Using capture–recapture methods to study recent transmission of tuberculosis

Martien W Borgdorff1, Judith R Glynn2 and Emilia Vynnycky3

1 University of Amsterdam and KNCV Tuberculosis Foundation, PO Box 22660, 1100 DD Amsterdam, The Netherlands. E-mail: m.w.borgdorff{at}amc.uva.nl
2 London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK
3 Communicable Disease Surveillance Centre, Health Protection Agency, UK

Sirs—A recent paper of Inigo et al. deals with a very interesting subject: use of the capture-recapture method to estimate the number of tuberculosis (TB) cases attributable to recent transmission.1 While estimating numbers of TBcases in the general population is an important topic, and the capture-recapture method may be a useful method to achieve this, we believe that the novel application in the study of Inigo et al. is seriously flawed.

When applying the capture-recapture method in a standard way, the number of people belonging to different groups or databases, and the extent to which these databases overlap, are determined. In the study of Inigo et al., capture-recapture is used not to get the total number of cases but to get the number attributable to recent transmission. Below we argue that this leads to invalid results, because the different databases use different case definitions of recent transmission, neither of which is 100% specific.

The amount of recent transmission identified with the two methods (contact investigation and restriction fragment length polymorphism [RFLP] results, respectively) was very different. This is not surprising. Epidemiological contact information has low sensitivity since casual contacts are often missed, while its specificity may be limited in high-risk populations.2 If we understand Inigo et al. correctly, epidemiological identification of recent transmission in their study had a positive predictive value of 55% since of 29 contacts with known RFLP results, 16 (55%) were found to be clustered, while 13 were not clustered. Incidentally, this result should also have been applied to the 20 epidemiologically linked cases without RFLP results available. RFLP typing on the other hand may have limited sensitivity if sampling is incomplete3,4 and limited specificity in stable populations.5,6

In the Table we show a theoretical example of a population which is completely captured, and in which two tests are used to identify cases of recent transmission. One test has low sensitivity (8/30 = 27%) and high specificity (63/70 = 90%) (epidemiological information on contact) and the other higher sensitivity (26/30 = 87%) and lower specificity (56/70 = 80%) (RFLP typing). The Table does not claim that sensitivity and specificity of these techniques are known to have these values, but explores the consequences of sub-optimal sensitivity and specificity of different diagnostic tests if their results are used in a capture-recapture analysis.


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Table Theoretical results of capture-recapture analysis using tests with limited sensitivity and specificity

 
In the Table, A and B summarize the ‘test’ results in a population in which 30% of cases are attributable to recent transmission. C and D compare the results of the two tests in ‘true’ positives and ‘true’ negatives, assuming errors in the two tests are independent (thus, for example, the expected value for Epi recent transmission = yes and RFLP recent transmission = yes is (8 x 26)/30). E provides a comparison of test results in the total population (by summing C and D), and F applies the capture-recapture analysis as proposed by Inigo et al. on those positive on either test. The 75 cases attributed to recent transmission suggested by this capture-recapture analysis in this example are an extreme overestimate, which is due to the limited sensitivity and specificity of the two tests.

Another way of showing the method is flawed, is by making an estimate of the proportion of cases attributable to remote transmission (i.e. transmission which is not recent), using exactly the same method. In that case, those negative on either test would be included, and the total number of cases attributed to remote transmission would be 96 (Table G). Clearly, the method used by Inigo et al. leads to inconsistency and does not give results reflecting the true situation.

In conclusion, the capture-recapture method may be valuable if applied in its standard way (comparing membership of various databases). However, additional requirements on how these individuals are classified within the databases may invalidate the results, unless either exactly the same case definition is used, or perhaps, if adjustments can be made if the case definition is not identical.7 If for the identification of TBcases attributable to recent transmission one database uses data from contact investigation and the other uses molecular data, the case definitions of recent transmission in the two databases are very different, while their sensitivity and specificity are insufficiently known to allow appropriate adjustments. Therefore, this application of the capture-recapture method leads to invalid results.

References

1 Inigo J, Arce A, Martin-Moreno JM, Herruzo R, Palenque E, Chaves F. Recent transmission of tuberculosis in Madrid: application of capture-recapture analysis to conventional and molecular epidemiology. Int J Epidemiol 2003;32:763–69.[Abstract/Free Full Text]

2 Behr MA, Hopewell PC, Paz EA, Kawamura LM, Schecter GF, Small PM. Predictive value of contact investigation for identifying recent transmission of Mycobacterium tuberculosis. Am J Respir Crit Care Med 1998;158:465–69.[Abstract/Free Full Text]

3 Glynn JR, Vynnycky E, Fine PE. Influence of sampling on estimates of clustering and recent transmission of Mycobacterium tuberculosis derived from DNA fingerprinting techniques. Am J Epidemiol 1999;149:366–71.[Abstract]

4 Van Soolingen D, Borgdorff MW, De Haas PEW et al. Molecular epidemiology of tuberculosis in The Netherlands: a nationwide study from 1993 through 1997. J Infect Dis 1999;180:726–36.[CrossRef][ISI][Medline]

5 Braden CR, Templeton GL, Cave MD et al. Interpretation of restriction fragment length polymorphism analysis of Mycobacterium tuberculosis isolates from a state with a large rural population. J Infect Dis 1997;175:1446–52.[ISI][Medline]

6 Vynnycky E, Borgdorff MW, Van Soolingen D, Fine PEM. Annual Mycobacterium tuberculosis infection risk and interpretation of clustering statistics. Emerg Infect Dis 2003;9:176–83.[ISI][Medline]

7 Hook EB, Regal RR. Capture-recapture methods in epidemiology: methods and limitations. Epidemiol Rev 1995;17:243–64.[ISI][Medline]





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