Tracking the introduction and spread of SARS-CoV-2 in coastal Kenya.
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ABSTRACT:
SUBMITTER: Githinji G
PROVIDER: S-EPMC8355311 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties following the statewide "Safer at Home" order, which went into effect 25 March 2020. Our results suggest patterns of SARS-CoV-2 transmission may vary substantially even in nearby communities. Understanding these local patterns will enable better targeting of public health interventions.
| S-EPMC7609670 | biostudies-literature
Project description:The rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is manifested by the emergence of an ever-growing pool of genetic lineages. The aim of this study was to analyze the genetic variability of SARS-CoV-2 in Jordan, with a special focus on the UK variant of concern. A total of 579 SARS-CoV-2 sequences collected in Jordan were subjected to maximum likelihood and Bayesian phylogenetic analysis. Genetic lineage assignment was undertaken using the Pango system. Amino acid substitutions were investigated using the Protein Variation Effect Analyzer (PROVEAN) tool. A total of 19 different SARS-CoV-2 genetic lineages were detected, with the most frequent being the first Jordan lineage (B.1.1.312), first detected in August 2020 (n = 424, 73.2%). This was followed by the second Jordan lineage (B.1.36.10), first detected in September 2020 (n = 62, 10.7%), and the UK variant of concern (B.1.1.7; n = 36, 6.2%). In the spike gene region, the molecular signature for B.1.1.312 was the non-synonymous mutation A24432T resulting in a deleterious amino acid substitution (Q957L), while the molecular signature for B.1.36.10 was the synonymous mutation C22444T. Bayesian analysis revealed that the UK variant of concern (B.1.1.7) was introduced into Jordan in late November 2020 (mean estimate); four weeks earlier than its official reporting in the country. In Jordan, an exponential increase in COVID-19 cases due to B.1.1.7 lineage coincided with the new year 2021. The highest proportion of phylogenetic clustering was detected for the B.1.1.7 lineage. The amino acid substitution D614G in the spike glycoprotein was exclusively present in the country from July 2020 onwards. Two Jordanian lineages dominated infections in the country, with continuous introduction/emergence of new lineages. In Jordan, the rapid spread of the UK variant of concern should be monitored closely. The spread of SARS-CoV-2 mutants appeared to be related to the founder effect; nevertheless, the biological impact of certain mutations should be further investigated.
| S-EPMC8000902 | biostudies-literature
Project description:BackgroundDetailed 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.MethodsHere, 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.ResultsDuring 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.ConclusionsOur analysis supports moving COVID-19 control strategies in the region from a focus on international travel to strategies that will reduce local transmission.FundingThis 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.
| S-EPMC9282859 | biostudies-literature
Project description:Understanding why or how the emergence of SARS-CoV-2 variants has occurred and how to control them is crucial as regards the potential of global reopening. To explore and further understand the spatiotemporal dynamics of the B.1.1.7 spread in the 368 districts of Taiwan, a district-level geographic prediction model of the risk of COVID-19 symptom onset has been proposed. It has been found that, (a) the human mobility, epidemic alert measures, and vaccination rates all played an important role in the spatiotemporal heterogeneity of B.1.1.7 transmission; (b) for regions with high human mobility and low vaccination rates, the partial relaxation of entry quarantine measures for specific imported groups would, in fact, lead to a wide spread of B.1.1.7 with a consequent doubling of high-onset-risk areas and together with the overall onset risk, a further increase of more than 20% would occur; (c) compared with the closing of business places and public venues in all districts, both lockdown in those areas of high-onset-risk and the gathered control effects regarding other districts, the control of B.1.1.7 spread would be better enabled by an onset risk reduction of up to 91.36%. Additionally, an increase in the vaccination rate in each district by up to 5-10 times would further reduce the onset risk by 6.07%-62.22%.
| S-EPMC8665480 | biostudies-literature
Project description:In February 2012, the novel respiratory syncytial virus (RSV) group A, genotype ON1, was detected in Kilifi County, coastal Kenya. ON1 is characterized by a 72-nt duplication within the highly variable G gene (encoding the immunogenic attachment surface protein). Cases were diagnosed through surveillance of pneumonia in children at the county hospital. Analysis of epidemiologic, clinical, and sequence data of RSV-A viruses detected over 5 RSV seasons (2010/2011 to 2014/2015) indicated the following: 1) replacement of previously circulating genotype GA2 ON1, 2) an abrupt expansion in the number of ON1 variants detected in the 2014/2015 epidemic, 3) recently accumulation of amino acid substitutions within the ON1 duplicated sequence, and 4) no clear evidence of altered pathogenicity relative to GA2. The study demonstrates the public health importance of molecular surveillance in defining the spread, clinical effects, and evolution of novel respiratory virus variants.
