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Journal of Clinical Microbiology logoLink to Journal of Clinical Microbiology
. 2008 Oct 8;46(12):3924–3930. doi: 10.1128/JCM.00793-08

Transmission Classification Model To Determine Place and Time of Infection of Tuberculosis Cases in an Urban Area

G de Vries 1,2,*, H W M Baars 1, M M G G Šebek 3,4, N A H van Hest 1, J H Richardus 2,5
PMCID: PMC2593293  PMID: 18842933

Abstract

We conducted a population-based study in the Rotterdam region of The Netherlands to determine the place and time of infection of tuberculosis (TB) cases using conventional epidemiological and genotyping information. In particular, we focused on the extent of misclassification if genotyping was not combined with epidemiological information. Cases were divided into those with a unique mycobacterial DNA fingerprint, a clustering fingerprint, and an unknown fingerprint. We developed transmission classification trees for each category to determine whether patients were infected in a foreign country or recently (≤2 years) or remotely (>2 years) infected in The Netherlands. Of all TB cases during the 12-year study period, 38% were infected in a foreign country, 36% resulted from recent transmission in The Netherlands, and 18% resulted from remote infection in The Netherlands, while in the remaining cases (9%) either the time or place of infection could not be determined. The conventional epidemiological data suggested that at least 29% of clustered cases were not part of recent chains of transmission. Cases with unknown fingerprints, almost all culture negative, relatively frequently had confirmed epidemiological links with a recent pulmonary TB case in The Netherlands and were more often identified by contact tracing. Our findings highlight the idea that genotyping should be combined with conventional epidemiological investigation to establish the place and time of infection of TB cases as accurately as possible. A standardized way of classifying TB into recently, remotely, and foreign-acquired disease provides indicators for surveillance and TB control program performance that can be used to decide on interventions and allocation of resources.


The steady decline of tuberculosis (TB) incidence, especially since the introduction of chemotherapy in the 1950s, was reversed in the late 1980s in many developed countries due to immigration, concurrent human immunodeficiency virus (HIV) infections, and inadequate TB control practices (16). In the last 10 years, however, the general downward trend has resumed in many of these countries, necessitating review of current TB control strategies. Several countries where the incidence of TB is low are currently developing TB elimination plans in order to reach the goal of less than 1 case per million population per year (5, 22).

For TB control, it is relevant to know where and when patients were infected, because recently infected patients represent ongoing transmission, those with remotely acquired infection are a result of TB transmission in the past, and patients infected in a foreign country are an expression of the particular TB situation in that country. The absolute TB incidence and the relative contributions of recently, remotely, and foreign-acquired disease influence the choice of TB control strategies (1, 14, 15). The proportion of recent transmission is also an important indicator for surveillance and TB control program performance (25, 27).

DNA fingerprinting of Mycobacterium tuberculosis isolates provides a tool to disentangle the different transmission pathways (12, 15, 26). The percentage of clustered cases in an area indicates the amount of recent transmission in a community, but clustering is not identical with recent transmission (4, 18, 30). Furthermore, fingerprinting studies alone ignore culture-negative cases, although their contribution to the TB caseload and to recent transmission may be substantial. Thus, a combined use of conventional epidemiological and genotyping data will ascertain more accurately where and when patients were infected (17, 25, 27). A standardized way of classifying transmission will help to monitor and compare TB control programs.

We developed and applied a transmission classification model to determine the place and time of infection of all TB cases in a highly urbanized area by using information from conventional epidemiological investigation and molecular typing. In addition, we assessed the extent of misclassification for cases with a DNA fingerprint if genotyping was not combined with epidemiological information.

MATERIALS AND METHODS

Study area and study population.

The study was conducted in a highly urbanized area with 1.9 million inhabitants in the southern part of the province of South-Holland, The Netherlands. Reported cases diagnosed between 1 January 1995 and 31 December 2006 were included in the study, excluding 41 sailors with a residential address outside The Netherlands and 12 inmates of a deportation center for illegal immigrants transferred from other regions of the country. M. tuberculosis complex strains were identified by using an Accuprobe culture confirmation test (Genprobe, Inc., San Diego, CA) or, since January 2004, with a GenoType MTBC assay (Hain Lifescience GmbH, Nehren, Germany). Species within the M. tuberculosis complex were distinguished by a combination of biochemical tests and DNA fingerprint methods, as described in detail by van Klingeren et al. (34). Mycobacterium africanum isolates were not distinguished from M. tuberculosis and are therefore included among the isolates identified as M. tuberculosis. All 34 patients infected with Mycobacterium bovis, the 2 patients with Mycobacterium canettii strains, and the single patient with Mycobacterium bovis bacillus Calmette-Guérin were excluded from our study. In culture-negative cases, diagnosis was based upon clinical, radiographic, histopathological, and/or epidemiological grounds.

