Estimating Long-term Tuberculosis Reactivation Rates in Australian Migrants

Katie D. Dale, James M. Trauer, Peter J. Dodd, Rein M.G.J. Houben, Justin T. Denholm

Research output: Contribution to journalArticleResearchpeer-review

Abstract

BACKGROUND: The risk of progression to tuberculosis (TB) disease is greatest soon after infection, yet disease may occur many years or decades later. However, rates of TB reactivation long after infection remain poorly quantified. Australia has a low incidence of TB and most cases occur among migrants. We explored how TB rates in Australian migrants varied with time from migration, age, and gender. METHODS: We combined TB notifications in census years 2006, 2011, and 2016 with time- and country-specific estimates of latent TB prevalences in migrant cohorts to quantify postmigration reactivation rates. RESULTS: During the census years, 3246 TB cases occurred among an estimated 2 084 000 migrants with latent TB. There were consistent trends in postmigration reactivation rates, which appeared to be dependent on both time from migration and age. Rates were lower in cohorts with increasing time, until at least 20 years from migration, and on this background there also appeared to be increasing rates during youth (15-24 years of age) and in those aged 70 years and above. Within 5 years of migration, annual reactivation rates were approximately 400 per 100 000 (uncertainty interval [UI] 320-480), dropping to 170 (UI 130-220) from 5 to 10 years and 110 (UI 70-160) from 10 to 20 years, then sustaining at 60-70 per 100 000 up to 60 years from migration. Rates varied depending on age at migration. CONCLUSIONS: Postmigration reactivation rates appeared to show dependency on both time from migration and age. This approach to quantifying reactivation risks will enable evaluations of the potential impacts of TB control and elimination strategies.

Original languageEnglish
Pages (from-to)2111-2118
Number of pages8
JournalClinical infectious diseases : an official publication of the Infectious Diseases Society of America
Volume70
Issue number10
DOIs
Publication statusPublished - 6 May 2020

Keywords

  • disease progression
  • epidemiologic methods
  • incidence
  • latent tuberculosis
  • mathematical modelling

Cite this