The research work on transfer function modelling of COVID-19 pandemic in Nigeria purposely describes and adequately model the daily cases of COVID-19 from April to August 2020. The study yields a theoretical and empirical knowledge on the disease with univariate transfer function model and ARIMA (2, 1, 3) model. The fitted transfer function and ARIMA model is adequate for the study. The augmented Dick-Fuller (ADF) unit root test was used to test the stationarity of the series. The residual plot of the series shows adequacy of the fitted model. The study provides an estimate of the parameters via the transfer function which yields forecast value of 200 days of increasing daily cases. The study recommends the use of preventive measures stated here as non-adherence to increase the number of cases. An appropriate transfer function model was specified and its parameters were estimated. The choice of the best model is based on the model selection criteria application to the research. The univariate transfer function model is the best model for describing the COVID-19 pandemic in Nigeria. Evidently, from the forecast values, there exists a gradual increase of the cases of coronavirus in Nigeria as days go by. This is as a result of non-compliance to the preventive measures put in place by government and related agencies.
Abdulaziz, G.M., Faith, A.A.S., Ashaikh, A.A. and Salem, A.Z. (2020). A transfer function technique for modelling Sudanese agricultural exports, International Journal of Current Research,12 (9), 13699-13705.
Adhikari, S.P., Meng, S., Wu, Y.J., Mao, Y.P., Ye, R.X., Wang, Q.Z., Sun, C., Sylvia, S., Rozelle, S. and Raat, H. (2020). Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (Covid-19) during the early outbreak period: A scoping review, Infect. Dis. Poverty, 9, 29.
Amzat, J. (2011). Health inequality in Nigeria, In: Ogundiya IS, Olutayo A O, Amzat J. (eds),Assessment of democratic trends in Nigeria, Gyan Publishing House, New Delhi, 313-322.
Andres, H.M. and Hector, P.M. (2020). Forecasting of Covid-19 per regions using ARIMA models and polynomial functions, Applied Soft Computing Journal, 96, 1568-4946.
Antonio, G.–F. (2020). Forecasting Covid-19 daily outcomes in Spain with simple transfer function models, Coronavirus resource center of the John Hopkins University, International Journal of Forecasting.
Arumugam, P. and Anithakumari, V. (2013). Seasonal time series and transfer function modeling for natural rubber forecasting in India, International Journal of Computer Trends and Technology, 4, 1366 – 1369.
Box, G.E.P., Jenkins, G.M. (1976). Time series analysis forecasting and control, 5th ed, John Wiley & Sons, Hoboken, N.J.
Brodin, P. (2020). Why is Covid-19 so mild in children? Acta paediatr. DOI:10.1111/apa.15271.
Dickey, D.A. and Fuller, W.A. (1969). Distribution of the estimators for autoregressive time series with a unit root, Journal of the American Statistical Association. 74, 427 – 431.
Hasan, A., Susanto, H., Venansius, R.T., Rudy, K. (2020). A new estimation method for Covid-19 time-varying reproduction number using active cases,
Lai C.C., Liu, Y.H., Wang, C.Y., Wang, Y.H., Hsueh, S.C., Yen, M.Y., KO W.C. and Hsueh, P.R. (2020). A symptomatic carrier state, acute respiratory disease, and pneumonia due to severe acute respirator syndrome coronavirus 2 (SARS COV-2): Facts and myths, J. Microbial. Immunol. Infect., 53(3), 404-412.
Linlin, Z., Jasper, M.; Zhansheng, L.; Huiwang, Z. (2019). Transfer function analysis: modelling residential building cost in New Zealand by including influences of house price and work volume, Buildings, 9(6), 152-167.
Livio F., (2020). Forecasting the Covid-19 diffusion in Italy and the related occupancy of intensive care units, Journal of probability and statistics, 2021, DOI:
Marbot, O. (2020). Coronavirus Africa Map: which countries are most at risk? http://www.theafricareport.com/23948/coronavirus-africa-which-countries-are-mostat-risk/.
Makoni, M. (2020). Africa prepares for coronavirus, National Library of Medicine, 395(10223), 483. DOI: https://doi: 10.1016/S0140-6736(20)30355-X.
NCDC (2020). Coronavirus disease (Covid-19). http//covid-19.ncdc.gov.ng/.
Nwafor, G.O, Etuk. E.H., Emeka, A. (2018). Multivariate transfer function modeling: an application, Research Journal of Mathematics. Vol. 5(5), 2349-5375.
Okyay, R.A.; Sahin, A.R.; Ayuinada, R.A.; Tasdogan, A.M. (2020) Why are children less affected by Covid-19? Could there be an over looked bacteria co-infection? Eurasia J.Med. Oncol., 4, 104-105
Mellodge, P. (2016). A practical approach to dynamical systems for Engineers, Woodhead publishing, Swanston, Cambridge
Peng, X., Xu, X., Li, Y., Cheng, L., Zhou, X., Ren, B. (2020). Transmission routes of 2019 –nCov and controls in dental practice, Int. J. Oral Sci, 12.
Pullano, G., Pinotti, F., Valdona, E., Boelle, P.Y., Polletto, C. and Colizza, V. (2020). Novel coronavirus (2019- nCov) early state importation risk to Europe, Euro Surveillence,25(4). DOI: https://doi.org/10.2807/1560-7917.ES.2020.25.4.2000057.
Rediat, T. (2020). Stochastic for predicting covid-19 prevalence in East Africa countries Infectious disease modelling, 5,598-607.
Resa, S.P., Solichatus, Z., Yuyun, H., Ralu, A., Nabila, M.J. and Sukono, S. (2020). Covid-19 modelling in South Korea using A time series approach, International journal of advanced science and technology, 29(7), 1620 – 1632.
Roussel, Y., Giraud – Gatineau, A., Jimeno, M.T., Rolain, J.M., Zandotti, C., Colson, P. and Raoult, D. (2020). SARS – Cov-2: fear versus data, Int. J. Antimicrob, Agents, 55(5), 105947. DOI: 10.1016/j.ijantimicag.2020.105947.
Saikhu, A. Hudiyanti, C.V., Buliali J.L. and Hariad. V. (2021). Predicting Covid-19 confirmed cases in Surabaya using autoregressive integrated moving average, Bivariate and Multivariate transfer function, IOP Conference Series: Materials Science and Engineering, DOI:10.1088/1757-899X/1077/1/012055.
Saswat, S., Chandreyee, C. and Sarmistha, N. (2021). Time series analysis of Covid-19 Data to study the effect of Lockdown and unlock in India, Journal of the institution of Engineers, Series B, 102, 1275–1281.
WHO (2019). WHO supports one million malnourished children in North–East Nigeria, WHO: Geneva, Switzerland.
World Health Organization (2020). Coronavirus disease 2019 (Covid-19) situation report37.2020.
SHARE WITH OTHERS