@article{Adedire_Sadiku_Adedire_Collina_Oladejo_Sikiru_2022, place={Arau, Malaysia}, title={Data Driven Mathematical Models for Forecast of COVID-19 Disease in Nigeria}, volume={7}, url={https://jcrinn.com/index.php/jcrinn/article/view/258}, DOI={10.24191/jcrinn.v7i1.258}, abstractNote={<p>In this research, two mathematical models are proposed for investigation of laboratory confirmed daily COVID-19 disease incidence and total active daily infectious COVID-19 cases using data obtained from Nigeria Centre for Disease Control.  Due to the observed patterns in the raw data, the Autoregressive Integrated Moving Average (ARIMA) method is used on the data which covers a period of 521 days (27 February, 2020-  1st  August 2021).  While diagnostic check of ARIMA (11,1,0) indicate Ljung-BoxQ(18) statistics value of 12.544  with p-value  of 0.084,  diagnostic check of ARIMA(1, 1, 1)  indicate Ljung Box Q(18) statistics value of 22.420 with p-value of 0.130.  Furthermore, stationary R- squared values are 0.803 and 0.858 at 95% confidence bound for ARIMA (11, 1, 0) and ARIMA (1, 1, 1) respectively which are indicative of good models.  Results from ARIMA (11, 1, 0) forecast show a slightly moderate upward trend in confirmed daily COVID-19 incidence in Nigeria and results from ARIMA (1, 1, 1) indicate significant upward trend in total active daily infectious COVID-19 cases in the Nigerian population.  Therefore, the developed models can be adopted by the presidential task force and other agencies in the health sector regarding future vaccination towards prevention of the spread of COVID-19 disease in Nigeria provided that the present general prevailing conditions of disease spread remain fairly the same.</p>}, number={1}, journal={Journal of Computing Research and Innovation}, author={Adedire, Oludare and Sadiku, Yahaya and Adedire, Olufemi. O and Collina, Kambai and Oladejo, Afolabi. O and Sikiru, G.K}, year={2022}, month={Mar.}, pages={1–14} }