Insights into SARS-CoV-2 in Angola during the COVID-19 peak: Molecular epidemiology and genome surveillance.

Background: In Angola, COVID-19 cases have been reported in all provinces, resulting in >105,000 cases and >1900 deaths. However, no detailed genomic surveillance into the introduction and spread of the SARS-CoV-2 virus has been conducted in Angola. We aimed to investigate the emergence and epidemic progression during the peak of the COVID-19 pandemic in Angola. Methods: We generated 1210 whole-genome SARS-CoV-2 sequences, contributing West African data to the global context, that were phylogenetically compared against global strains. Virus movement events were inferred using ancestral state reconstruction. Results: The epidemic in Angola was marked by four distinct waves of infection, dominated by 12 virus lineages, including VOCs, VOIs, and the VUM C.16, which was unique to South-Western Africa and circulated for an extended period within the region. Virus exchanges occurred between Angola and its neighboring countries, and strong links with Brazil and Portugal reflected the historical and cultural ties shared between these countries. The first case likely originated from southern Africa. Conclusion: A lack of a robust genome surveillance network and strong dependence on out-of-country sequencing limit real-time data generation to achieve timely disease outbreak responses, which remains of the utmost importance to mitigate future disease outbreaks in Angola.

Surveillance of antimicrobial resistance in human health in Tanzania: 2016-2021.

Background: Antimicrobial resistance (AMR) surveillance plays an important role in early detection of resistant strains of pathogens and informs treatments decisions at local, regional and national levels. In 2017, Tanzania developed a One Health AMR Surveillance Framework to guide establishment of AMR surveillance systems in the human and animal sectors. Aim: We reviewed AMR surveillance studies in Tanzania to document progress towards establishing an AMR surveillance system and determine effective strengthening strategies. Methods: We conducted a literature review on AMR studies conducted in Tanzania by searching Google Scholar, PubMed, and the websites of the Tanzania Ministry of Health and the World Health Organization for articles written in English and published from January 2012 to March 2021 using relevant search terms. Additionally, we reviewed applicable guidelines, plans, and reports from the Tanzanian Ministry of Health. Results: We reviewed 10 articles on AMR in Tanzania, where studies were conducted at hospitals in seven of Tanzania's 26 regions between 2012 and 2019. Nine AMR sentinel sites had been established, and there was suitable and clear coordination under 'One Health'. However, sharing of surveillance data between sectors had yet to be strengthened. Most studies documented high resistance rates of Gram-negative bacteria to third-generation cephalosporins. There were few laboratory staff who were well trained on AMR. Conclusion: Important progress has been made in establishing a useful, reliable AMR surveillance system. Challenges include a need to develop, implement and build investment case studies for the sustainability of AMR surveillance in Tanzania and ensure proper use of third-generation cephalosporins. What this study adds: This article adds to the knowledge base of AMR trends in Tanzania and progress made in the implementation of AMR surveillance in human health sector as a contribution to the global AMR initiatives to reduce AMR burden worldwide. It has highlighted key gaps that need policy and implementation level attention.

Implementation of the COVID-19 laboratory testing certification program (CoLTeP), Zimbabwe, 2021.

The Africa Union (AU) Trusted Travel Initiative was introduced in 2021 to support Africa Union member states enhance their current health screening systems. Trusted Travel offers an online digital platform for the verification and authentication of COVID-19 results based on a collaborative effort across a network of participating COVID-19 testing laboratories. In this paper, we describe the certification process of laboratories to qualify for listing on the AU Trusted Travel platform as approved and recognized COVID-19 testing facilities. A checklist prepared from the ISO15189: 2012, ISO15190: 2020 and World Health Organization Laboratory Safety Manual, 4th edition was used to audit laboratories. Approved auditors completed the audit checklist through reviewing laboratory documents and records, observing laboratory operations whilst asking open-ended questions to clarify documentation seen and observations made. A laboratory was recommended for certification after scoring at least 90%. Between May and September 2021, a total of 26 (19%) of the 134 medical laboratories authorized for SARS-CoV-2 testing had been audited for CoLTeP certification in Zimbabwe. The majority 16 (62%) attained 5 stars rating with 10 (38%) attaining 0-4 stars. Performance was highest in the area of test result and data management (mean score 93%, SD 9.1). The least performance of the laboratories was on the laboratory biosafety and biosecurity (mean score 73%, SD 17.0) and Quality Control and Assurance (mean score 71%, SD 15.0). There is need for laboratories to commit their resources to quality assurance programs and training of laboratory personnel in biosafety and biosecurity as part of continuous quality improvement.

Implementation of COVID-19 Laboratory Testing Certification Program (CoLTeP) in African Region.

Objectives: Coronavirus disease 2019 was declared a global pandemic in March 2020 with correct and early detection of cases using laboratory testing central to the response. Hence, the establishment of quality management systems and monitoring their implementation are critical. This study describes the experience of implementing the COVID-19 Laboratory Testing and Certification Program (CoLTeP) in Africa. Methods: Private and public laboratories conducting SARS-CoV-2 testing using polymerase chain reaction were enrolled and assessed for quality and safety using the CoLTeP checklists. Results: A total of 84 laboratories from 7 countries were assessed between April 2021 to December 2021 with 52% of these from the private sector. Among them, 64% attained 5 stars and were certified. Section 4 had the highest average score of 92% and the lowest of 78% in Section 3. Also, 82% of non-conformities (NCs) were related to sample collection, transportation, and risk assessments. Non-availability, inconsistency in performing, recording, instituting corrective actions for failed internal and external quality controls were among major NCs reported. Conclusions: Laboratories identified for SARS-CoV-2 testing by public and private institutions mostly met the requirements for quality and safe testing as measured by the CoLTeP checklist.

Maximising mentorship: variations in laboratory mentorship models implemented in Zimbabwe

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

Maximising mentorship: Variations in laboratory mentorship models implemented in Zimbabwe.

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.

Weighing the costs: Implementing the SLMTA programme in Zimbabwe using internal versus external facilitators.

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.