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Estimating the annual risk of tuberculosis infection and disease in southeast of Iran using the bayesian mixture method
المؤلفون المشاركون
Haghdoost, Ali Akbar
Nasihi, Mahshid
Afshari, Mahdi
Baneshi, Muhammad Riza
Gouya, Muhammad Mahdi
Movahednia, Mahtab
المصدر
Iranian Red Crescent Medical Journal
العدد
المجلد 16، العدد 9 (30 سبتمبر/أيلول 2014)، ص ص. 1-6، 6ص.
الناشر
تاريخ النشر
2014-09-30
دولة النشر
الإمارات العربية المتحدة
عدد الصفحات
6
التخصصات الرئيسية
الموضوعات
الملخص EN
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. Objectives : We used a newly developed approach to estimate the incidence of tuberculosis in Sistan, an endemic area in southeast of Iran in 2012-13. Patients and 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.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Haghdoost, Ali Akbar& Afshari, Mahdi& Baneshi, Muhammad Riza& Gouya, Muhammad Mahdi& Nasihi, Mahshid& Movahednia, Mahtab. 2014. Estimating the annual risk of tuberculosis infection and disease in southeast of Iran using the bayesian mixture method. Iranian Red Crescent Medical Journal،Vol. 16, no. 9, pp.1-6.
https://search.emarefa.net/detail/BIM-408139
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Haghdoost, Ali Akbar…[et al.]. Estimating the annual risk of tuberculosis infection and disease in southeast of Iran using the bayesian mixture method. Iranian Red Crescent Medical Journal Vol. 16, no. 9 (Sep. 2014), pp.1-6.
https://search.emarefa.net/detail/BIM-408139
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Haghdoost, Ali Akbar& Afshari, Mahdi& Baneshi, Muhammad Riza& Gouya, Muhammad Mahdi& Nasihi, Mahshid& Movahednia, Mahtab. Estimating the annual risk of tuberculosis infection and disease in southeast of Iran using the bayesian mixture method. Iranian Red Crescent Medical Journal. 2014. Vol. 16, no. 9, pp.1-6.
https://search.emarefa.net/detail/BIM-408139
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 6
رقم السجل
BIM-408139
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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