Prediction of COVID-19 Pandemic in Nigeria using Time SeriesModels Approach

Ikuomola, Aderonke J.

dc.contributor.author	Ikuomola, Aderonke J.
dc.date.accessioned	2024-09-15T16:22:57Z
dc.date.available	2024-09-15T16:22:57Z
dc.date.issued	2023
dc.identifier.issn	3027-0650
dc.identifier.uri	http://hdl.handle.net/123456789/623
dc.description	Forecasting is the process of predicting future events or occurrences based on previous or present experiences. Alternatively, forecasting uses historical data as the primary input to determine the direction of future trends. A pandemic is "an epidemic occurring globally, or over a very wide area, crossing international boundaries, and typically affecting a large number of people; examples include Ebola, Lassa fever, cholera, swine flu, the coronavirus disease of 2019 (COVID-19), and the like." Among all known ribonucleic acid (RNA) viruses, coronaviruses have the biggest genomes, which gives the virus more flexibility in accepting and changing genes.	en_US
dc.description.abstract	The problems that arise during a pandemic outbreak include: loss of track of trends by health practitioners, lack of resources to contain the pandemic, poor decision-making, and inability to track the effect of the pandemic on society. As COVID-19 is a threat to human lives, it is important to study the trends and see into the future on damages and ways to either prevent or contain it. In this work, auto-regression integrated moving average (ARIMA) and seasonal auto-regression integrated moving average (SARIMA) time series techniques were used to predict the future trend of the COVID-19 pandemic. The models were implemented using the Python programming language. The ARIMA (2,2,0) and (0,2,0) models were finally selected based on the parameter test. It was also used to predict the spread of the COVID-19 pandemic for seven days, and the results show a step-up trend in the spread of COVID-19 in Nigeria within the selected time frame.	en_US
dc.language.iso	en	en_US
dc.publisher	[Department of Computer Science, Olusegun Agagu University of Science and Technology, Okitipupa, Ondo State, Nigeria]	en_US
dc.relation.ispartofseries	American University of Nigeria, 1st International Conference Proceeding;
dc.title	Prediction of COVID-19 Pandemic in Nigeria using Time SeriesModels Approach	en_US
dc.type	Article	en_US