Kenneth Okonkwo Ugwu1, Ifeanyi Sunday Onah2, Godwin Christopher Mbah3, Ifeoma Maureen Ezeonu4. 1. Department of Microbiology, University of Nigeria, Nsukka, Enugu State, Nigeria. kenneth.ugwu@unn.edu.ng. 2. Department of Mathematics, University of Nigeria, Nsukka, Enugu State, Nigeria. sunday.ifeanyi@unn.edu.ng. 3. Department of Mathematics, University of Nigeria, Nsukka, Enugu State, Nigeria. godwin.mbah@unn.edu.ng. 4. Department of Microbiology, University of Nigeria, Nsukka, Enugu State, Nigeria. ifeoma.ezeonu@unn.edu.ng.
Abstract
INTRODUCTION: Tuberculosis (TB) continues to be a public health problem globally. The burden is further exacerbated in developing countries like Nigeria, by poor diagnosis, management and treatment, as well as rapid emergence of drug-resistant TB. This study was conducted to evaluate the prevalence of drug-resistant TB, determine the rpoB gene mutation patterns of Mycobacterium tuberculosis (MTB) and model the dynamics of multidrug resistant TB (MDR-TB) in Enugu, Nigeria. METHODOLOGY: A total of 868 samples, from patients accessing DOTS services in designated centres within the zone, were screened by sputum-smear microscopy, while 207 samples were screened by Nucleic Acid Amplification (Xpert® MTB/Rif) Test (NAAT). A deterministic model was formulated to study the transmission dynamics of TB and MDR-TB, using live data generated through epidemiological study. RESULTS: The results showed TB prevalence values of 22.1% and 21.3% by sputum-smear and NAAT assays, respectively. Analysis of the rifampicin resistance patterns showed the highest occurrence of mutations (50%) along codons 523 - 527. Factors such as combination therapy, multiple therapy and compliance to treatment had influence on both prevalence and development of TB drug resistance in the population. CONCLUSIONS: This first documentation of Rifampicin resistance patterns in MTB from Nigeria shows that a majority of rpoB gene mutations occurred along codons 523 to 527, contrary to the widely reported codon 531 mutation and that multiple interventions such as combination therapy, with good compliance to treatment are needed to reduce both prevalence and development of TB drug resistance in the population. Copyright (c) 2020 Kenneth Okonkwo Ugwu, Ifeanyi Sunday Onah, Godwin Christopher Mbah, Ifeoma Maureen Ezeonu.
INTRODUCTION:Tuberculosis (TB) continues to be a public health problem globally. The burden is further exacerbated in developing countries like Nigeria, by poor diagnosis, management and treatment, as well as rapid emergence of drug-resistant TB. This study was conducted to evaluate the prevalence of drug-resistant TB, determine the rpoB gene mutation patterns of Mycobacterium tuberculosis (MTB) and model the dynamics of multidrug resistant TB (MDR-TB) in Enugu, Nigeria. METHODOLOGY: A total of 868 samples, from patients accessing DOTS services in designated centres within the zone, were screened by sputum-smear microscopy, while 207 samples were screened by Nucleic Acid Amplification (Xpert® MTB/Rif) Test (NAAT). A deterministic model was formulated to study the transmission dynamics of TB and MDR-TB, using live data generated through epidemiological study. RESULTS: The results showed TB prevalence values of 22.1% and 21.3% by sputum-smear and NAAT assays, respectively. Analysis of the rifampicin resistance patterns showed the highest occurrence of mutations (50%) along codons 523 - 527. Factors such as combination therapy, multiple therapy and compliance to treatment had influence on both prevalence and development of TB drug resistance in the population. CONCLUSIONS: This first documentation of Rifampicin resistance patterns in MTB from Nigeria shows that a majority of rpoB gene mutations occurred along codons 523 to 527, contrary to the widely reported codon 531 mutation and that multiple interventions such as combination therapy, with good compliance to treatment are needed to reduce both prevalence and development of TB drug resistance in the population. Copyright (c) 2020 Kenneth Okonkwo Ugwu, Ifeanyi Sunday Onah, Godwin Christopher Mbah, Ifeoma Maureen Ezeonu.
Entities:
Keywords:
M. tuberculosis; Nigeria; Xpert MTB/RIF; numerical simulation; rpoB