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Modeling Covid-19 Cases in West African Countries: A Comparative Analysis of Quartic Curve Estimation Models and Estimators

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Modeling, Control and Drug Development for COVID-19 Outbreak Prevention

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 366))

Abstract

COVID-19 has remained and continued to be a severe pandemic threatening the present and future health stability of all the countries, the West African Countries inclusive. The challenge to avert the threat by modeling the reported cases in each of these West African Countries becomes needful for future planning and a concern in this book chapter. Consequently, COVID-19 data on daily confirmed and death cases in each of the sixteen (16) countries in West Africa were collected from European Centre for disease prevention and control (www.ecdc.europa.eu) beginning from the first day of its occurrence until 25th September 2020. As at this time, West African counties had recorded 181,376 confirmed cases and 2748 death cases. It is intended to determine and use an appropriate curve estimation statistical model to forecast for the remaining days of the year 2020; and establish the direction of movement of the future forecast values for effective planning. The Quartic Curve Estimation Model with autocorrelated error terms of order 1 (AR (1)) was found useful with some estimators. The best estimator of the model parameters was identified to be either the Cochrane Orcutt or the Hildreth-LU or the Prais-Winsten estimator. There is an upward movement of forecast values of COVID-19 cumulative confirmed cases towards the end of the year 2020 in Burkina Faso, Cape Verde, Code d'Ivoire, Liberia, Mali, Mauritania, Nigeria, Senegal and Sierra Leone. So, the government in these countries needs not to relax in their fight against the spread of COVI-19. Similarly, there is an upward movement of forecast values of COVID-19 cumulative death cases in Benin, Cape Verde, Guinea Bissau, Mali, Mauritania, Nigeria and Togo. So, these countries would need to critically look after their COVID-19 confirmed patients so as not to lose them to death. COVID-19 cases in Gambia, Ghana, Guinea and Niger are expected to flatten out towards the year while they have to be approached with all seriousness in Cape Verde, Mali, Mauritania and Nigeria.

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Authors and Affiliations

  1. Department of Statistics, Federal University of Technology, Akure, Nigeria

    Kayode Ayinde, Hamidu Abimbola Bello, Omokova Mary Attah, Oluwatoyin Kikelomo Bodunwa, Oluwadare Olatunde Ojo, Abayomi Ayodele Akomolafe, Olabimpe Bodunde Aladeniyi & Emmanuel Idowu Olamide

  2. Department of Statistics, University of Abuja, Abuja, Nigeria

    Rauf Ibrahim Rauf & Samuel Olayemi Olanrewaju

  3. Department of Statistics, Federal University of Technology, Owerri, Nigeria

    Ugochinyere Ihuoma Nwosu

  4. Department of Computer Science, Landmark University, Omu Aran, Nigeria

    Roseline Oluwaseun Ogundokun

  5. Department of Mathematics and Statistics, Federal Polytechnic Ado Ekiti, Ekiti, Nigeria

    Taiwo Stephen Fayose

  6. Department of Mathematics and Statistics, Federal Polytechnic Ilaro, Ilaro, Nigeria

    Rasaki Yinka Akinbo

  7. Department of Statistics, University of Ilorin, Ilorin, Nigeria

    Adebowale Olusola Adejumo

  8. Department of Community Health and Primary Care, College of Medicine, University of Lagos, Lagos, Nigeria

    Oluwatosin Akinsola

  9. Olabisi Onabanjo University, Ago-Iwoye, Nigeria

    Timothy Olabisi Olatayo

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  1. Kayode Ayinde
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Correspondence to Kayode Ayinde .

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  1. Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt

    Ahmad Taher Azar

  2. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Ayinde, K. et al. (2022). Modeling Covid-19 Cases in West African Countries: A Comparative Analysis of Quartic Curve Estimation Models and Estimators. In: Azar, A.T., Hassanien, A.E. (eds) Modeling, Control and Drug Development for COVID-19 Outbreak Prevention. Studies in Systems, Decision and Control, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-030-72834-2_12

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