The Effects of Malaria Control Interventions on Out-patient and In-patient Malaria Cases in the Northern Region of Ghana

Main Article Content

Emmanual Mohammed Dokurugu
Suleman Nasiru
Benson Abdul Majeed


In this study, change detection in Out-patient and In-patient malaria cases in the Northern Region of Ghana was examined using time series intervention analysis. Data on monthly Out-patient and In-patient malaria cases obtained from the Northern Regional Health Directorate were modelled using Seasonal Autoregressive Integrated Moving Average with an Independent variable (SARIMAX) and Autoregressive Integrated Moving Average with an Independent variable (ARIMAX) models. The results revealed that SARIMAX (1, 1, 1)(1, 1, 1)12 was the best model for predicting Out-patient malaria cases while SARIMAX (1, 1, 1)(2, 1, 1)12 emerged as the best model for predicting the In-patient cases in the region. Diagnostic checks of the two models with the Ljung-Box test and Autoregressive Conditional Heteroscedasticity Lagrange Multiplier (ARCH-LM) test revealed that both models were free from higher-order serial correlation and conditional heteroscedasticity respectively. A chi-square goodness-of-fit test also revealed that there was no significant difference between the predicted values from the models and the observed values for the year 2018. The study further revealed that the coefficients of the intervention variable for the Out-patient and In-patient cases were both negative, which suggest that the intervention policy the government of Ghana implemented brought about a decline in the number of Out-patient and In-patient cases in the region.

Out-patient, In-patient, SARIMAX, ARIMAX, ARCH-LM test, intervention.

Article Details

How to Cite
Dokurugu, E. M., Nasiru, S., & Majeed, B. A. (2020). The Effects of Malaria Control Interventions on Out-patient and In-patient Malaria Cases in the Northern Region of Ghana. Asian Journal of Probability and Statistics, 6(3), 61-73.
Original Research Article


Multiple Indicator Cluster Survey Final Report. Ghana Statistical Service; 2012.
[Accessed on 23 February 2018]

Landoh ED, Tchamdja P, Bayaki S, Khin ST, Gitta SN, Wasswa P, de Jager C. Morbidity and mortality due to malaria in Est Mono district, Togo, from 2005 to 2010: A times series analysis. Malaria Journal. 2012;11:389.

Nyarango PM, Gebremeskel T, Mebrahtu G, Mufunda J, Abdulmumini U, Ogbamariam A, et al. A steep decline of malaria morbidity and mortality trends in Eritrea between 2000 and 2004: The effect of combination of control methods. Malaria Journal. 2006;5:33.

Karema C, Aregawi CW, Rukundo A, Kabayiza A, Mulindahabi M, Ibrahima SF, et al. Trends in malaria cases, hospital admissions and deaths following scale-up of anti-malarial interventions, 2000–2010. Rwanda. Malaria Journal. 2012;11:236.

Briet OJT, Amerasingbe PHA, Vounatsou P. Generalized seasonal autoregressive integrated moving average models for count data with application to malaria time series with low case numbers. PLos ONE. 2013;8(6):e65761.

Osadolor E, Gebreslasie M, Magubane L. Modelling malaria control intervention effect in Kwazulu-Natal, South Africa using intervention time series analysis. Journal of Infection and Public Health. 2017;10:334-38.

Anokye R, Acheampong E, Owusu I, Obeng EI. Time series analysis of malaria in Kumasi: Using ARIMA models to forecast future incidence. Cogent Social Sciences. 2018;4:1461544.

Hassan HE, Bin Y. Time series analysis and forecasting model for monthly malaria infection by Box-Jenkins techniques in the Kass Zone, South Darfur State, Sudan. Journal of Scientific and Engineering Research. 2018;5(9):35-42.

Alhassan EA, Adjei MI, Aidoo E. Time series analysis of malaria cases in Kasena Nankana Municipality. ResearchGate. 2017;312574174.

Anwar MY, Lewnard JA, Parikh S, Pitzer V. Time series analysis of malaria in Afghanistan: Using ARIMA models to predict future trends in incidence. Malaria Journal. 2016;15:566.

Ankamah S, Nokoe KS, Iddrisu WA. Modelling trends of climatic variability and malaria in Ghana using vector autoregression. Hindawi; 2018.

Perez EG, Ceballos RF. Malaria incidence in the Philippines: Prediction using autoregressive moving average models. International Journal of Engineering and Future Technology. 2019;16(4):1-10.

Box GEP, Jenkins GM. Time series analysis: Forecasting and control. Holden-Day, San-Francisco; 1976.

Dickey DA, Fuller WA. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica. 1981;49:1057-1072.

Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control. 1974;19(6):716-723.

Eagle RF. Autoregressive conditional heteroscedasticity with estimates of the variance of U.K. inflation. Econometrica. 1982;50:987-1008.

Ljung GM, Box GEP. On a measure of lack of fit time series models. Biometrika. 1978;65:297-303.

Jula D. Introduction in econometrics. Ed. Professional Consulting, Bucuresti; 2003.