Browsing by Author "Ngadaya, E."
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Item Genome sequence of Mycobacterium yongonense RT 955-2015 isolate from a patient misdiagnosed with multidrug-resistant tuberculosis: First clinical detection in Tanzania(International Journal of Infectious Diseases, 2018-06) Mnyambwa, N.P.; Kim, D.-J.; Ngadaya, E.; Chun, J.; Ha, S.-M.; Petrucka, P.; Addo, K.K.; Kazwala, R.R.; Mfinanga, S.G.Background: Mycobacterium yongonense is a recently described novel species belonging to Mycobacterium avium complex, which is the most prevalent aetiology of non-tuberculous mycobacteria associated with pulmonary infections, and poses tuberculosis diagnostic challenges in high-burden, resource-constrained settings. Methods: Whole genome shotgun sequencing and comparative microbial genomic analyses were used to characterize the isolate from a patient diagnosed with multidrug-resistant tuberculosis (MDR-TB) after relapse. Results: The genome sequence of the first case of M. yongonense (M. yongonense RT 955-2015) in Tanzania is presented. Sequence analysis revealed that the RT 955-2015 strain had a high similarity to M. yongonense 05-1390(T) (98.74%) and Mycobacterium chimaera DSM 44623(T) (98%). Its 16S rRNA showed similarity to Mycobacterium paraintracellulare KCTC 290849(T) (100%), Mycobacterium intracellulare ATCC 13950(T) (100%), M. chimaera DSM 44623(T) (99.9%), and M. yongonense 05-1390(T) (98%). The strain exhibited a substantially different rpoB sequence to that of M. yongonense 05-1390 (95.16%), but closely related to that of M. chimaera DSM 44623(T) (99.86%), M. intracellulare ATCC 13950(T), (99.53%), and M. paraintracellulare KCTC 290849(T) (99.53%). Conclusions: In light of the OrthoANI algorithm and phylogenetic analysis, it was concluded that the isolate was M. yongonense Type II genotype, which is an indication that the patient was misdiagnosed with TB/MDR-TB and received inappropriate treatment. © 2018 The Author(s)Item Implementation of distance learning IMCI training in rural districts of Tanzania(BMC Health Services Research, 2023) Isangula, K.; Ngadaya, E.; Manu, A.; Mmweten, M.; Philbert, D.; Burengelo, D.; Kagaruki, G.; Hailegebriel, T.D.; et al.Background The standard face-to-face training for the integrated management of childhood illness (IMCI) continues to be plagued by concerns of low coverage of trainees, the prolonged absence of trainees from the health facility to attend training and the high cost of training. Consequently, the distance learning IMCI training model is increasingly being promoted to address some of these challenges in resource-limited settings. This paper examines participants’ accounts of the paper-based IMCI distance learning training programme in three district councils in Mbeya region, Tanzania. Methods A cross-sectional qualitative descriptive design was employed as part of an endline evaluation study of the management of possible serious bacterial infection in Busokelo, Kyela and Mbarali district councils of Mbeya Region in Tanzania. Key informant interviews were conducted with purposefully selected policymakers, partners, programme managers and healthcare workers, including beneficiaries and training facilitators. Results About 60 key informant interviews were conducted, of which 53% of participants were healthcare workers, including nurses, clinicians and pharmacists, and 22% were healthcare administrators, including district medical officers, reproductive and child health coordinators and programme officers. The findings indicate that the distance learning IMCI training model (DIMCI) was designed to address concerns about the standard IMCI model by enhancing efficiency, increasing outputs and reducing training costs. DIMCI included a mix of brief face-to-face orientation sessions, several weeks of self-directed learning, group discussions and brief face-to-face review sessions with facilitators. The DIMCI course covered topics related to management of sick newborns, referral decisions and reporting with nurses and clinicians as the main beneficiaries of the training. The problems with DIMCI included technological challenges related to limited access to proper learning technology (e.g., computers) and unfriendly learning materials. Personal challenges included work-study-family demands, and design and coordination challenges, including low financial incentives, which contributed to participants defaulting, and limited mentorship and follow-up due to limited funding and transport.