| S-EPMC5324789 | biostudies-literature
Project description:Genomic surveillance of SARS-CoV-2 is paramount for understanding viral dynamics, contributing to disease control. This study analyzed SARS-CoV-2 genomic diversity in Rio Grande do Sul (RS), Brazil, including the first reported case in each Regional Health Coordination and cases from three epidemic peaks. Ninety SARS-CoV-2 genomes from RS were sequenced and analyzed through comparison with SARS-CoV-2 datasets available in GISAID for phylogenetic inference and mutation analysis. Among the first reported cases, we found the following lineages: B.1 (33.3%), B.1.1.28 (26.7%), B.1.1 (13.3%), B.1.1.33 (10.0%), and A (6.7%), evidencing SARS-CoV-2 introduction by both international origin and community-driven transmission. We found predominance of B.1.1.33 (50.0%) and B.1.1.28 (35.0%) during the first epidemic peak (July-August 2020), emergence of P.2 (55.6%) in the second peak (November-December 2020), and massive spread of P.1 and related sequences (78.4%), such as P.1-like-II, P.1.1 and P.1.2 in the third peak (February-April, 2021). Eighteen novel mutation combinations were found among P.1 genomes, and 22 different spike mutations and/or deletions among P.1 and related sequences. This study shows the dispersion of SARS-CoV-2 lineages in Southern Brazil and describes SARS-CoV-2 diversity during three epidemic peaks, highlighting the spread of P.1 and the high genetic diversity of currently circulating lineages. Genomic monitoring of SARS-CoV-2 is essential to guide health authorities' decisions to control COVID-19 in Brazil.
| S-EPMC8595253 | biostudies-literature
Project description: Not available
| S-BSST379 | biostudies-other
Project description:Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.
| S-EPMC8176267 | biostudies-literature
Project description:BackgroundAlthough an increasing body of data reports the detection of SARS-CoV-2 RNA in air, this does not correlate to the presence of infectious viruses, thus not evaluating the risk for airborne COVID-19. Hence there is a marked knowledge gap that requires urgent attention. Therefore, in this systematic review, viability/stability of airborne SARS-CoV-2, SARS-CoV and MERS-CoV viruses is discussed.MethodsA systematic literature review was performed on PubMed/MEDLINE, Web of Science and Scopus to assess the stability and viability of SARS-CoV, MERS-CoV and SARS-CoV-2 on air samples.Results and discussionThe initial search identified 27 articles. Following screening of titles and abstracts and removing duplicates, 11 articles were considered relevant. Temperatures ranging from 20 °C to 25 °C and relative humidity ranging from 40% to 50% were reported to have a protective effect on viral viability for airborne SARS-CoV and MERS-CoV. As no data is yet available on the conditions influencing viability for airborne SARS-CoV-2, and given the genetic similarity to SARS-CoV and MERS-CoV, one could extrapolate that the same conditions would apply. Nonetheless, the effect of these conditions seems to be residual considering the increasing number of cases in the south of USA, Brazil and India, where high temperatures and humidities have been observed.ConclusionHigher temperatures and high relative humidity can have a modest effect on SARS-CoV-2 viability in the environment, as reported in previous studies to this date. However, these studies are experimental, and do not support the fact that the virus has efficiently spread in the tropical regions of the globe, with other transmission routes such as the contact and droplet ones probably being responsible for the majority of cases reported in these regions, along with other factors such as human mobility patterns and contact rates. Further studies are needed to investigate the extent of aerosol transmission of SARS-CoV-2 as this would have important implications for public health and infection-control policies.
| S-EPMC7543729 | biostudies-literature
Project description:Background: Kenya introduced the monovalent Rotarix® rotavirus group A (RVA) vaccine nationally in mid-2014. Long-term surveillance data is important prior to wide-scale vaccine use to assess the impact on disease and to investigate the occurrence of heterotypic strains arising through immune selection. This report presents baseline data on RVA genotype circulation patterns and intra-genotype genetic diversity over a 7-year period in the pre-vaccine era in Kilifi, Kenya, from 2002 to 2004 and from 2010 to 2013. Methods: A total of 745 RVA strains identified in children admitted with acute gastroenteritis to a referral hospital in Coastal Kenya, were sequenced using the di-deoxy sequencing method in the VP4 and VP7 genomic segments (encoding P and G proteins, respectively). Sequencing successfully generated 569 (76%) and 572 (77%) consensus sequences for the VP4 and VP7 genes respectively. G and P genotypes were determined by use of BLAST and the online RotaC v2 RVA classification tool. Results: The most common GP combination was G1P[8] (51%), similar to the Rotarix® strain, followed by G9P[8] (15%) , G8P[4] (14%) and G2P[4] (5%). Unusual GP combinations-G1P[4], G2P[8], G3P[4,6], G8P[8,14], and G12P[4,6,8]-were observed at frequencies of <5%. Phylogenetic analysis showed that the infections were caused by both locally persistent strains as evidenced by divergence of local strains occurring over multiple seasons from the global ones, and newly introduced strains, which were closely related to global strains. The circulating RVA diversity showed temporal fluctuations both season by season and over the longer-term. None of the unusual strains increased in frequency over the observation period. Conclusions: The circulating RVA diversity showed temporal fluctuations with several unusual strains recorded, which rarely caused major outbreaks. These data will be useful in interpreting genotype patterns observed in the region during the vaccine era.
| S-EPMC6464063 | biostudies-literature