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

Author:

Agoti Charles N12ORCID,Ochola-Oyier Lynette Isabella1,Dellicour Simon34ORCID,Mohammed Khadija Said1,Lambisia Arnold W1,de Laurent Zaydah R1,Morobe John M1ORCID,Mburu Maureen W1,Omuoyo Donwilliams O1ORCID,Ongera Edidah M1,Ndwiga Leonard1,Maitha Eric5,Kitole Benson5,Suleiman Thani5,Mwakinangu Mohamed5,Nyambu John K5,Otieno John5,Salim Barke5,Musyoki Jennifer1,Murunga Nickson1,Otieno Edward1ORCID,Kiiru John N5,Kasera Kadondi5,Amoth Patrick5,Mwangangi Mercy5,Aman Rashid5,Kinyanjui Samson126,Warimwe George16,Phan My7ORCID,Agweyu Ambrose1,Cotten Matthew78ORCID,Barasa Edwine1,Tsofa Benjamin1ORCID,Nokes D James19ORCID,Bejon Philip16,Githinji George12ORCID

Affiliation:

1. Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme

2. Pwani University

3. Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles

4. Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, University of Leuven

5. Ministry of Health

6. Nuffield Department of Medicine, University of Oxford

7. Medical Research Centre (MRC)/ Uganda Virus Research Institute

8. MRC-University of Glasgow Centre for Virus Research

9. University of Warwick

Abstract

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.

Funder

National Institute for Health and Care Research

Wellcome Trust

Medical Research Council

H2020 European Research Council

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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