Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: a retrospective genomic study
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kenya
- University of Leuven, Belgium
- Ministry of Health, Kenya
- Uganda Virus Research Institute, Uganda
Abstract
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.
Funding: This work was funded by The Wellcome (grant numbers; 220985, 203077/Z/16/Z, and 222574/Z/21/Z) 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.
Data availability
1) Sequence data have been deposited in GISAID database under accession numbers provided in Supplement File 22) Source Data files have been provided for Figures 1-2 and 4-10.3) Source Code associated with the figures has been uploaded (Source Code File 1) and also been made available through Harvard Dataverse
-
Replication Data for: Genomic surveillance reveals the spread patterns of SARS-CoV-2 in coastal Kenya during the first two wavesHarvard Dataverse, V3, UNF:6:RL6Vg7q0JyS7YoCkjhHe1A== [fileUNF].
-
Genomic epidemiology of SARS-CoV-2 in coastal Kenya (March - July 2020)Github; sars-cov-2-early-phase-manuscript.
Article and author information
Author details
Donwilliams O Omuoyo
Funding
National Institute for Health Research (17/63/82)
- D James Nokes
National Institute for Health Research (16/136/33)
- Charles N Agoti
- Samson Kinyanjui
- George Warimwe
- D James Nokes
- George Githinji
Wellcome Trust (220985)
- D James Nokes
- George Githinji
Wellcome Trust (203077/Z/16/Z)
- Edwine Barasa
- Benjamin Tsofa
- Philip Bejon
Wellcome Trust (220977/Z/20/Z)
- My Phan
- Matthew Cotten
Medical Research Council (NC_PC_19060)
- My Phan
- Matthew Cotten
H2020 European Research Council (n{degree sign}874850)
- Simon Dellicour
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Samples analysed here were collected under the Ministry of Health protocols as part of the national COVID-19 public health response. The whole genome sequencing study protocol was reviewed and approved by the Scientific and Ethics Review Committee (SERU) at Kenya Medical Research Institute (KEMRI), Nairobi, Kenya (SERU protocol #4035). Individual patient consent was not required by the committee for the use of these samples for studies of genomic epidemiology to inform public health response.
Copyright
© 2022, Agoti et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,428
- views
-
- 396
- downloads
-
- 9
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Transmission networks of SARS-CoV-2 in Coastal Kenya during the first two waves: a retrospective genomic study
eLife 11:e71703.
https://doi.org/10.7554/eLife.71703
Further reading
-
- Epidemiology and Global Health
- Genetics and Genomics
Alzheimer’s disease (AD) is a complex degenerative disease of the central nervous system, and elucidating its pathogenesis remains challenging. In this study, we used the inverse-variance weighted (IVW) model as the major analysis method to perform hypothesis-free Mendelian randomization (MR) analysis on the data from MRC IEU OpenGWAS (18,097 exposure traits and 16 AD outcome traits), and conducted sensitivity analysis with six models, to assess the robustness of the IVW results, to identify various classes of risk or protective factors for AD, early-onset AD, and late-onset AD. We generated 400,274 data entries in total, among which the major analysis method of the IVW model consists of 73,129 records with 4840 exposure traits, which fall into 10 categories: Disease, Medical laboratory science, Imaging, Anthropometric, Treatment, Molecular trait, Gut microbiota, Past history, Family history, and Lifestyle trait. More importantly, a freely accessed online platform called MRAD (https://gwasmrad.com/mrad/) has been developed using the Shiny package with MR analysis results. Additionally, novel potential AD therapeutic targets (CD33, TBCA, VPS29, GNAI3, PSME1) are identified, among which CD33 was positively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. TBCA and VPS29 were negatively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. GNAI3 and PSME1 were negatively associated with the main outcome traits of AD, as well as with LOAD, but had no significant causal association with EOAD. The findings of our research advance our understanding of the etiology of AD.
-
- Epidemiology and Global Health
Artificially sweetened beverages containing noncaloric monosaccharides were suggested as healthier alternatives to sugar-sweetened beverages. Nevertheless, the potential detrimental effects of these noncaloric monosaccharides on blood vessel function remain inadequately understood. We have established a zebrafish model that exhibits significant excessive angiogenesis induced by high glucose, resembling the hyperangiogenic characteristics observed in proliferative diabetic retinopathy (PDR). Utilizing this model, we observed that glucose and noncaloric monosaccharides could induce excessive formation of blood vessels, especially intersegmental vessels (ISVs). The excessively branched vessels were observed to be formed by ectopic activation of quiescent endothelial cells (ECs) into tip cells. Single-cell transcriptomic sequencing analysis of the ECs in the embryos exposed to high glucose revealed an augmented ratio of capillary ECs, proliferating ECs, and a series of upregulated proangiogenic genes. Further analysis and experiments validated that reduced foxo1a mediated the excessive angiogenesis induced by monosaccharides via upregulating the expression of marcksl1a. This study has provided new evidence showing the negative effects of noncaloric monosaccharides on the vascular system and the underlying mechanisms.
