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COVID-19 transmission dynamics underlying epidemic waves in Kenya

Authors :
Kadondi Kasera
James Nyagwange
J. Anthony G. Scott
Samuel Brand
Caroline Mburu
Mark Otiende
John N. Gitonga
Ifedayo M. O. Adetifa
Vincent Were
Matthew James Keeling
Wangari Ng’ang’a
Mercy Mwangangi
Ambrose Agweyu
Nickson Murunga
John Ojal
George Githinji
George M. Warimwe
Sophie Uyoga
Henry K. Karanja
Morris Ogero
Benjamin Tsofa
Lynette Isabella Ochola-Oyier
Edwine Barasa
D. James Nokes
Rabia Aziza
Daisy Mugo
Edward Otieno
Ivy K. Kombe
Emelda A. Okiro
Philip Bejon
Rashid Aman
Patrick Amoth
Charles N. Agoti
Source :
Science (New York, N.Y.)
Publication Year :
2022
Publisher :
American Association for the Advancement of Science, 2022.

Abstract

Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya (∼75% June 1st) have implications for a fourth wave and future control strategies.One Sentence SummaryCOVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure

Details

Language :
English
ISSN :
00368075
Database :
OpenAIRE
Journal :
Science (New York, N.Y.)
Accession number :
edsair.doi.dedup.....943d057ea5b4fc4f2211818ec8e03613
Full Text :
https://doi.org/10.1126/science.abk0414