Research

A Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting model to predict monthly malaria cases in KwaZulu-Natal, South Africa

O Ebhuoma, M Gebreslasie, L Magubane

Abstract


Background. South Africa (SA) in general, and KwaZulu-Natal (KZN) Province in particular, have stepped up efforts to eliminate malaria. To strengthen malaria control in KZN, a relevant malaria forecasting model is important.

Objectives. To develop a forecasting model to predict malaria cases in KZN using the Seasonal Autoregressive Integrated Moving Average (SARIMA) time series approach.

Methods. The study was carried out retrospectively using a clinically confirmed monthly malaria case dataset that was split into two. The first dataset (January 2005 - December 2013) was used to construct a SARIMA model by adopting the Box-Jenkins approach, while the second dataset (January - December 2014) was used to validate the forecast generated from the best-fit model.

Results. Three plausible models were identified, and the SARIMA (0,1,1)(0,1,1)12 model was selected as the best-fit model. This model was used to forecast malaria cases during 2014, and it was observed to fit closely with malaria cases reported in 2014.

Conclusions. The SARIMA (0,1,1)(0,1,1)12 model could serve as a useful tool for modelling and forecasting monthly malaria cases in KZN. It could therefore play a key role in shaping malaria control and elimination efforts in the province.

 


Authors' affiliations

O Ebhuoma, School of Agricultural, Earth and Environmental Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South Africa

M Gebreslasie, School of Agricultural, Earth and Environmental Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South Africa

L Magubane, School of Agricultural, Earth and Environmental Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South Africa

Full Text

PDF (716KB)

Keywords

SARIMA; Time series; Malaria; Malaria elimination; Forecast; KwaZulu-Natal; South Africa

Cite this article

South African Medical Journal 2018;108(7):573-578. DOI:10.7196/SAMJ.2018.v108i7.12885

Article History

Date submitted: 2018-06-26
Date published: 2018-06-26

Article Views

Abstract views: 3183
Full text views: 1545

Comments on this article

*Read our policy for posting comments here