Abstract
Subnational estimates of under-five mortality rates (U5MRs) are a vital statistic for the United Nations to reduce mortality inequalities between high-income and Low-and-Middle Income Countries (LMICs). Current methods of modelling U5MR in LMICs smooth across trends in age and year of death, but not birth-cohort, to reduce uncertainty in estimates caused by data-sparsity. Using survey data from Kenya, we innovatively apply an Age-Period-Cohort model which accounts for spatial trends and the complex survey design of the data to estimate subnational U5MRs in Kenya. After validating our results against current methods, the inclusion of cohort can provide new insights into U5MRs. We ensure our method is flexible and can be applied to other LMICs.
| Original language | English |
|---|---|
| Article number | 100708 |
| Journal | Spatial and Spatio-temporal Epidemiology |
| Volume | 52 |
| Early online date | 13 Dec 2024 |
| DOIs | |
| Publication status | E-pub ahead of print - 13 Dec 2024 |
Data Availability Statement
Data from the DHS is free to download after registration with a suitable project that allows access to the Kenyan dataset specifically. The full code for implementing the APC (and any other) model considered in this paper can be found at https://github.com/connorgascoigne/Subnational-U5MR-with-APC-models.Acknowledgements
The authors would like acknowledge Alana McGovern, Zehang Richard Li and Yunhan Wu for their help with producing the results for the direct estimates, Fay–Herriot estimates and subnational weights for proportional aggregation. Furthermore, the authors are grateful for the insightful suggestions of the two referees and editor who helped improve this manuscript.Keywords
- Age-period-cohort
- Complex surveys
- Space–time smoothing
- Stratified cluster sampling
- Under-five mortality rates
ASJC Scopus subject areas
- Epidemiology
- Geography, Planning and Development
- Infectious Diseases
- Health, Toxicology and Mutagenesis
