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Link to original content: http://pubmed.ncbi.nlm.nih.gov/17570116
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Review
. 2007 Jul 15;196(2):281-8.
doi: 10.1086/518898. Epub 2007 Jun 4.

Prediction of the tuberculosis reinfection proportion from the local incidence

Jann-Yuan Wang  1 , Li-Na Lee, Hsin-Chih Lai, Hsiao-Leng Hsu, Yuang-Shuang Liaw, Po-Ren Hsueh, Pan-Chyr Yang
Affiliations
Review

Prediction of the tuberculosis reinfection proportion from the local incidence

Jann-Yuan Wang et al. J Infect Dis. .

Abstract

Background: Reinfection is a major contributor to tuberculosis (TB). It seems that the higher the local incidence, the higher the proportion of reinfection.

Methods: Based on a systematic review of the literature, we established a regression model to predict the reinfection proportion from the local incidence. We then used our local data to verify the algorithm.

Results: Of the 23 studies addressing reinfection in recurrent TB, 6 were population based. The reinfection proportion was correlated with the local incidence (reinfection proportion=-29.7+36.8 x log Incidence) (95% confidence interval [CI] for coefficient, 15.3-58.3; R2=0.849). The reinfection proportion in Taiwan (incidence, 62.4/100,000 people) was estimated to be 36% (95% CI, 3%-69%). Of our 49 recurrent patients, 51% had reinfection. Patients with reactivation seemed more likely to have underlying diseases and less likely to be smear positive. The relapse isolates seemed more resistant than the initial isolates.

Conclusions: The regression model could possibly predict the TB reinfection proportion from the local incidence. This algorithm is probably helpful in policy making for TB control programs. In areas where TB is endemic, reinfection might be responsible for >50% of TB cases, and aggressive surveillance to detect asymptomatic carriers could be an important strategy for controlling the disease.

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Comment in

  • Predicting reinfection in tuberculosis.
    van Helden PD, Warren RM, Uys P. van Helden PD, et al. J Infect Dis. 2008 Jan 1;197(1):172-3; author reply 173-4. doi: 10.1086/523829. J Infect Dis. 2008. PMID: 18171301 No abstract available.

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