Multivariate time series modeling of selected childhood diseases in Akwa Ibom State

Abstract

This paper is focused on modeling the five most prevalent childhood diseases in Akwa Ibom State using a multivariate approach to time series. An aggregate of 78,839 reported cases of malaria, upper respiratory tract infection (URTI), Pneumonia, anaemia and tetanus were extracted from five randomly selected hospitals in the State from 1997 to 2011. The monthly Cumulative clinical cases of aforesaid childhood diseases constitute vector time series. Prewhitening approach was employed to determine whether the components of vector series are interrelated so that each series can be predicted on the bases of lagged values of itself and others. This process revealed that except tetanus; malaria, URTI, Pneumonia and anaemia series are interrelated. Hence, the four interrelated time series were considered in the multivariate analysis. Order selection criteria were employed to determine the order of the vector autoregressive (VAR) model to be fitted to these series. It was discovered that VAR(1) model fitted well. Diagnostic checks were applied to ascertain the adequacy of the model and VAR(1) model was found appropriate. Forecasts were generated. The model revealed that upper respiratory tract infection, pneumonia and anaemia are linked to or caused by malaria.

Keywords: Multivariate Approach, Pre-whitening, Vector Time Series, Vector Autoregressive Model, Diagnostic Checks and Forecasts