The national TB disease register provided data for reported cases after approval by its data protection committee. Cases that resulted from laboratory cross-contamination had been withdrawn from the register. The data were completed and validated using local registers, patient records, and the DNA fingerprinting register of the National Mycobacteria Reference Laboratory. The Medical Ethics Committee of Erasmus MC, University Medical Center Rotterdam, Rotterdam, approved the study protocol.

Recurrent TB was defined as disease reoccurring more than 1 year after the start of a previous episode. Twenty-five patients had two episodes during the study period, all with a culture-confirmed first episode. Of these recurrent cases, 14 were considered relapses, because 6 were not bacteriologically confirmed in the second episode, 7 had the same fingerprint as the first episode and their clusters had no pulmonary case since the first episode, and in 1 case, the M. tuberculosis isolate was erroneously not forwarded for restriction fragment length polymorphism (RFLP) typing. These 14 second-episode cases were excluded from the study. The other 11 recurrent cases were considered reinfections and both episodes were included in the study. Five of these cases had different fingerprints in both episodes, and 6 had identical fingerprints, but these cases shared epidemiological features with 1 or more pulmonary TB cases that were added to the cluster since the first episode.

DNA fingerprints.

Since 1 January 1993, all M. tuberculosis isolates in The Netherlands have been subject to standardized IS6110-based RFLP typing, also called DNA fingerprinting (33). Clusters are defined as groups of patients having isolates with fully identical RFLP patterns or, if mycobacterial strains harbor fewer than 5 IS6110 copies, isolates with identical subtyping in assays using the polymorphic GC-rich sequence (PGRS) probe (35). The first case in each cluster was classified as unique. In one cluster, the first and second positions were changed because a 4-month-old child was the first case in the cluster but she was unquestionably infected by her mother, who was diagnosed with urogenital TB 2 months later (11).

Transmission classification model.

Cases were grouped into three main categories: (i) cases with a unique fingerprint, (ii) cases with a clustering fingerprint, and (iii) cases with an unknown DNA fingerprint. The category with unique fingerprints was subdivided into cases in immigrant and nonimmigrant patients. Transmission classification trees were developed for each category (see Table 1 and the supplemental material) and discussed during three consensus meetings with TB public health specialists.

TABLE 1.

Selected demographic and disease-related factors of 2,636 TB cases in the Rotterdam region, 1995 to 2006

Patient characteristic No. or % of TB cases with indicated type of fingerprint
Unique
Clustering
Unknown
No. % No. % No. %
Total no. 919 1,108 609
Male 485 52.8 738 66.6 322 52.9
Age (yr)
    0-14 15 1.6 32 2.9 109 17.9
    15-29 258 28.1 386 34.8 145 23.8
    30-44 276 30.0 400 36.1 157 25.8
    45-64 164 17.8 229 20.7 121 19.9
    ≥65 206 22.4 61 5.5 77 12.6
Born in The Netherlands 219 23.8 338 30.5 273 44.8
Previous history of TB 68 7.4 58 5.2 35 5.7
HIV infection 51 5.5 50 4.5 13 2.1
Illicit drug user or homeless person 25 2.7 157 14.2 19 3.1
Pulmonary TB 576 62.7 811 73.2 271 44.5
Active case found by contact investigation 11 1.2 107 9.7 121 19.9
Active case found by screening 99 10.8 108 9.7 57 9.4

The outcome of the classification process was, first of all, a likelihood scale of place of transmission, i.e., confirmed infected in a foreign country, probably infected in a foreign country, indeterminate, probably infected in The Netherlands, and confirmed infected in The Netherlands. The questions leading to this outcome were related to the date and time period of residence in The Netherlands for cases in immigrants; documented contact with a pulmonary TB case; documented history of frequent travel to countries where TB is endemic, i.e., more than 3 months cumulative during the 5 years prior to diagnosis; and the time difference with the last preceding pulmonary case in the cluster for clustered cases. In addition, the results of entrance screening were used to determine the most likely place of infection in immigrant patients without a DNA-fingerprinted isolate.

