Repurposing an integrated national influenza platform for genomic surveillance of SARS-CoV-2 in Ghana: a molecular epidemiological analysis

Background Genomic surveillance of SARS-CoV-2 is crucial for monitoring the spread of COVID-19 and guiding public health decisions, but the capacity for SARS-CoV-2 testing and sequencing in Africa is low. We integrated SARS-CoV-2 surveillance into an existing influenza surveillance network with the aim of providing insights into SARS-CoV-2 transmission and genomics in Ghana. Methods In this molecular epidemiological analysis, which is part of a wider multifaceted prospective observational study, we collected national SARS-CoV-2 test data from 35 sites across 16 regions in Ghana from Sept 1, 2020, to Nov 30, 2021, via the Ghanaian integrated influenza and SARS-CoV-2 surveillance network. SARS-CoV-2-positive samples collected through this integrated national influenza surveillance network and from international travellers arriving in Accra were sequenced with Oxford Nanopore Technology sequencing and the ARTIC tiled amplicon method. The sequence lineages were typed with pangolin and the phylogenetic analysis was conducted with IQ-Tree2 and TreeTime. Findings During the study period, 5495 samples were submitted for diagnostic testing through the national influenza surveillance network (2121 [46·1%] of 4021 samples with complete demographic data were from female individuals and 2479 [53·9%] of 4021 samples were from male individuals). We also obtained 2289 samples from travellers who arrived in Accra and had a positive lateral flow test, of whom 1626 (71·0%, 95% CI 69·1–72·9) were confirmed to be SARS-CoV-2 positive. Co-circulation of influenza and SARS-CoV-2 in Ghana was detected, with increased cases of influenza in November, 2020, November, 2021, and January and June, 2021. In 4124 samples from individuals with influenza-like illness, SARS-CoV-2 was identified in 583 (14·1%, 95% CI 13·1–15·2) samples and influenza in 356 (8·6%, 7·8–9·5). Conversely, in 476 samples from individuals with of severe acute respiratory illness, SARS-CoV-2 was detected in 58 (12·2%, 9·5–15·5) samples and influenza in 95 (19·9%, 16·5–23·9). We detected four waves of SARS-CoV-2 infections in Ghana; each wave was driven by a different variant: B.1 and B.1.1 were the most prevalent lineages in wave 1, alpha (B.1.1.7) was responsible for wave 2, delta (B.1.617.2) and its sublineages (closely related to delta genomes from India) were responsible for wave 3, and omicron variants were responsible for wave 4. We detected omicron variants among 47 (32%) of 145 samples from travellers during the start of the omicron spread in Ghana (wave 4). Interpretation This study shows the value of repurposing existing influenza surveillance platforms to monitor SARS-CoV-2. Influenza continued to circulate in Ghana in 2020 and 2021, and remained a major cause of severe acute respiratory illness. We detected importations of SARS-CoV-2 variants into Ghana, including those that did or did not lead to onward community transmission. Investment in strengthening national influenza surveillance platforms in low-income and middle-income countries has potential for ongoing monitoring of SARS-CoV-2 and future pandemics. Funding The EDCTP2 programme supported by the EU

Energy economics and optimal generation mix of selected power plants technologies in Ghana

Currently most countries in Africa are plagued with a persistent trend of inadequate power supply, which has a ripple effect on all sectors of the economy. Governments needs to expand electricity generation and supply and manage the existing generating facilities efficiently and effectively to make electricity accessible and less expensive. In this study eleven power plant technologies were analyzed in terms of fuel type, fuel cost and carbon dioxide emissions. Economic analysis of each power plant was analyzed. With the help of screening and load-duration curves, the optimum generation mix was determined. The paper therefore concludes that SGT-400 Technology of 80 MW with 3, 6% contribution to the current load should be used as peaking power plant. Orenda OGT25000 Technology of 220 MW rated capacity which contributes 10% to the load should be used for Mid-load generation, while Coal Supercritical Technology of 1500 MW capacity should be used as Base-Load power plant. However, the other technologies considered in the analysis were found to uneconomical and cannot be advice to be used in power generation. Keywords: Power plants, Fuel, Electricity cost, Energy economics, Optimal mi