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Coronavirus Disease-2019 tests require a Nasopharyngeal (NP) and/or Oropharyngeal (OP) specimen from the upper airway, from which virus RNA is extracted and detected through quantitative reverse transcription-Polymerase Chain Reaction (qRT-PCR). The viability of the virus is maintained after collection by storing the NP/OP swabs in Viral Transport Media (VTM). We evaluated the performance of four transport media: locally manufactured ("REVITAL") Viral Transport Media (RVTM), Standard Universal Transport Media (SUTM), PBS and 0.9% (w/v) NaCl (normal saline). We used laboratory cultured virus to evaluate: i) viral recovery and maintaining integrity at different time periods and temperatures; ii) stability in yielding detectable RNA consistently for all time points and conditions; and iii) their overall accuracy. Four vials of SARS-CoV-2 cultured virus (2 high and 2 low concentration samples) and 1 negative control sample were prepared for each media type (SUTM, RVTM, PBS and normal saline) and stored at the following temperatures, -80{degrees}C, 4{degrees}C, room temperature (25{degrees}C) and 37{degrees}C for 7 days. Viral Ribonucleic acid (RNA) extractions and qRT-PCR were done on the following days after inoculation with the cultured virus, days 1, 2, 3, 4 and 7 to assess virus stability and viral recovery. CT values fell over time at room temperature, but normal saline, PBS, RVTM and SUTM all showed comparable performance in maintaining virus integrity and stability allowing for the detection of SARS-CoV-2 viral RNA. Overall, this study demonstrated that normal saline, PBS and the locally manufactured VTM can be used for COVID-19 sample collection and testing, thus expanding the range of SARS-CoV-2 viral collection media.
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BackgroundAnalysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequence data from household infections should aid its detailed epidemiological understanding. Using viral genomic sequence data, we investigated household SARS-CoV-2 transmission and evolution in coastal Kenya households. MethodsWe conducted a case-ascertained cohort study between December 2020 and February 2022 whereby 573 members of 158 households were prospectively monitored for SARS-CoV-2 infection. Households were invited to participate if a member tested SARS-CoV-2 positive or was a contact of a confirmed case. Follow-up visits collected a nasopharyngeal/oropharyngeal (NP/OP) swab on days 1, 4 and 7 for RT-PCR diagnosis. If any of these were positive, further swabs were collected on days 10, 14, 21 and 28. Positive samples with an RT-PCR cycle threshold of <33.0 were subjected to whole genome sequencing followed by phylogenetic analysis. Ancestral state reconstruction was used to determine if multiple viruses had entered households. ResultsOf 2,091 NP/OP swabs that were collected, 375 (17.9%) tested SARS-CoV-2 positive. Viral genome sequences (>80% coverage) were obtained from 208 (55%) positive samples obtained from 61 study households. These genomes fell within 11 Pango lineages and four variants of concern (Alpha, Beta, Delta and Omicron). We estimated 163 putative transmission events involving members of the sequenced households, 40 (25%) of which were intra-household transmission events while 123 (75%) were infections that likely occurred outside the households. Multiple virus introductions (up-to-5) were observed in 28 (47%) households with the 1-month follow-up period. ConclusionsWe show that a considerable proportion of SARS-CoV-2 infections in coastal Kenya occurred outside the household setting. Multiple virus introductions frequently occurred into households within the same infection wave in contrast to observations from high income settings, where single introduction appears to be the norm. Our findings suggests that control of SARS-CoV-2 transmission by household member isolation may be impractical in this setting.
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We generated 274 SARS-CoV-2 genomes from samples collected during the early phase of the Kenyan pandemic. Phylogenetic analysis identified 8 global lineages and at least 76 independent SARS-CoV-2 introductions into Kenyan coast. The dominant B.1 lineage (European origin) accounted for 82.1% of the cases. Lineages A, B and B.4 were detected from screened individuals at the Kenya-Tanzania border or returning travellers but did not lead to established transmission. Though multiple lineages were introduced in coastal Kenya within three months following the initial confirmed case, none showed extensive local expansion other than cases characterised by lineage B.1, which accounted for 45 of the 76 introductions. We conclude that the international points of entry were important conduits of SARS-CoV-2 importations. We speculate that early public health responses prevented many introductions leading to established transmission, but nevertheless a few undetected introductions were sufficient to give rise to an established epidemic.
