5 research outputs found

    Tracking the introduction and spread of SARS-CoV-2 in coastal Kenya

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    Genomic surveillance of SARS-CoV-2 is important for understanding both the evolution and the patterns of local and global transmission. Here, we generated 311 SARS-CoV-2 genomes from samples collected in coastal Kenya between 17th March and 31st July 2020. We estimated multiple independent SARS-CoV-2 introductions into the region were primarily of European origin, although introductions could have come through neighbouring countries. Lineage B.1 accounted for 74% of sequenced cases. Lineages A, B and B.4 were detected in screened individuals at the Kenya-Tanzania border or returning travellers. Though multiple lineages were introduced into coastal Kenya following the initial confirmed case, none showed extensive local expansion other than lineage B.1. International points of entry were important conduits of SARS-CoV-2 importations into coastal Kenya and early public health responses prevented established transmission of some lineages. Undetected introductions through points of entry including imports from elsewhere in the country gave rise to the local epidemic at the Kenyan coast

    Transmission networks of SARS-CoV-2 in coastal Kenya during the first two waves : a retrospective genomic study

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    Background: Detailed understanding on SARS-CoV-2 regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. Methods: Here, we analysed 1,139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction and virus dispersal between counties were estimated using discrete phylogeographic analysis. Results: During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; nine of which occurred in both waves, and four seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1 and N.8). Most of the sequenced infections belonged to lineage B.1 (n=723, 63%) which predominated in both Wave 1 (73%, followed by lineages N.8 (6%) and B.1.1 (6%)) and Wave 2 (56%, followed by lineages B.1.549 (21%) and B.1.530 (5%). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many COVID-19 government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. Conclusions: Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission

    Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: a retrospective genomic study

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    Background: Detailed understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) regional transmission networks within sub-Saharan Africa is key for guiding local public health interventions against the pandemic. Methods: Here, we analysed 1139 SARS-CoV-2 genomes from positive samples collected between March 2020 and February 2021 across six counties of Coastal Kenya (Mombasa, Kilifi, Taita Taveta, Kwale, Tana River, and Lamu) to infer virus introductions and local transmission patterns during the first two waves of infections. Virus importations were inferred using ancestral state reconstruction, and virus dispersal between counties was estimated using discrete phylogeographic analysis. Results: During Wave 1, 23 distinct Pango lineages were detected across the six counties, while during Wave 2, 29 lineages were detected; 9 of which occurred in both waves and 4 seemed to be Kenya specific (B.1.530, B.1.549, B.1.596.1, and N.8). Most of the sequenced infections belonged to lineage B.1 (n = 723, 63%), which predominated in both Wave 1 (73%, followed by lineages N.8 [6%] and B.1.1 [6%]) and Wave 2 (56%, followed by lineages B.1.549 [21%] and B.1.530 [5%]). Over the study period, we estimated 280 SARS-CoV-2 virus importations into Coastal Kenya. Mombasa City, a vital tourist and commercial centre for the region, was a major route for virus imports, most of which occurred during Wave 1, when many Coronavirus Disease 2019 (COVID-19) government restrictions were still in force. In Wave 2, inter-county transmission predominated, resulting in the emergence of local transmission chains and diversity. Conclusions: Our analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission. Funding: This work was funded by The Wellcome (grant numbers: 220985, 203077/Z/16/Z, 220977/Z/20/Z, and 222574/Z/21/Z) and the National Institute for Health and Care 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. The views expressed in this publication are those of the author(s) and not necessarily those of the funding agencies

    An optimisation of four SARS-CoV-2 qRT-PCR assays in a Kenyan laboratory to support the national COVID-19 rapid response teams

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    Background: The global COVID-19 outbreak relies on a quantitative real-time polymerase chain reaction (qRT-PCR) for the detection of severe acute respiratory syndrome coronavirus (SARS-CoV-2), to facilitate the roll-out of patient care and infection control measures. There are several qRT-PCR assays with little evidence on their comparability. We report alterations to the developers’ recommendations to sustain the testing capability in our setting, where the supply of testing reagents is limited. Methods: Standards generated from a serially-diluted positive control and previously identified positive/negative samples were used to determine the optimal volumes of the qRT-PCR reagents and to evaluate the validity and performance of four assays: Charité Berlin and European Virus Archive – GLOBAL (EVAg) primer-probe sets, and DAAN and Beijing Genomics Institute (BGI) premixed commercial kits. A multiplex and singleplex RT-PCR kit was used with the two primer-probe sets and the recommended assay volumes of the two premixed kits were altered. Results: In comparison to the multiplex RT-PCR kit, the singleplex RT-PCR kit combined with the primer-probe sets yielded consistent cycle threshold (Ct) values across the different titrations tested. The DAAN premixed kit produced comparable Ct values across the titrations, while the BGI kit showed incomparable Ct values and inconsistent results between batches using the manufacturer’s recommended volumes. Conclusion: We achieved a 2.5-fold and 4-fold increase in the number of tests/kit for the premixed kits and the primer-probe sets, respectively. The primer-probe set assays were reliable and consistent, and we preferred a combination of an EVAg and a Berlin target. Any inconclusive result was repeated by different individuals following the same protocol. DAAN was a consistent and reliable assay even at lower concentrations from the stated recommendations. BGI in contrast, required dilution to improve its performance and was hence an assay that was used in combination with EVAg or Berlin targets.</p

    An optimization of four SARS-CoV-2 qRT-PCR assays in a Kenyan laboratory to support the national COVID-19 rapid response teams

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    Background: The COVID-19 pandemic relies on real-time polymerase chain reaction (qRT-PCR) for the detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), to facilitate roll-out of patient care and infection control measures. There are several qRT-PCR assays with little evidence on their comparability. We report alterations to the developers’ recommendations to sustain the testing capability in a resource-limited setting. Methods: We used a SARS-CoV-2 positive control RNA sample to generate several 10-fold dilution series that were used for optimization and comparison of the performance of the four qRT-PCR assays: i) Charité Berlin primer-probe set, ii) European Virus Archive – GLOBAL (EVAg) primer-probe set, iii) DAAN premixed commercial kit and iv) Beijing Genomics Institute (BGI) premixed commercial kit. We adjusted the manufacturer- and protocol-recommended reaction component volumes for these assays and assessed the impact on cycle threshold (Ct) values. Results: The Berlin and EVAg E gene and RdRp assays reported mean Ct values within range of each other across the different titrations and with less than 5% difference. The DAAN premixed kit produced comparable Ct values across the titrations, while the BGI kit improved in performance following a reduction of the reaction components. Conclusion: We achieved a 2.6-fold and 4-fold increase in the number of tests per kit for the commercial kits and the primer-probe sets, respectively. All the assays had optimal performance when the primers and probes were used at 0.375X, except for the Berlin N gene assay. The DAAN kit was a reliable assay for primary screening of SARS-CoV-2 whereas the BGI kit’s performance was dependent on the volumes and concentrations of both the reaction buffer and enzyme mix. Our recommendation for SARS-CoV-2 diagnostic testing in resource-limited settings is to optimize the assays available to establish the lowest volume and suitable concentration of reagents required to produce valid results
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