For patients infected in The Netherlands, the time of infection was classified as recently infected (≤2 years), remotely infected (>2 years), and unknown time of infection. Decisions were based on information routinely collected by TB public health nurses on the relationship between clustered cases and their assessment of whether an epidemiological link was confirmed, i.e., the patient knew a person in the cluster by name or was at the same place at the same time with a clustered pulmonary case, or the link was possible, i.e., the patient shared behavioral patterns (such as homelessness, illicit drug use, and pub visiting) with other patients in the cluster (23, 27). For confirmed epidemiologically linked clustered cases, the time difference between the dates of sample collection determined whether a secondary case had a recent or remote infection. Clustered cases without a confirmed epidemiological link were considered infected by the last preceding pulmonary case in the cluster. In cases without a fingerprint, decisions on the time of infection were based on a documented contact with a pulmonary TB case and a history of previous TB.

RESULTS

Table 1 shows selected demographic and disease characteristics of the 2,636 cases included in the analysis. Of the 2,027 cases (77%) with a known DNA fingerprint, 919 (45%) were unique, of which 135 were the first case in a national cluster and 1,108 (55%) were clustered cases which were not the first case. Of the 609 cases (23%) with an unknown DNA fingerprint, 13 were culture confirmed but not RFLP typed and 596 were culture negative.

Patients older than 64 years more often had an infection with a unique fingerprint rather than a clustering or unknown fingerprint, patients between 15 and 44 years old more frequently had an infection with a clustering fingerprint rather than a unique or unknown fingerprint, and patients less than 15 years old more often had an infection with an unknown fingerprint rather than a known fingerprint. Patients with clustered cases were more often male, illicit drug users, or homeless than patients with infections with a unique fingerprint. Patients with isolates with a known fingerprint had pulmonary TB or an HIV coinfection more frequently than patients with isolates with an unknown fingerprint, while patients with isolates with an unknown fingerprint were more frequently born in The Netherlands or were identified in a contact investigation.

Classification of place of transmission.

Epidemiological information suggested in 19 of 700 (3%) cases in immigrants with an isolate with a unique fingerprint that they were probably infected in The Netherlands (Table 2). Travel history suggested in 32 of 219 (15%) cases in nonimmigrants with an isolate with a unique fingerprint that they were probably infected in a foreign country. Sixty-two clustered cases were not preceded by a pulmonary case in the cluster (52 were the second, 8 the third, 1 the sixth, and 1 the seventh case in a cluster) and followed the classification tree for unique fingerprints. Altogether, 114 (10%) clustered cases were classified as infected in a foreign country, while the remaining 994 (90%) were probably or confirmed infected in The Netherlands. Of the cases with an unknown fingerprint, 318 (52%) were classified as probably or confirmed infected in The Netherlands and 221 (36%) as probably or confirmed infected in a foreign country, and for the remaining 70 (12%), no decision could be made on possible place of infection.

TABLE 2.

Classification of place and time period of transmission of TB cases in the Rotterdam region, 1995 to 2006

Criteriona Place of infection
Time of infection for patients infected in The Netherlandse
Infected in a foreign country
Indeterminateb Infected in The Netherlands
≤2 yrs >2 yrs Unknown
Confirmed Probably Probably Confirmed
Cases with a unique fingerprint (n = 919)
    Cases in immigrants (n = 700)
        Arrived in The Netherlands after 1/1/1993 376
        In residence before 1/1/1993 and had documented contact with PTB case in The Netherlands 18 1 1c 18
        In residence before 1/1/1993 and had documented history of frequent travel to countries where TB is endemic 79
        In residence before 1/1/1993 and lived more yrs in foreign country than in The Netherlands in the pregenotyping period 170
        In residence before 1/1/1993 without identified risks 56
    Cases in nonimmigrants (n = 219)
        Documented contact with PTB case in The Netherlands 39 1c 38
        Documented history of frequent travel to countries where TB is endemic 32
        No documented risks 148 148
Cases with a clustering fingerprint (n = 1,108)
    No preceding PTB in the clusterd (n = 62) 29 21 12 2c 10
    Diagnosis within 3 mo of arrival 32
    Not in residence in The Netherlands with a clustered TB case 32
    Cases with a confirmed epidemiological link 258 195 63
    Cases with a possible epidemiological link 190 185 5
    Cases without an established epidemiological link 534 401 133
Cases without a DNA fingerprint (n = 609)
    Documented contact with PTB case in The Netherlands 192 154 38
    Documented contact with PTB case in a foreign country 13
    Chest X-ray abnormalities or positive TST at entrance screening 43
    Cases in immigrants who lived more yrs in a foreign country than in The Netherlands 151
    Cases in immigrants without other documented risks 70
    Cases in nonimmigrants with documented history of frequent travel to countries where TB is endemic 14
    Cases of recurrent TB in nonimmigrants 13 13
    Cases in nonimmigrants without documented risks 113 113
Total (n = 2,636) 525 467 126 838 680 939 466 113
% 19.9 17.7 4.8 31.8 25.8 35.6 17.7 4.3
a

Dates are given as month/day/year. PTB, pulmonary tuberculosis; TST, tuberculin skin test.

b

Twenty-two of 56 and 21 of 70 cases had unknown dates of arrival in The Netherlands.

c

Patients were infected by a visiting person later diagnosed with infectious TB shortly after leaving The Netherlands.

d

These clustered cases without a preceding PTB were classified according to the trees for unique fingerprints.

e

The classification of time of infection for 994 clustered cases infected in The Netherlands, presented in boldface in this table, is explained in Fig. 1.

