title: Estimating the annual risk of tuberculosis infection and disease in southeast of iran using the bayesian mixture method.
abstract: BACKGROUND
  Tuberculosis is still a public health concern in Iran. The main challenge in monitoring epidemiological status of tuberculosis is to estimate its incidence accurately.
  
  
  OBJECTIVE
  We used a newly developed approach to estimate the incidence of tuberculosis in Sistan, an endemic area in southeast of Iran in 2012-13.
  
  
  METHODS
  This cross-sectional study was conducted on school children aged 6-9 years. We estimated a required sample size of 6350. Study participants were selected using stratified two-stage cluster sampling method and recruited in a tuberculin skin test survey. Indurations were assessed after 72 hours of the injection and their distributions were plotted. Prevalence and annual risk of tuberculosis infection (ARTI) were estimated using the Bayesian mixture model and some traditional methods. The incidence of active disease was calculated using the Markov Chain Monte Carlo technique.
  
  
  RESULTS
  We assumed weibull, normal and normal as the best distributions for indurations due to atypical reactions, BCG (Bacillus Calmette-Guérin) reactions and Mycobacterium tuberculosis infection, respectively. The estimated infection prevalence and ARTI were 3.6% (95%CI: 3.1, 4.1) and 0.48%, respectively. These estimates were lower than those obtained from the traditional methods. The incidence of active tuberculosis was estimated as 107 (87-149) per 100000 population with a CDR of 54% (40%-68%).
  
  
  CONCLUSIONS
  Although the mixture model showed slightly lower estimates than the traditional methods, it seems that this method might generate more accurate results for deep exploration of tuberculosis endemicity. Besides, we found that Sistan is a high endemic area for tuberculosis in Iran with a low case detection rate.
authors.affiliation: Research Center for Modeling in Health, Institute of Futures Studies in Health, Kerman University of Medical Sciences, Kerman, IR Iran.
authors.forename: Ali Akbar
authors.initials: AA
authors.lastname: Haghdoost
authors.affiliation: Research Center for Modeling in Health, Institute of Futures Studies in Health, Kerman University of Medical Sciences, Kerman, IR Iran.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Afshari
authors.affiliation: Research Center for Modeling in Health, Institute of Futures Studies in Health, Kerman University of Medical Sciences, Kerman, IR Iran.
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Baneshi
authors.affiliation: Center for Infectious Disease Control, Ministry of Health and Medical Education, Tehran, IR Iran.
authors.forename: Mohammad Mehdi
authors.initials: MM
authors.lastname: Gouya
authors.affiliation: Epidemiology and Biostatistics Department, School of Public Health, Tehran University of Medical Sciences, Tehran, IR Iran.
authors.forename: Mahshid
authors.initials: M
authors.lastname: Nasehi
authors.affiliation: Zabol University of Medical Sciences, Zabol, IR Iran.
authors.forename: Mahtab
authors.initials: M
authors.lastname: Movahednia
keywords: Infection; Survey; Tuberculosis