Modeling and forecasting of the under-five mortality rate in Kermanshah province in Iran: a time series analysis.
- Author:
Mehran ROSTAMI
1
;
Abdollah JALILIAN
;
Behrooz HAMZEH
;
Zahra LAGHAEI
Author Information
- Publication Type:Original Article
- Keywords: Fourth Millennium Development Goal; Infant mortality; Time series; Seasonal auto-regressive integrated moving average model; Iran
- MeSH: Data Collection; Forecasting*; Health Facilities; Humans; Infant; Infant Mortality; Iran*; Mortality*; Patient Selection; Periodicity; Public Health; Seasons
- From:Epidemiology and Health 2015;37(1):e2015003-
- CountryRepublic of Korea
- Language:English
- Abstract: OBJECTIVES: The target of the Fourth Millennium Development Goal (MDG-4) is to reduce the rate of under-five mortality by two-thirds between 1990 and 2015. Despite substantial progress towards achieving the target of the MDG-4 in Iran at the national level, differences at the sub-national levels should be taken into consideration. METHODS: The under-five mortality data available from the Deputy of Public Health, Kermanshah University of Medical Sciences, was used in order to perform a time series analysis of the monthly under-five mortality rate (U5MR) from 2005 to 2012 in Kermanshah province in the west of Iran. After primary analysis, a seasonal auto-regressive integrated moving average model was chosen as the best fitting model based on model selection criteria. RESULTS: The model was assessed and proved to be adequate in describing variations in the data. However, the unexpected presence of a stochastic increasing trend and a seasonal component with a periodicity of six months in the fitted model are very likely to be consequences of poor quality of data collection and reporting systems. CONCLUSIONS: The present work is the first attempt at time series modeling of the U5MR in Iran, and reveals that improvement of under-five mortality data collection in health facilities and their corresponding systems is a major challenge to fully achieving the MGD-4 in Iran. Studies similar to the present work can enhance the understanding of the invisible patterns in U5MR, monitor progress towards the MGD-4, and predict the impact of future variations on the U5MR.