Classification of time of transmission for patients infected in The Netherlands.

All cases with a unique fingerprint with a probable or confirmed infection in The Netherlands were classified as remotely infected in The Netherlands, with the exception of two patients who had a documented contact with a visiting person diagnosed with pulmonary TB shortly after leaving The Netherlands (Table 2). Figure 1 shows the classification of time of infection for clustered cases infected in The Netherlands, indicated in Table 2 by boldface. Of these 994 cases, 369 patients (2 + 256 + 111) (37%) were confirmed to be recently infected, 414 (42%) were possibly recently infected, and 211 (10 + 160 + 41) (21%) were confirmed remotely infected. Of all cases with an unknown fingerprint, 154 (25%) were recently infected in The Netherlands. The majority of these cases (121 of 154) were identified by tracing contacts, while 33 cases had a documented contact with a recent pulmonary TB case in The Netherlands.

FIG. 1.

FIG. 1.

Classification of time of infection for clustered cases from the Rotterdam area that were probably or confirmed infected in The Netherlands, 1995 to 2006 (n = 994). PTB, pulmonary tuberculosis; EPI link, epidemiological link.

Epidemiological links.

An epidemiological link was confirmed in 260 (23%) clustered cases, with 197 patients being recently infected and 63 remotely infected. In 190 (17%) clustered cases an epidemiological link was likely, because these patients shared the same behavioral characteristics. The other cases did not fulfill our criteria for a confirmed or possible epidemiological link, although patients often had a similar ethnic background and lived in the same geographical area. Epidemiological links were significantly more frequently confirmed in RFLP clusters with at least 5 bands (254 of 1,031; 25%) than in low-copy-number RFLP clusters which required additional PGRS typing (6 of 77; 8%) (P value of <0.01). Cases with an unknown fingerprint (154 of 609; 25%) had a confirmed recent epidemiological link more often than cases with a clustering strain (197 of 1,108; 18%) (P value of <0.01).

Table 2 summarizes data showing that of all culture-confirmed and culture-negative TB cases, 38% were probably or confirmed infected in a foreign country, 36% were probably or confirmed recently infected in The Netherlands, and 18% were probably or confirmed remotely infected in The Netherlands. In 4% of all cases, a decision on the time of infection in The Netherlands could not be reached, while in 5% of all cases, both the place and time of infection remained indeterminate in the classification process.

Cluster size.

The 1,243 clustering bacteria strains, including 135 cases which were the first case in a national cluster, were part of 452 national clusters. The cases in the study contributed with 1 case to 263 national clusters, with 2 cases to 98 clusters, with 3 to 10 cases to 74 clusters, and with more than 10 cases to 17 clusters. The largest cluster in The Netherlands, with 160 cases nationwide, contained 132 cases from the study area. The proportion of clustered cases recently infected in The Netherlands increased with the sequential number in a cluster (Table 3). Thirty-eight percent of cases that had the second rank in a cluster were recently infected in The Netherlands, while this proportion increased to more than 75% when the person was more than the 10th case in a cluster.

TABLE 3.

Contribution to cluster size in The Netherlands of clustered cases from the Rotterdam region that were not the first in the cluster and their classification of transmission, 1995 to 2006

Patient's sequential no. in national clusters Total no. of regional cases No. (%) of patients that were:
Infected in a foreign country Recently infected in The Netherlands Remotely infected in The Netherlands
2 184 55 (29.9) 70 (38.0) 59 (32.1)
3 98 18 (18.4) 49 (50.0) 31 (31.6)
4-5 121 10 (8.3) 76 (62.8) 35 (28.9)
6-10 195 18 (9.2) 144 (73.8) 33 (16.9)
11-20 168 8 (4.8) 130 (77.4) 30 (17.9)
21-50 197 4 (2.0) 178 (90.4) 15 (7.6)
≥51 145 1 (0.7) 135 (93.8) 8 (5.5)
Total 1,108 114 (10.3) 783 (70.7) 211 (19.0)

