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  Short-term forecasts of the COVID-19 pandemic: a study case of Cameroon

Nkwayep, C. H., Bowong, S., Tewa, J., Kurths, J. (2020): Short-term forecasts of the COVID-19 pandemic: a study case of Cameroon. - Chaos, Solitons and Fractals, 140, 110106.
https://doi.org/10.1016/j.chaos.2020.110106

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 Creators:
Nkwayep, C. Hameni1, Author
Bowong, S.1, Author
Tewa, J.J.1, Author
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: In this paper, an Ensemble of Kalman filter (EnKf) approach is developed to estimate unmeasurable state variables and unknown parameters in a COVID-19 model. We first formulate a mathematical model for the dynamic transmission of COVID-19 that takes into account the circulation of free coronaviruses in the environment. We provide the basic properties of the model and compute the basic reproduction number that plays an important role in the outcome of the disease. After, assuming continuous measurement of newly COVID-19 reported cases, deceased and recovered individuals, the EnKf approach is used to estimate the unmeasured variables and unknown COVID-19 transmission rates using real data of the current COVID-19 pandemic in Cameroon. We present the forecasts of the current pandemic in Cameroon and explore the impact of non-pharmaceutical interventions such as mass media-based sensitization, social distancing, face-mask wearing, contact tracing and the desinfection and decontamination of infected places by using suitable products against free coronaviruses in the environment in order to reduce the spread of the disease. Through numerical simulations, we find that at that time (i) meaning that the disease will not die out without any control measures, (ii) the infection from COVID-19 infected cases is more important than the infection from free coronaviruses in the environment, (iii) the number of new COVID-19 cases will still increase and there is a necessity to increase timely the surveillance by using contact tracing and sensibilisation of the population to respect social distancing, face-masks wearing through awareness programs and (iv) the eradication of the pandemic is highly dependent on the control measures taken by governments.

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 Dates: 2020-11-15
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.chaos.2020.110106
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Regional keyword: Africa
Model / method: Nonlinear Data Analysis
Research topic keyword: Health
Research topic keyword: Nonlinear Dynamics
Working Group: Network- and machine-learning-based prediction of extreme events
 Degree: -

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Title: Chaos, Solitons and Fractals
Source Genre: Journal, SCI, Scopus, p3
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Publ. Info: -
Pages: - Volume / Issue: 140 Sequence Number: 110106 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/190702
Publisher: Elsevier