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The rapid emergence and global dissemination of SARS-CoV-2 highlighted a need for robust, adaptable surveillance systems. However, financial and infrastructure requirements for whole genome sequencing (WGS) mean most surveillance data have come from higher-resource geographies, despite unprecedented investment in sequencing in low-middle income countries (LMICs) throughout the SARS-CoV-2 pandemic. Consequently, the molecular epidemiology of SARS-CoV-2 in some LMICs is limited, and there is a need for more cost-accessible technologies to help close data gaps for surveillance of SARS-CoV-2 variants. To address this, we have developed two high-resolution melt curve (HRM) assays that target key variant-defining mutations in the SARS-CoV-2 genome, which give unique signature profiles that define different SARS-CoV-2 variants of concern (VOCs). Extracted RNA from SARS-CoV-2 positive samples collected from 205 participants (112 in Burkina Faso, 93 in Kenya) on the day of enrolment in the MALCOV study (Malaria as a Risk Factor for COVID-19) between February 2021 and February 2022 were analysed using our optimised HRM assays and compared to Next Generation Sequencing (NGS) on Oxford Nanopore MinION . With NGS as a reference, two HRM assays, HRM-VOC-1 and HRM-VOC-2, demonstrated sensitivity/specificity of 100%/99.29% and 92.86/99.39%, respectively, for detecting Alpha, 90.08%/100% and 92.31%/100% for Delta and 93.75%/100% and 100%/99.38% for Omicron. The assays described here provide a lower-cost approach (<$1 per sample) to conducting molecular epidemiology, capable of high-throughput testing. We successfully scaled up the HRM-VOC-2 assay to screen a total of 506 samples from which we were able to show the replacement of Alpha with the introduction of Delta and the replacement of Delta by the Omicron variant in this community in Kisumu, Kenya. These assays are readily adaptable and can focus on local epidemiological surveillance questions or be updated quickly to accommodate the emergence of a novel variant or adapt to novel and emerging pathogens.
Subject(s)
COVID-19 , Malaria , Genomic InstabilityABSTRACT
Background The World Health Organization (WHO) model list of Essential In vitro Diagnostic (EDL) introduced in 2018 complements the established Essential Medicines List (EML) and improves its impact on advancing universal health coverage and better health outcomes. We conducted a scoping review of the literature on the implementation of the WHO essential lists in Africa to inform the implementation of the recently introduced EDL. Methods We searched eight electronic databases for studies reporting on the implementation of the WHO EDL and EML in Africa. Two authors independently conducted study selection and data extraction, with disagreements resolved through discussion. We used the Supporting the Use of Research Evidence (SURE) framework to extract themes and synthesized findings using thematic content analysis. We used the Mixed Method Appraisal Tool (MMAT) version 2018 to assess the quality of included studies where applicable. Results We included 172 studies reporting on EDL and EML after screening 3,813 articles titles and abstracts and 1,545 full-text papers. Most (75%, n=129) included studies were purely quantitative in design comprising descriptive cross-sectional designs (60%, n=104), 15% (n=26) were purely qualitative, and 10% (n=17) had mixed-methods approaches. There were no qualitative or randomised experimental studies about the EDL. The main barrier facing the EML and EDL was poorly equipped health facilities - including unavailability or stock-outs of essential in vitro diagnostics and medicines and inadequate infrastructure to enable health service delivery. Financial and non-financial incentives to health facilities and workers were a key enabler to the implementation of the EML however, their impact differed from one context to another. Fifty-six (33%) of the included studies were of high quality. Conclusions The EDL implementation at the national level can learn from health system interventions to improve the availability and supply of essential medicines such as financial and non-financial incentives in different contexts. Plain language summary The World Health Organization (WHO) periodically publishes the Model lists of essential medicines (EML) and essential in vitro diagnostics (EDL) to offer guidance to member states. The model lists help countries prioritise the critical health products that should be widely available and affordable throughout health systems. Countries frequently use these model lists to help develop their local lists of essential medicines and diagnostics. The model list of essential diagnostics was introduced in 2018, while the essential medicines were introduced 45 years ago. This work evaluates current evidence on the implementation of the more established model list of essential medicines to inform the development and implementation of the national list of essential in vitro diagnostics in Africa. We reviewed results from all available studies that looked at the provision of treatment and/or diagnostic services in Africa and assessed the barriers and enablers for their implementation. We found 172 articles assessing the provision of treatment and diagnostics in Africa. We looked in detail at the barriers and enablers to implementing the model lists of essential medicines and essential in vitro diagnostics. We also assessed the quality of the included research studies. We combined the results of the studies and established that the health system barriers were the most dominant constraints to implementing the model lists. Our review found the implementation of the established EML, the new EDL was mainly due to poorly equipped health facilities, including limited availability, and stock outs of essential medicines and tests. It is important to consider these constraints when developing and implementing the EDL at various national levels. EDL Implementation at the national level can learn from interventions to improve the availability and supply of essential medicines. Financial and non-financial incentives may be enabling interventions, but their effect varies in different countries and contexts.
