Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 3 March 2021 / Approved: 4 March 2021 / Online: 4 March 2021 (10:04:14 CET)
Version 2 : Received: 18 March 2021 / Approved: 19 March 2021 / Online: 19 March 2021 (11:22:38 CET)

A peer-reviewed article of this Preprint also exists.

Journal reference: Biology 2021, 10
DOI: 10.3390/biology10050365

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

MATHEMATICS & COMPUTER SCIENCE, Algebra & Number Theory

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