wald 95%
confidence intervals given in parentheses). Only genetic clusters with
significant predictors are listed. Age was modeled as a continuous
variable.
(c) The National Tuberculosis Genotyping Surveillance Network (NTGSN)
designation for the IS6110 RFLP pattern is represented; spoligotype
octal code designations are presented only for those genetic clusters
from isolates that had [less than or equal to] 6 copies of IS6110. RFLP
patterns and spoligotypes are detailed elsewhere (11).
(d) isolates observed in [greater than or equal to] 4 sites over 5
years.
(e) First-line drug resistance is resistance to at least one of the
following: isoniazid, rifampin, ethambutol, or streptomycin. S
econd-line drug resistance is resistance to one or more of the
following: ethionamide, kanamycin, cycloserine, capreomycin, para-amino
salicylic acid, amikacin, rifabutin, ciprofloxacin, ofloxacin, or other
drugs.
Acknowledgments We thank Ida Onorato, Ken Castro, Tom Shinnick, and Thomas Navin for their scientific guidance and logistic support; Elsa Villarino and James Mills for valuable comments on an earlier version of the manuscript; Annie Faye Prescott for excellent editorial assistance; and the health officials at local and state TB control offices that supported the activities of the National Tuberculosis Genotyping and Surveillance Network. References (1.) Foxman B, Riley L. Molecular epidemiology: focus on infection. Am J Epidemiol 2001;153:113541. (2.) van Soolingen D. Molecular epidemiology of tuberculosis and other mycobacterial infections: main methodologies and achievements. J Intern Med 2001;249:1-26. (3.) van Embden JD, van Soolingen D, Small PM, Hermans PW. Genetic markers for the epidemiology of tuberculosis. Res Microbiol 1992;143:385-91. (4.) Fletcher HA. Molecular epidemiology of tuberculosis: recent developments and applications. Curt Opin Pulm Med 2001;7:154-9. (5.) 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Genewein A, Telenti A, Bernasconi C, Mordasini C, Weiss S, Maurer AM, et al. Molecular approach to identifying route of transmission of tuberculosis in the community. Lancet 1993;342:841-4. (25.) Park YK, Bai GH, Kim SJ. Restriction fragment length polymorphism analysis of Mycobacterium tuberculosis isolated from countries in the western pacific region. J Clin Microbiol 2000;38:191-7. (26.) Bifani PJ, Plikaytis BB, Kapur V, Stockbauer K, Pan X, Lutfey ML, et al. Origin and interstate spread of a New York City multidrug-resistant Mycobacterium tuberculosis clone family. JAMA 1996;275:452-7. (27.) Yang Z, Barnes PF, Chaves F, Eisenach Eisenach (ī`zənäkh), city (1994 pop. 42,580), Thuringia, central Germany. It is an industrial center and rail junction. Industries include tourism, the manufacture of machinery, metal and wood products, chemicals, and electrical goods. KD, Weis SE, Bates JH, et al. Diversity of DNA fingerprints of Mycobacterium tuberculosis isolates in the United States. J Clin Microbiol 1998;36:1003-7. (28.) Bauer J, Yang Z, Poulsen S, Andersen AB. Results from 5 years of nationwide DNA fingerprinting of Mycobacterium tuberculosis complex isolates in a country with a low incidence of M. tuberculosis infection. J Clin Microbiol 1998;36:305-8. (29.) Pfyffer GE, Strassle A, Rose N, Wirth R, Brandli O, Shang H. Transmission of tuberculosis in the metropolitan area of Zurich: a 3 year survey based on DNA fingerprinting. Eur Respir J 1998;11:804-8. (30.) de Boer AS, Borgdorff MW, de Haas PE, Nagelkerke NJ, van Embden JD, van Soolingen D. Analysis of rate of change of IS6110 RFLP patterns of Mycobacterium tuberculosis based on serial patient isolates. J Infect Dis 1999;180:123844. (31.) Warren RM, van der Spuy GD, Richardson M, Beyers N, Borgdorff MW, Behr MA, et al. Calculation of the stability of the IS6110 banding pattern in patients with persistent Mycobacterium tuberculosis disease. J Clin Microbiol 2002;40:1705-8. (32.) Niemann S, Rusch-Gerdes S, Richter E, Thielen H, Heykes-Uden H, Diel R. Stability of IS6110 restriction fragment length polymorphism patterns of Mycobacterium tuberculosis strains in actual chains of transmission. J Clin Microbiol 2000;38:2563-7. (33.) Murray M, Alland D. Methodological problems in the molecular epidemiology of tuberculosis. Am J Epidemiol 2002;155:565-71. Barbara A. Ellis, * Jack T. Crawford, * Christopher R. Braden, * Scott J. N. McNabb, * Marisa Moore, * Steve Kammerer, * and the National Tuberculosis Genotyping and Surveillance Network Work Group (1) * Centers for Disease Control and Prevention, Atlanta, Georgia, USA (1) Members of the National Tuberculosis Genotyping and surveillance Network Work Group, in addition to the listed authors, included Joseph Bates, William Benjamin, Pablo Bifani, M. Donald Cave, Rebecca Cox, Wendy Cronin, Ed Desmond, Jeffrey Driscoll, Nancy Dunlap, Jennifer Flood, Kashef Ijaz,, Michael Kucab, Barry Kreiswirth, Zary Liu, D. Mitchell Magee, Jeffrey Massey, Ann Miller, Donna Mulcahy, Robert Pratt, Teresa Quitugua, Barbara Schable, Kenneth Shilkret, Harry Taber, Jeffrey Taylor, Sharon Sharnprapai, Sumi Sun, Zhenhua Yang Dr. Ellis is a senior microbiologist with the National Center for Infectious Diseases, Centers for Disease Control and Prevention. Her research interests focus on the molecular epidemiology of infectious diseases, rodent-borne zoonotic diseases, and bioterrorism preparedness. Her work has included disease ecology studies of rodent-borne hemorrhagic fever viruses, molecular characterization of novel bartonellae, and molecular epidemiologic studies of Mycobacterium tuberculosis. Address for correspondence: Barbara Ellis, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Mailstop E79, Atlanta, GA 30333, USA; fax: 404-498-2270; e-mail: bae7@cdc.gov |
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