Preprint
Article

A Hybrid Modelling Technique of Epidemic Outbreaks With Application to COVID-19 Dynamics in West Africa

Submitted:

03 March 2021

Posted:

04 March 2021

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A peer-reviewed article of this preprint also exists.

Abstract
The widely used logistic model for epidemic case reporting data may be either restrictive or unrealistic in presence of containment measures when implemented after an epidemic outbreak. For flexibility in epidemic case reporting data modelling, we combined an exponential growth curve for the early epidemic phase with a exible growth curve to account for the potential change in growth pattern after implementation of containment measures. We also fitted logistic regression models to recoveries and deaths from the confirmed positive cases. In addition, the growth curves were integrated in a SIQKU (Susceptible, Infective, Quarantined, Known recovered, Unknown recovered) model framework to provide an overview on the modelled epidemic wave. We focused on the estimation of: (1) the delay between the appearance of the first infectious case in the population and the outbreak ("epidemic latency period"); (2) the duration of the exponential growth phase; (3) the basic and the time-varying reproduction numbers; and (4) the peaks (time and size) in confirmed positive cases, active cases and new infections. The application of this approach to COVID-19 data from West Africa allowed to discuss the e ectiveness of some containment measures implemented across the region.
Keywords: 
Growth model; Epidemic latency period; Reproduction number; West Africa
Subject: 
Computer Science and Mathematics  -   Algebra and Number Theory
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.

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