Applying spatiotemporal models to study risk of smear-positive tuberculosis in Iran, 2001-2012

Int J Tuberc Lung Dis. 2015 Apr;19(4):469-74. doi: 10.5588/ijtld.14.0459.

Abstract

Setting: Assessing tuberculosis (TB) distribution in regions over time is essential for health officials to have a proper understanding of current status, determine high-risk areas, and improve case management and resource allocation.

Objective: To evaluate spatial distribution and trends in the risk of smear-positive Mycobacterium tuberculosis in Iran during 2001-2012 using spatiotemporal models.

Design: Overall and province-specific trends in TB risk were estimated using a Bayesian spatiotemporal model. We obtained Bayesian posterior probabilities to test the hypothesis of the relative risk (RR) being equal to 1 and the significance of TB trends in each province.

Results: Estimated countrywide trends declined at a rate of almost 3% per decade. The RR was the highest in the provinces of Sistan and Baluchestan, followed by Golestan, Khorasan-Razavi, Hormozgan, Qom, Guilan and South Khorasan. Upward temporal trends were observed in nine provinces.

Conclusion: TB risk was generally high in provinces bordering high TB burden countries; population movements from high-risk provinces and adjacent countries appear to be the main challenge to TB control. Nevertheless, the declining risk pattern in these provinces indicates good, but inadequate, progress with TB control. Different health policies according to TB risk and trend are required for each province.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Humans
  • Iran / epidemiology
  • Models, Theoretical
  • Mycobacterium tuberculosis
  • Retrospective Studies
  • Risk Factors
  • Spatio-Temporal Analysis*
  • Tuberculosis, Multidrug-Resistant / epidemiology*