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
-
- 1,449
- views
-
- 399
- downloads
-
- 10
- 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
Background:
Biological aging exhibits heterogeneity across multi-organ systems. However, it remains unclear how is lifestyle associated with overall and organ-specific aging and which factors contribute most in Southwest China.
Methods:
This study involved 8396 participants who completed two surveys from the China Multi-Ethnic Cohort (CMEC) study. The healthy lifestyle index (HLI) was developed using five lifestyle factors: smoking, alcohol, diet, exercise, and sleep. The comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera–Doubal method based on longitudinal clinical laboratory measurements, and validation were conducted to select BA reflecting related diseases. Fixed effects model was used to examine the associations between HLI or its components and the acceleration of validated BAs. We further evaluated the relative contribution of lifestyle components to comprehension and organ systems BAs using quantile G-computation.
Results:
About two-thirds of participants changed HLI scores between surveys. After validation, three organ-specific BAs (the cardiopulmonary, metabolic, and liver BAs) were identified as reflective of specific diseases and included in further analyses with the comprehensive BA. The health alterations in HLI showed a protective association with the acceleration of all BAs, with a mean shift of –0.19 (95% CI −0.34, –0.03) in the comprehensive BA acceleration. Diet and smoking were the major contributors to overall negative associations of five lifestyle factors, with the comprehensive BA and metabolic BA accounting for 24% and 55% respectively.
Conclusions:
Healthy lifestyle changes were inversely related to comprehensive and organ-specific biological aging in Southwest China, with diet and smoking contributing most to comprehensive and metabolic BA separately. Our findings highlight the potential of lifestyle interventions to decelerate aging and identify intervention targets to limit organ-specific aging in less-developed regions.
Funding:
This work was primarily supported by the National Natural Science Foundation of China (Grant No. 82273740) and Sichuan Science and Technology Program (Natural Science Foundation of Sichuan Province, Grant No. 2024NSFSC0552). The CMEC study was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305, 2017YFC0907300). The sponsors had no role in the design, analysis, interpretation, or writing of this article.
-
- Epidemiology and Global Health
- Microbiology and Infectious Disease
Background:
In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.
Methods:
We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).
Results:
275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.
Conclusions:
In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.
Funding:
This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).
