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J Glob Infect Dis ; 13(2): 85-90, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34194175


Introduction: Routine viral load (VL) testing is fraught with challenges in resource-limited settings which lead to longer turnaround times for the return of VL results. We assessed the turnaround times for VL testing and factors associated with long turnaround (>30 days) in Marondera, Zimbabwe, between January and September 2018. Methods: This was an analytical study of routine program data. Data were extracted from electronic records and paper-based reports at two laboratories and at antiretroviral therapy (ART) facilities. The unit of analysis was the VL sample. Duration (in days) between sample collection and sample testing (pre-test turnaround time), duration between sample testing and receipt of VL result at ART the site (post-test turnaround time), and duration between sample collection and receipt of result at the ART site (overall turnaround time) were calculated. Days on which the VL testing machine was not functional, and workload (number of tests done per month) were used to assess associations. We used binomial log models to assess the factors associated with longer turnaround time. Results: A total of 3348 samples were received at the two VL testing laboratories, and 3313 were tested, of these, 1111 were analyzed for overall turnaround time. Pre-test, post-test, and overall turnaround times were 22 days (interquartile range (IQR): 11-41), 51 days (IQR: 30-89), and 67 days (IQR: 46-100), respectively. Laboratory workload (relative risk [RR]: 1.12, 95% confidence interval [CI]: 1.10-1.14) and machine break down (RR: 1.15, 95% CI: 1.14-1.17) were associated with long turnaround time. Conclusions: Routine VL turnaround time was long. Decentralizing VL testing and enhancing laboratory capacity may help shorten the turnaround time.

J Trop Med ; 2020: 4761051, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32518566


Globally, childhood tuberculosis (TB among those aged <15 years) is a neglected component of national TB programmes in high TB burden countries. Zimbabwe, a country in southern Africa, is a high burden country for TB, TB-HIV, and drug-resistant TB. In this study, we assessed trends in annual childhood TB notifications in Harare (the capital of Zimbabwe) from 2009 to 2018 and the demographic, clinical profiles, and treatment outcomes of childhood TB patients notified from 2015-2017 by reviewing the national TB programme records and reports. Overall, there was a decline in the total number of TB patients (all ages) from 5,943 in 2009 to 2,831 in 2018. However, the number of childhood TB patients had declined exponentially 6-fold from 583 patients (117 per 100,000 children) in 2009 to 107 patients (18 per 100,000 children) in 2018. Of the 615 childhood TB patients notified between 2015 and 2017, 556 (89%) patient records were available. There were 53% males, 61% were aged <5 years, 92% were new TB patients, 85% had pulmonary TB, and 89% were treated for-drug sensitive TB, 3% for drug-resistant TB, and 40% were HIV positive (of whom 59% were on ART). Although 58% had successful treatment outcomes, the treatment outcomes of 40% were unknown (not recorded or not evaluated), indicating severe gaps in TB care. The disproportionate decline in childhood TB notifications could be due to the reduction in the TB burden among HIV positive individuals from the scale up of antiretroviral therapy and isoniazid preventive therapy. However, the country is experiencing economic challenges which could also contribute to the disproportionate decline in childhood TB notification and gaps in quality of care. There is an urgent need to understand the reasons for the declining trends and the gaps in care.

Afr J Lab Med ; 3(2): 241, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-29043196


BACKGROUND: Laboratory mentorship has proven to be an effective tool in building capacity and assisting laboratories in establishing quality management systems. The Zimbabwean Ministry of Health and Child Welfare implemented four mentorship models in 19 laboratories in conjunction with the Strengthening Laboratory Management Toward Accreditation (SLMTA) programme. OBJECTIVES: This study outlines how the different models were implemented, cost involved per model and results achieved. METHODS: Eleven of the laboratories had been trained previously in SLMTA (Cohort I). They were assigned to one of three mentorship models based on programmatic considerations: Laboratory Manager Mentorship (Model 1, four laboratories); One Week per Month Mentorship (Model 2, four laboratories); and Cyclical Embedded Mentorship (Model 3, three laboratories). The remaining eight laboratories (Cohort II) were enrolled in Cyclical Embedded Mentorship incorporated with SLMTA training (Model 4). Progress was evaluated using a standardised audit checklist. RESULTS: At SLMTA baseline, Model 1-3 laboratories had a median score of 30%. After SLMTA, at mentorship baseline, they had a median score of 54%. At the post-mentorship audit they reached a median score of 75%. Each of the three mentorship models for Cohort I had similar median improvements from pre- to post-mentorship (17 percentage points for Model 1, 23 for Model 2 and 25 for Model 3; p > 0.10 for each comparison). The eight Model 4 laboratories had a median baseline score of 24%; after mentorship, their median score increased to 63%. Median improvements from pre-SLMTA to post-mentorship were similar for all four models. CONCLUSION: Several mentorship models can be considered by countries depending on the available resources for their accreditation implementation plan.

Afr J Lab Med ; 3(2): 248, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-29043197


BACKGROUND: In 2010, the Zimbabwe Ministry of Health and Child Welfare (MoHCW) adopted the Strengthening Laboratory Management Toward Accreditation (SLMTA) programme as a tool for laboratory quality systems strengthening. OBJECTIVES: To evaluate the financial costs of SLMTA implementation using two models (external facilitators; and internal local or MoHCW facilitators) from the perspective of the implementing partner and to estimate resources needed to scale up the programme nationally in all 10 provinces. METHODS: The average expenditure per laboratory was calculated based on accounting records; calculations included implementing partner expenses but excluded in-kind contributions and salaries of local facilitators and trainees. We also estimated theoretical financial costs, keeping all contextual variables constant across the two models. Resource needs for future national expansion were estimated based on a two-phase implementation plan, in which 12 laboratories in each of five provinces would implement SLMTA per phase; for the internal facilitator model, 20 facilitators would be trained at the beginning of each phase. RESULTS: The average expenditure to implement SLMTA in 11 laboratories using external facilitators was approximately US$5800 per laboratory; expenditure in 19 laboratories using internal facilitators was approximately $6000 per laboratory. The theoretical financial cost of implementing a 12-laboratory SLMTA cohort keeping all contextual variables constant would be approximately $58 000 using external facilitators; or $15 000 using internal facilitators, plus $86 000 to train 20 facilitators. The financial cost for subsequent SLMTA cohorts using the previously-trained internal facilitators would be approximately $15 000, yielding a break-even point of 2 cohorts, at $116 000 for either model. Estimated resources required for national implementation in 120 laboratories would therefore be $580 000 using external facilitators ($58 000 per province) and $322 000 using internal facilitators ($86 000 for facilitator training in each of two phases plus $15 000 for SLMTA implementation in each province). CONCLUSION: Investing in training of internal facilitators will result in substantial savings over the scale-up of the programme. Our study provides information to assist policy makers to develop strategic plans for investing in laboratory strengthening.