ABSTRACT
INTRODUCTION In Africa almost half of healthcare services are delivered through private sector providers. These are often underused in national public health responses. In line with our previous HIV experience and to support and accelerate the public sector’s COVID-19 response, we initiated a public-private project (PPP) in Kisumu County, Kenya. In this manuscript we demonstrate this PPP’s performance, using COVID-19 testing as an aggregator and with semi-real time digital monitoring tools for rapid scaling of COVID-19 response. METHODS COVID-19 diagnostic testing formed the basis for a PPP between KEMRI, Department of Health Kisumu County, PharmAccess Foundation, and local faith-based and private healthcare facilities: COVID-Dx. COVID-Dx was implemented from June 01, 2020, to March 31, 2021 in Kisumu County, Kenya. Trained laboratory technologists in participating healthcare facilities collected nasopharyngeal and oropharyngeal samples from patients meeting the Kenyan MoH COVID-19 case definition. Samples were rapidly transported by motorbike and tested using RT-PCR at the central reference laboratory in KEMRI. Healthcare workers in participating facilities collected patient clinical data using a digitized MoH COVID-19 Case Identification Form. We shared aggregated results from these data via (semi-) live dashboards with all relevant stakeholders through their mobile phones. Statistical analyses were performed using Stata 16 to inform project processes. RESULTS Nine private facilities participated in the project. A detailed patient trajectory was developed from case identification to result reporting, all steps supported by a semi-real time digital dashboard. A total of 4,324 PCR tests for SARS-CoV-2 (16%) were added to the public response, identifying 425 positives. Geo-mapped and time-tagged information on incident cases was depicted on Google maps dashboards and fed back to policymakers for informed rapid decision making. Preferential COVID-19 testing was performed on health workers at risk, with 1,009 tested (43% of all County health workforce). CONCLUSION We demonstrate feasibility of rapidly increasing the public health sector response to a COVID-19 epidemic outbreak in an African setting. Our PPP intervention in Kisumu, Kenya was based on a joint testing strategy and demonstrated that semi-real time digitalization of patient trajectories in the healthcare system can gain significant efficiencies, linking public and private healthcare efforts, increasing transparency, support better quality health services and informing policy makers to target interventions. This PPP has since scaled to 33 facilities in Kisumu and subsequently to 84 sites in 14 western Kenyan Counties.
Subject(s)
COVID-19 , HIV InfectionsABSTRACT
BackgroundLow- and middle-income countries (LMICs) are increasingly adopting low-cost Coronavirus disease 2019 (COVID-19) rapid antigen tests to meet the high demand for SARS-CoV-2 testing. Whilst testing using real-time polymerase chain reaction (RT-PCR) is the current gold standard, its widespread use in LMICs is limited by high costs, turnaround times and is not readily available in most places. COVID-19 antigen tests (Ag-RDT) provide a suitable alternative due to their low cost, rapid turnaround time and easy to set up and use. This study aimed to assess the field performance of the NowCheck COVID-19 antigen kit (Ag-RDT) as a point of care test (POCT) in select healthcare facilities in western Kenya. MethodsWe conducted a prospective multi-facility field evaluation study of the NowCheck COVID-19 rapid antigen test (Ag-RDT) compared to SARS-CoV-2 RT-PCR (RT-PCR). After obtaining informed consent, trained laboratory technicians collected two pairs of oropharyngeal and nasopharyngeal swabs, both antigen and RT-PCR testing, first for Ag-RDT and next for RT-PCR. We performed Ag-RDTs on-site and shared the results with both the study participants and their healthcare providers within 15-30 minutes. We carried out all RT-PCR tests in a central referral laboratory. The turnaround time for RT-PCR results was typically 24-48 hours. We captured the results of both methods using an electronic digital application. FindingsBetween December 2020 and March 2021, we enrolled 997 participants who met the Kenyan Ministry of Health COVID-19 case definition. The median age of study participants was 39 years (range one to 80 years), with 54% male. Ag-RDT had a sensitivity of 84.5% (76.0-90.8) and a specificity of 94.4% (95% CI: 92.7-95.8) with an accuracy of 94.2% (92.5-95.6) when a cycle threshold value (Ct value) of [≤]35 was used. The highest sensitivity of 87.7% (77.2-94.5) was observed in samples with Ct values [≤] 30 and the highest specificity of 97.5% (96.2-98.5) at Ct value of <40. InterpretationThe NowCheck COVID-19 Ag-RDT showed good performance in field evaluation in multiple healthcare facilities in a developing country. The sensitivity of the kit exceeded the minimum recommended cut-off of 80% as recommended by WHO1. The high specificity of this kit at 94.4% at Ct values [≤]33 and 97.5% at Ct values <40 matched that of real-time PCR, making it a good rule-out test for symptomatic patients with COVID-19-like symptoms. The faster turnaround time to results, lower cost, simple analytical steps requiring no equipment or infrastructure makes antigen testing an attractive field-screening method to meet the high demand for COVID-19 testing. FundingAchmea Foundation, Pfizer Foundation, Dimagi and the Netherlands Ministry of Foreign Affairs supported this project. The funding sources did not have any role in study design, data collection, analysis, interpretation, summarizing the data or decision to submit the manuscript for publication.