Bayesian analysis of multidrug resistance tuberculosis from Amravati Region using non-informative priors

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dc.contributor.authorAhemed, S. F.en_US
dc.contributor.authorSingh, R.en_US
dc.contributor.authorSingh, P.en_US
dc.date.accessioned2025-06-19T06:00:14Z
dc.date.available2025-06-19T06:00:14Z
dc.date.issued2025-03
dc.description.abstractThis study is an attempt to fit a binary logistic model on the data of TB- patients registered under DOTS from Amravati region, with the aim to determine predictors (risk factors) of MDR-TB, under Bayesian framework. Drug resistant tuberculosis is a serious public health problem in India and worldwide. Detection and treatment of MDR?TB is a priority in National Tuberculosis program in India. Bayesian approach with Non-informative prior is employed for data analysis in this study. MDR-TB presence is taken as the response variable in this study, with 18 explanatory variables related to clinical and treatment details of present and past history of the patients. Odds ratios for the Bayesian estimates of parameters are calculated using Gibbs Sampling procedure. It is found in the study that probability of developing MDR-Tb increases with increase in the number of previous TB treatment. Out of 18, eight variables are found to be potentially effective in the development of MDR-TB among TB patients.en_US
dc.identifier.affiliationsResearch Scholar, Department of Statistics, Sant Gadge Baba Amravati University, Tapovan Road, Amaravati -444601en_US
dc.identifier.affiliationsMobile 9423871751en_US
dc.identifier.affiliationsProfessor & Head, Department of Statistics, Sant Gadge Baba Amravati University, Tapovan Road, Amaravati -444601; Email :rsinghamt@hotmail.com; Mobile 9422840360en_US
dc.identifier.affiliationsAssistant Professor, Department of Statistics, Institute of Science, Nagpur; Email:priteesingh25@gmail.com; Mob.9422857429.en_US
dc.identifier.citationAhemed S. F., Singh R., Singh P.. Bayesian analysis of multidrug resistance tuberculosis from Amravati Region using non-informative priors. Indian Journal of Preventive and Social Medicine. 2025 Mar; 56(1): 17-26en_US
dc.identifier.issn0301-1216
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/249993
dc.languageenen_US
dc.publisherDepartment of Community Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi- 221005, India.en_US
dc.relation.issuenumber1en_US
dc.relation.volume56en_US
dc.source.urihttps://ijpsm.co.in/index.php/ijpsm/article/view/722en_US
dc.subjectMultidrug-resistant tuberculosis (MDR-TB)en_US
dc.subjectBayesian approachen_US
dc.subjectGibbs Sampling procedureen_US
dc.subjectodds ratiosen_US
dc.titleBayesian analysis of multidrug resistance tuberculosis from Amravati Region using non-informative priorsen_US
dc.typeJournal Articleen_US
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