DISCUSSION

We used classification trees and combined molecular and conventional epidemiological data to ascertain the place and time of infection of all TB cases in our study population. Although most studies divide transmission into recent and remote infections, we added a separate category of infections acquired in a foreign country and limited the recent and remote categories to those infections acquired in The Netherlands. Of all TB cases during the 12-year study period, 38% were infected in a foreign country, 36% resulted from recent transmission in The Netherlands, and 18% resulted from remote infections in The Netherlands, while in the remaining cases (9%), either the time or place of infection could not be determined. The conventional epidemiological data suggested that at least 29% of clustered cases were not recently infected in The Netherlands. Cases with unknown fingerprints, almost all culture negative, relatively frequently had confirmed epidemiological links with a pulmonary TB case and were more often identified by contact tracing and, therefore, presumably were recently infected in The Netherlands.

Molecular studies often use the n − 1 method, in which the first case in a cluster is considered unique (18, 29). The proportion of clustering, however, strongly depends on the time period of the study, the geographical area, and the proportion of cases included in a fingerprinting program (17, 18). In The Netherlands, genotyping has been performed for nearly all M. tuberculosis isolates for 14 years and clustering is confined to the national borders. If we had restricted the n − 1 method to the Rotterdam study region, 452 instead of 135 cases that were the first in a cluster would be considered unique and the clustering proportion would decrease from 55 to 39%, which underscores the influence of the geographical area on clustering.

In most studies, recently transmitted TB is defined as disease occurring within 2 years of infection (1, 8, 9, 31), although some studies have limited the latency period to 1 year (6, 15, 21) or extended it to 5 years after infection (36). There is a need to decide on the latency period of recent disease development so that outcomes, such as program performances, can be compared. We propose to use the 2-year latency period, as applied in our study.

Cases with unique strains are rarely the result of recent transmission in a country if universal genotyping has been applied for more than 2 years. There are some rare exceptions that we also encountered, such as transmission by a visiting person who is diagnosed with TB after leaving the country. Recently transmitted bacteria may also be reported as unique strains if the M. tuberculosis genotype has changed over time (25). The half-life of RFLP genotypes is unclear but has been estimated to vary between 3 and 10 years in certain situations (10, 37). In our study, five initially unique fingerprints of epidemiologically linked cases were reinvestigated by the National Mycobacteria Reference Laboratory and showed a 1-band difference with the expected clusters, and these strains were therefore placed in the respective RFLP clusters. We recommend that fingerprinting programs should assess epidemiological links if RFLP patterns differ by 1 band, to identify these molecular changes.

In our study, 71% (783 of 1,108) of clustered cases were confirmed or possibly recently infected in The Netherlands, 211 (19%) were remotely infected in The Netherlands, and 114 (10%) were infected in a foreign country. The proportion of clustered cases due to recent transmission in our study is an overestimation because all cases without known epidemiological links and with a preceding pulmonary case in the cluster within 2 years were classified as recently infected in The Netherlands. In particular in circumstances of high transmission with large clusters, it is more difficult to ascertain the source case and time of infection (24).

The results of our study also showed that patients with low rank numbers in their clusters were frequently infected in a foreign country or remotely infected in The Netherlands. There are basically three explanations for clustered cases not representing recent transmission (4, 12, 20). Immigrant patients may have been infected in their countries of origin with a genetically homogenous strain also present in the national fingerprinting database. Nonimmigrant patients may have been infected several years or decades before with a strain circulating at that time in the country under study. And last, RFLP typing may be unable to differentiate two nonidentical strains. We recommend that additional genotyping, such as direct repeat sequence or mycobacterial interspersed repetitive units and variable-number tandem repeat analysis, is considered if epidemiological links are not confirmed in small-sized clusters, as was done in other studies (19, 32). Cases in PGRS clusters with low-copy-number RFLP strains had a relatively low percentage of confirmed epidemiological links in our study, confirming the lack of discriminatory power of additional PGRS typing (2, 28).

In most developed countries, the diagnosis of TB is confirmed by culture in 80% of all cases at the most (7, 13). Thus, transmission studies that rely exclusively on genotyping overlook the contribution of culture-negative cases to recent transmission. In our study, cases without a fingerprint had a confirmed recent epidemiological link significantly more often than cases with a clustering strain, indicating the importance of culture-negative TB as a result of recent transmission.

