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|Title:||Estimating the Under-Five mortality rate using a Bayesian hierarchical time series model||Authors:||Alkema, L.
|Issue Date:||28-Sep-2011||Citation:||Alkema, L., Ann, W.L. (2011-09-28). Estimating the Under-Five mortality rate using a Bayesian hierarchical time series model. PLoS ONE 6 (9) : -. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0023954||Abstract:||Background: Millennium Development Goal 4 calls for a reduction in the under-five mortality rate by two-thirds between 1990 and 2015, which corresponds to an annual rate of decline of 4.4%. The United Nations Inter-Agency Group for Child Mortality Estimation estimates under-five mortality in every country to measure progress. For the majority of countries, the estimates within a country are based on the assumption of a piece-wise constant rate of decline. Methods and Findings: This paper proposes an alternative method to estimate under-five mortality, such that the underlying rate of change is allowed to vary smoothly over time using a time series model. Information about the average rate of decline and changes therein is exchanged between countries using a Bayesian hierarchical model. Cross-validation exercises suggest that the proposed model provides credible bounds for the under-five mortality rate that are reasonably well calibrated during the observation period. The alternative estimates suggest smoother trends in under-five mortality and give new insights into changes in the rate of decline within countries. Conclusions: The proposed model offers an alternative modeling approach for obtaining estimates of under-five mortality which removes the restriction of a piece-wise linear rate of decline and introduces hierarchy to exchange information between countries. The newly proposed estimates of the rate of decline in under-5 mortality and the uncertainty assessments would help to monitor progress towards Millennium Development Goal 4. © 2011 Alkema, Ann.||Source Title:||PLoS ONE||URI:||http://scholarbank.nus.edu.sg/handle/10635/105127||ISSN:||19326203||DOI:||10.1371/journal.pone.0023954|
|Appears in Collections:||Staff Publications|
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