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BackgroundThe transmission networks of SARS-CoV-2 in sub-Saharan Africa remain poorly understood. MethodsWe undertook phylogenetic analysis of 747 SARS-CoV-2 positive samples collected across six counties in coastal Kenya during the first two waves (March 2020 - February 2021). Viral imports and exports from the region were inferred using ancestral state reconstruction (ASR) approach. ResultsThe genomes were classified into 35 Pango lineages, six of which accounted for 79% of the sequenced infections: B.1 (49%), B.1.535 (11%), B.1.530 (6%), B.1.549 (4%), B.1.333 (4%) and B.1.1 (4%). Four identified lineages were Kenya specific. In a contemporaneous global subsample, 990 lineages were documented, 261 for Africa and 97 for Eastern Africa. ASR analysis identified >300 virus location transition events during the period, these comprising: 69 viral imports into Coastal Kenya; 93 viral exports from coastal Kenya; and 191 inter-county import/export events. Most international viral imports (58%) and exports (92%) occurred through Mombasa City, a key touristic and commercial Coastal Kenya center; and many occurred prior to June 2020, when stringent local COVID-19 restriction measures were enforced. After this period, local virus transmission dominated, and distinct local phylogenies were seen. ConclusionsOur analysis supports moving control strategies from a focus on international travel to local transmission. FundingThis work was funded by Wellcome (grant#: 220985) and the National Institute for Health Research (NIHR), project references: 17/63/and 16/136/33 using UK aid from the UK Government to support global health research, The UK Foreign, Commonwealth and Development Office.
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Seychelles, an archipelago of 155 islands in the Indian Ocean, had confirmed 24,788 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the 31st December 2021. The first SARS-CoV-2 cases in Seychelles were reported on the 14th of March 2020, but cases remained low until January 2021, when a surge of SARS-CoV-2 cases was observed on the islands. Here, we investigated the potential drivers of the surge by genomic analysis 1,056 SARS-CoV-2 positive samples collected in Seychelles between 14th March 2020 and 31st December 2021. The Seychelles genomes were classified into 32 Pango lineages, 1,042 of which fell within four variants of concern i.e., Alpha, Beta, Delta and Omicron. Sporadic cases of SARS-CoV-2 detected in Seychelles in 2020 were mainly of lineage B.1 (European origin) but this lineage was rapidly replaced by Beta variant starting January 2021, and which was also subsequently replaced by the Delta variant in May 2021 that dominated till November 2021 when Omicron cases were identified. Using ancestral state reconstruction approach, we estimated at least 78 independent SARS-CoV-2 introduction events into Seychelles during the study period. Majority of viral introductions into Seychelles occurred in 2021, despite substantial COVID-19 restrictions in place during this period. We conclude that the surge of SARS-CoV-2 cases in Seychelles in January 2021 was primarily due to the introduction of more transmissible SARS-CoV-2 variants into the islands.
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BackgroundFew studies have assessed the seroprevalence of antibodies against SARS-CoV-2 among Health Care Workers (HCWs) in Africa. We report findings from a survey among HCWs in three counties in Kenya. MethodsWe recruited 684 HCWs from Kilifi (rural), Busia (rural) and Nairobi (urban) counties. The serosurvey was conducted between 30th July 2020 and 4th December 2020. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using Bayesian modeling to account for assay performance. ResultsCrude overall seroprevalence was 19.7% (135/684). After adjustment for assay performance seroprevalence was 20.8% (95% CI 17.5-24.4%). Seroprevalence varied significantly (p<0.001) by site: 43.8% (CI 35.8-52.2%) in Nairobi, 12.6% (CI 8.8-17.1%) in Busia and 11.5% (CI 7.2-17.6%) in Kilifi. In a multivariable model controlling for age, sex and site, professional cadre was not associated with differences in seroprevalence. ConclusionThese initial data demonstrate a high seroprevalence of antibodies to SARS-CoV-2 among HCWs in Kenya. There was significant variation in seroprevalence by region, but not by cadre.
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Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks. One-Sentence SummaryExpanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.