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Author(s): Omosebi Oluwafunmilayo, Olanrewaju Samuel Olayemi, Adejumo Oluwasegun Agbailu.

Volume/Issue: Volume 3 , Issue 1 (2023)

Abstract:

TB is perhaps the most important contagious disease in the world and the leading cause of mortality by an infectious disease. As a result, WHO declared that achieving the reduction in TB incidence rate for achievement of the 90-90-90 target of the END-TB strategy will be an illusion, if something severe is not done. Therefore, it is imperative to assess the visibility of achieving the END-TB goal in the country (Nigeria) by assessing the success of TB treatments so far in the country. Hence, this paper aims to model the outcome of drug-resistant-tuberculosis and drug-susceptible-tuberculosis patients in Oyo state of Nigeria using the logit function of estimating binary logistic regression model vis-à-vis identifying the success of these TB treatments. At baseline, based on WHO categorization, the study revealed the commonest cases of patients receiving DS-TB seen are ‘New’ (90.5%) followed by relapse after failure (4.2%). Contrarily, the commonest cases of patients receiving DR-TB seen are treatment after failure (44.3%), new (27.5%) and relapse after failure cases (20.6%). Four months after starting treatment, 91.5% and 3.2% were reportedly alive and dead respectively for patients receiving DS-TB treatment while 85.3% and 11.5% were reportedly alive and dead respectively for receiving DR-TB treatment. Hence, the percentage success of DS-TB recorded was higher than the recorded for DR-TB patients. Furthermore, the chi-square results for DS-TB patients indicated that mortality significantly associated with DS-TB categorised patients (i.e. Relapse) and HIV status (i.e. Negative). Also, for the DR-TB patients, the results depicted that mortality significantly associated with DR-TB categorised patients (i.e. TAF, Treatment after Loss to Follow Up and New), both HIV status and Sputum Smear status (i.e. Positive). Nevertheless, among other findings, the binary logistic regression model estimations revealed that categorised New patients and Sputum Smear status unfavourably and significantly predicted the treatment outcome (mortality) of DS-TB and DR-TB patients. As well, categorised Relapse patients unfavourably and significantly predicted the treatment outcome (mortality) of DR-TB patients. Thus, the DS-TB method of treatment is recommended in order to achieve the target goal of the END-TB strategy in Oyo state Nigeria.

Keywords:

Drug resistant, Drug susceptible, Tuberculosis, Chi-square binary logistics model.

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