About: Forecasting the scale of the COVID-19 epidemic in Kenya

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Forecasting the scale of the COVID-19 epidemic in Kenya
Creator	Kombe, Ivy Agoti, Charles Brand, Samuel Parisi, Andrea Barasa, Edwine »more»
source	MedRxiv
abstract	Background The first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. Methods We developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. Results We find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 - 2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.
has issue date	2020-04-14(xsd:dateTime)
bibo:doi	10.1101/2020.04.09.20059865
has license	medrxiv
sha1sum (hex)	69a305813b49f0445c26970302a60731745798ff
schema:url	https://doi.org/10.1101/2020.04.09.20059865
resource representing a document's title	Forecasting the scale of the COVID-19 epidemic in Kenya
resource representing a document's body	covid:69a305813b49f0445c26970302a60731745798ff#body_text
is schema:about of	named entity 'potential' named entity 'INCIDENCE RATE' named entity 'HERE' named entity 'KENYA' named entity 'CONFIRMED' »more»

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