In our classification model, we used a number of questions leading to decisions of place and time of infection with a certain probability. Positive answers to questions about recent residence in The Netherlands in cases with a unique fingerprint and documented contact with a pulmonary TB case clearly provide stronger evidence for the outcome than, e.g., questions about frequent travel to countries where TB is endemic. We applied the questions stepwise, and in this way, we believe that we have made optimal use of relevant and available information. In the future, with improved interviewing skills of TB public health nurses and the use of a more-systematic approach to investigate and confirm links between cases, classification can become more accurate. Furthermore, the model should be evaluated in other transmission settings to assess its application in these circumstances.

Our findings underline the consensus that clustering should not be considered identical with recent transmission and that genotyping should be combined with conventional epidemiological investigation. A standardized way of classifying TB into recently, remotely, and foreign-acquired disease provides indicators for surveillance and program performance that can be used to decide on interventions and allocate resources. Programs with predominately recent transmission may focus on a package of targeted activities for active case finding, while those with a high proportion of imported strains should consider screening for TB and latent TB infection in immigrants and those with mainly reactivated cases can shift attention to the elimination of TB.

Supplementary Material

[Supplemental material]

Acknowledgments

This study is part of the work of the Huisman Research Center, which is a collaboration between the Erasmus MC Rotterdam and the Municipal Public Health Service Rotterdam-Rijnmond for research in the field of infectious diseases and public health.

The study was partially funded by a grant from the KNCV Tuberculosis Foundation.

Footnotes

Published ahead of print on 8 October 2008.

Supplemental material for this article may be found at http://jcm.asm.org/.

