EconPapers    
Economics at your fingertips  
 

Nigerian COVID-19 Incidence Modeling and Forecasting with Univariate Time Series Model

Abass Ishola Taiwo (), Adedayo Funmi Adedotun () and Timothy Olabisi Olatayo ()
Additional contact information
Abass Ishola Taiwo: Olabisi Onabanjo University
Adedayo Funmi Adedotun: Covenant University
Timothy Olabisi Olatayo: Olabisi Onabanjo University

Chapter Chapter 8 in Decision Sciences for COVID-19, 2022, pp 137-150 from Springer

Abstract: Abstract The occurrence of COVID-19 has given rise to dreadful medical difficulties due to its hyper-endemic effects on the human population. This made it fundamental to model and forecast COVID-19 pervasiveness and mortality to control the spread viably. The COVID-19 data used was from February, 28, 2020 to March 1, 2021. ARIMA(1,2,0) was selected for modeling COVID-19 confirmed and ARIMA(1,1,0) for death cases. The model was shown to be adequate for modeling and forecasting Nigerian COVID-19 data based on the ARIMA model building results. The forecasted values from the two models indicated Nigerian COVID-19 cumulative confirmed and death case continues to rise and maybe in-between 189,019–327,426 and interval 406–3043, respectively in the next 3 months (May 30, 2021). The ARIMA models forecast indicated an alarming rise in Nigerian COVID-19 confirmed and death cases on a daily basis. The findings indicated that effective treatment strategies must be put in place, the health sector should be monitored and properly funded. All the protocols and restrictions put in place by the NCDC, Nigeria should be clung to diminish the spread of the pandemic and possible mortality before immunizations that can forestall the infection is developed.

Keywords: COVID-19; ARIMA model; Confirmed cases; Death cases; Modeling; Forecasting (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-87019-5_8

Ordering information: This item can be ordered from
http://www.springer.com/9783030870195

DOI: 10.1007/978-3-030-87019-5_8

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:isochp:978-3-030-87019-5_8