Longitudinal Epidemiology and Variant Dynamics of SARS-CoV-2 in Coastal Kenya (2020 - 2025): Clinical Features and Wave Patterns

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Background SARS-CoV-2 is a major cause of outpatient attended acute respiratory infections (ARI). Data from Africa on SARS-CoV-2 infection, variants, symptom profile and longitudinal trends for outpatient presentation is limited. Methods Starting December 2020, we established an ARI surveillance at five outpatient clinics in coastal Kenya, recruiting ~15 participants (any age) per week per clinic for SARS-CoV-2 testing and genome analysis. Participants provided respiratory samples, demographic details, vaccination and symptoms data. We compared SARS-CoV-2 clinical and molecular epidemiology pre- and during Omicron waves using multivariable logistic regression. Results By February 2025, we had recruited 14,562 ARI cases, with 1,053 (7.2%) testing positive for SARS-CoV-2. The median age of cases was 25 years (interquartile range: 15-41) and 65.0% were female. Nine infection waves were recorded with positivity ranging 8.2-25.6%. Inter-wave intervals increased from ≤3 months in 2021 to ≥6 months in 2024. 68 PANGO lineages were identified from 782 (74.2%) sequenced cases, with four predominating local waves (AY.116, BQ.1.8, FY.4.1, LF.7.3.2), rare globally (<0.5%). Overall, common symptoms among positive cases were cough (91.5%), nasal discharge (76.7%) and fever (53.1%). Loss of sense of smell was strongly predictive of COVID-19 in the pre-Omicron era, but body malaise, sore throat, joint pains and nasal discharge were predictive during the Omicron period. Conclusion SARS-CoV-2 increasingly shows seasonal annual pattern in coastal Kenya, with its clinical features resembling established endemic respiratory viruses. Its case burden is most pronounced in adults. Locally dominant genetic variants may differ from those globally.

Article activity feed