REFERENCES

  • 1.Alland, D., G. E. Kalkut, A. R. Moss, R. A. McAdam, J. A. Hahn, W. Bosworth, E. Drucker, and B. R. Bloom. 1994. Transmission of tuberculosis in New York City. An analysis by DNA fingerprinting and conventional epidemiologic methods. N. Engl. J. Med. 3301710-1716. [DOI] [PubMed] [Google Scholar]
  • 2.Behr, M. A., and P. M. Small. 1997. Molecular fingerprinting of Mycobacterium tuberculosis: how can it help the clinician? Clin. Infect. Dis. 25806-810. [DOI] [PubMed] [Google Scholar]
  • 3.Reference deleted.
  • 4.Braden, C. R., G. I. Templeton, M. D. Cave, S. Valway, I. M. Onorato, K. G. Castro, D. Moers, Z. Yang, W. W. Stead, and J. H. Bates. 1997. Interpretation of restriction fragment length polymorphism analysis of Mycobacterium tuberculosis isolates from a state with a large rural population. J. Infect. Dis. 1751446-1452. [DOI] [PubMed] [Google Scholar]
  • 5.Broekmans, J. F., G. B. Migliori, H. L. Rieder, J. Lees, P. Ruutu, R. Loddenkemper, and M. C. Raviglione. 2002. European framework for tuberculosis control and elimination in countries with a low incidence. Recommendations of the World Health Organization (WHO), International Union Against Tuberculosis and Lung Disease (IUATLD) and Royal Netherlands Tuberculosis Association (KNCV) Working Group. Eur. Respir. J. 19765-775. [DOI] [PubMed] [Google Scholar]
  • 6.Cattamanchi, A., P. C. Hopewell, L. C. Gonzalez, D. H. Osmond, L. Masae Kawamura, C. L. Daley, and R. M. Jasmer. 2006. A 13-year molecular epidemiological analysis of tuberculosis in San Francisco. Int. J. Tuberc. Lung Dis. 10297-304. [PubMed] [Google Scholar]
  • 7.Centers for Disease Control and Prevention. 2007. Reported tuberculosis in the United States, 2006. U.S. Department of Health and Human Services, CDC, Atlanta, GA.
  • 8.Chin, D. P., C. M. Crane, M. Y. Diul, S. J. Sun, R. Agraz, S. Taylor, E. Desmond, and F. Wise. 2000. Spread of Mycobacterium tuberculosis in a community implementing recommended elements of tuberculosis control. JAMA 2832968-2974. [DOI] [PubMed] [Google Scholar]
  • 9.Cronin, W. A., J. E. Golub, M. J. Lathan, L. N. Mukasa, N. Hooper, J. H. Razeq, N. G. Baruch, D. Mulcahy, W. H. Benjamin, L. S. Magder, G. T. Strickland, and W. R. Bishai. 2002. Molecular epidemiology of tuberculosis in a low- to moderate-incidence state: are contact investigations enough? Emerg. Infect. Dis. 81271-1279. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.de Boer, A. S., M. W. Borgdorff, P. E. de Haas, N. J. Nagelkerke, J. D. van Embden, and D. van Soolingen. 1999. Analysis of rate of change of IS6110 RFLP patterns of Mycobacterium tuberculosis based on serial patient isolates. J. Infect. Dis. 1801238-1244. [DOI] [PubMed] [Google Scholar]
  • 11.de Steenwinkel, J. E., G. J. Driessen, M. H. Kamphorst-Roemer, A. G. Zeegers, A. Ott, and M. van Westreenen. 2008. Tuberculosis mimicking ileocecal intussusception in a 5-month-old girl. Pediatrics 1211434-1437. [DOI] [PubMed] [Google Scholar]
  • 12.Diel, R., S. Schneider, K. Meywald-Walter, C. M. Ruf, S. Rusch-Gerdes, and S. Niemann. 2002. Epidemiology of tuberculosis in Hamburg, Germany: long-term population-based analysis applying classical and molecular epidemiological techniques. J. Clin. Microbiol. 40532-539. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.EuroTB, et al. 2007. Surveillance of tuberculosis in Europe: report on tuberculosis cases notified in 2005. Institut de veille sanitaire, Saint-Maurice, France.
  • 14.Foxman, B., and L. Riley. 2001. Molecular epidemiology: focus on infection. Am. J. Epidemiol. 1531135-1141. [DOI] [PubMed] [Google Scholar]
  • 15.France, A. M., M. D. Cave, J. H. Bates, B. Foxman, T. Chu, and Z. Yang. 2007. What's driving the decline in tuberculosis in Arkansas? A molecular epidemiologic analysis of tuberculosis trends in a rural, low-incidence population, 1997-2003. Am. J. Epidemiol. 166662-671. [DOI] [PubMed] [Google Scholar]
  • 16.Frieden, T. R., P. I. Fujiwara, R. M. Washko, and M. A. Hamburg. 1995. Tuberculosis in New York City: turning the tide. N. Engl. J. Med. 333229-233. [DOI] [PubMed] [Google Scholar]
  • 17.Glynn, J. R., J. Bauer, A. S. de Boer, M. W. Borgdorff, P. E. Fine, P. Godfrey-Faussett, and E. Vynnycky. 1999. Interpreting DNA fingerprint clusters of Mycobacterium tuberculosis. European Concerted Action on Molecular Epidemiology and Control of Tuberculosis. Int. J. Tuberc. Lung Dis. 31055-1060. [PubMed] [Google Scholar]
  • 18.Glynn, J. R., E. Vynnycky, and P. E. Fine. 1999. Influence of sampling on estimates of clustering and recent transmission of Mycobacterium tuberculosis derived from DNA fingerprinting techniques. Am. J. Epidemiol. 149366-371. [DOI] [PubMed] [Google Scholar]
  • 19.Gutierrez, M. C., V. Vincent, D. Aubert, J. Bizet, O. Gaillot, L. Lebrun, C. Le Pendeven, M. P. Le Pennec, D. Mathieu, C. Offredo, B. Pangon, and C. Pierre-Audigier. 1998. Molecular fingerprinting of Mycobacterium tuberculosis and risk factors for tuberculosis transmission in Paris, France, and surrounding area. J. Clin. Microbiol. 36486-492. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Hermans, P. W., F. Messadi, H. Guebrexabher, D. van Soolingen, P. E. de Haas, H. Heersma, H. de Neeling, A. Ayoub, F. Portaels, D. Frommel, M. Zribi, and J. D. A. van Embden. 1995. Analysis of the population structure of Mycobacterium tuberculosis in Ethiopia, Tunisia, and The Netherlands: usefulness of DNA typing for global tuberculosis epidemiology. J. Infect. Dis. 1711504-1513. [DOI] [PubMed] [Google Scholar]
  • 21.Jasmer, R. M., J. A. Hahn, P. M. Small, C. L. Daley, M. A. Behr, A. R. Moss, J. M. Creasman, G. F. Schecter, E. A. Paz, and P. C. Hopewell. 1999. A molecular epidemiologic analysis of tuberculosis trends in San Francisco, 1991-1997. Ann. Intern. Med. 130971-978. [DOI] [PubMed] [Google Scholar]
  • 22.Jereb, J. A. 2002. Progressing toward tuberculosis elimination in low-incidence areas of the United States. Recommendations of the Advisory Council for the Elimination of Tuberculosis. MMWR Recommend. Rep. 511-14. [PubMed] [Google Scholar]
  • 23.Lambregts-van Weezenbeek, C. S., M. M. Sebek, P. J. van Gerven, G. de Vries, S. Verver, N. A. Kalisvaart, and D. van Soolingen. 2003. Tuberculosis contact investigation and DNA fingerprint surveillance in The Netherlands: 6 years’ experience with nation-wide cluster feedback and cluster monitoring. Int. J. Tuberc. Lung Dis. 7S463-S470. [PubMed] [Google Scholar]
  • 24.McNabb, S. J., C. R. Braden, and T. R. Navin. 2002. DNA fngerprinting of Mycobacterium tuberculosis: lessons learned and implications for the future. Emerg. Infect. Dis. 81314-1319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.McNabb, S. J., J. S. Kammerer, A. C. Hickey, C. R. Braden, N. Shang, L. S. Rosenblum, and T. R. Navin. 2004. Added epidemiologic value to tuberculosis prevention and control of the investigation of clustered genotypes of Mycobacterium tuberculosis isolates. Am. J. Epidemiol. 160589-597. [DOI] [PubMed] [Google Scholar]
  • 26.Murray, M., and D. Alland. 2002. Methodological problems in the molecular epidemiology of tuberculosis. Am. J. Epidemiol. 155565-571. [DOI] [PubMed] [Google Scholar]
  • 27.National Tuberculosis Controllers Association/CDC Advisory Group on Tuberculosis Genotyping. 2004. Guide to the application of genotyping to tuberculosis prevention and control. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Atlanta, GA.
  • 28.Sharnprapai, S., A. C. Miller, R. Suruki, E. Corkren, S. Etkind, J. Driscoll, M. McGarry, and E. Nardell. 2002. Genotyping analyses of tuberculosis cases in U.S.- and foreign-born Massachusetts residents. Emerg. Infect. Dis. 81239-1245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Small, P. M., P. C. Hopewell, S. P. Singh, A. Paz, J. Parsonnet, D. C. Ruston, G. F. Schecter, C. L. Daley, and G. K. Schoolnik. 1994. The epidemiology of tuberculosis in San Francisco. A population-based study using conventional and molecular methods. N. Engl. J. Med. 3301703-1709. [DOI] [PubMed] [Google Scholar]
  • 30.Sonnenberg, P., and P. Godfrey-Faussett. 2003. The use of DNA fingerprinting to study tuberculosis, p. 60-73. In P. D. O. Davies (ed.), Clinical tuberculosis, 3rd ed. Hodder Arnold, London, United Kingdom.
  • 31.van Deutekom, H., S. P. Hoijng, P. E. de Haas, M. W. Langendam, A. Horsman, D. van Soolingen, and R. A. Coutinho. 2004. Clustered tuberculosis cases: do they represent recent transmission and can they be detected earlier? Am. J. Respir. Crit. Care Med. 169806-810. [DOI] [PubMed] [Google Scholar]
  • 32.van Deutekom, H., P. Supply, P. E. de Haas, E. Willery, S. P. Hoijng, C. Locht, R. A. Coutinho, and D. van Soolingen. 2005. Molecular typing of Mycobacterium tuberculosis by mycobacterial interspersed repetitive unit-variable-number tandem repeat analysis, a more accurate method for identifying epidemiological links between patients with tuberculosis. J. Clin. Microbiol. 434473-4479. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.van Embden, J. D., M. D. Cave, J. T. Crawford, J. W. Dale, K. D. Eisenach, B. Gicquel, P. Hermans, C. Martin, R. McAdam, T. M. Shinnick, and P. M. Small. 1993. Strain identification of Mycobacterium tuberculosis by DNA fingerprinting: recommendations for a standardized methodology. J. Clin. Microbiol. 31406-409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.van Klingeren, B., M. Dessen-Kroon, T. van der Laan, K. Kremer, and D. van Soolingen. 2007. Drug susceptibility testing of Mycobacterium tuberculosis complex using a high-throughput, reproducible, absolute concentration method. J. Clin. Microbiol. 452662-2668. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.van Soolingen, D., P. E. de Haas, P. W. Hermans, P. M. Groenen, and J. D. van Embden. 1993. Comparison of various repetitive DNA elements as genetic markers for strain differentiation and epidemiology of Mycobacterium tuberculosis. J. Clin. Microbiol. 311987-1995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Vynnycky, E., and P. E. Fine. 1997. The natural history of tuberculosis: the implications of age-dependent risks of disease and the role of reinfection. Epidemiol. Infect. 119183-201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Warren, R. M., G. D. van der Spuy, M. Richardson, N. Beyers, M. W. Borgdorff, M. A. Behr, and P. D. van Helden. 2002. Calculation of the stability of the IS6110 banding pattern in patients with persistent Mycobacterium tuberculosis disease. J. Clin. Microbiol. 401705-1708. [DOI] [PMC free article] [PubMed] [Google Scholar]

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