Peer-reviewed article
Tracking progress towards Sustainable Development Goal 3.2 in Kenya using time series models.
Dlamini WJ, Melesse SF, Mwambi HG ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study uses statistical time series models to project Kenya's under-five mortality rate (UFMR) to 2030. The analysis of data from 1995 to 2022 shows the rate has declined but is slowing. Current trends suggest Kenya will miss the SDG 3.2 target of 25 deaths per 1000 live births, with a projected 2030 rate of 27.8 deaths per 1000. To meet the goal, Kenya would need to accelerate annual declines to roughly 2.43 deaths per 1000 starting in 2023, much faster than recent progress.
Key points
- Kenya's UFMR has significantly decreased over the 27-year study period, but the rate of decline is slowing
- ARIMA statistical model projects the 2030 UFMR at 27.8 deaths per 1000 live births (95% PI: 25.2–30.3), exceeding the SDG 3.2 target of 25
- Kenya would need annual declines of 2.43 deaths per 1000 from 2023 onward to meet the SDG target, far higher than recent trends
- Even the lower bound of the 95% prediction interval (25.2) barely meets the target, indicating high uncertainty
- The authors recommend improved mother and child health services, community interventions, addressing social injustices, and county-specific strategies to accelerate progress
Limitations
This is a modelling study based on historical national-level data and cannot evaluate specific interventions or their impacts on mortality reduction. The projections depend on the quality of historical data and assumptions about future trends, and do not account for potential policy changes or new health initiatives that could alter the trajectory.
Abstract
Background Sustainable Development Goal (SDG) 3.2, which aims to reduce under-five mortality rate (UFMR) below 25 deaths per 1000 live births by 2030, is still a crucial target for improved child survival in sub-Saharan Africa because UFMRs are still high and progress has stalled in recent years. Objective This study aimed to model the possibility of reaching the SDG 3.2 target by 2030 and evaluate trends in under-five mortality in Kenya. Method Three models: autoregressive integrated moving average (ARIMA), autoregressive fractionally integrated moving average (ARFIMA) and hybrid were fitted to annual national under-five mortality data from 1995 to 2022. Automated model selection showed ARIMA (0,2,1) as the best fitting model from information criteria, predictive accuracy and residual diagnostics. The model was tested with mean absolute error, root mean square error, mean absolute percentage error and tested against the 80/20 train-test split. Results Kenya's UFMR has been slightly declining over the course of the study, but the ARIMA projection indicates that the rate of fall is slowing. By 2030, the UFMR is expected to be 27.8 deaths per 1000 live births (95% prediction interval (PI) 25.2 to 30.3), over the SDG 3.2 goal level (signifying an increase in predicted uncertainty). The upper bound of humanity's real 95% PI still far exceeds the aim, even as the lower bound has started to move closer. Kenya would require an accelerated annual decline in roughly 2.43 fatalities per 1000 starting in 2023 much higher than trends seen in the recent past to meet SDG 3.2. Conclusion Kenya's UFMR has significantly decreased; however, the SDG 3.2 target might not be met by 2030 without more initiatives. To accelerate progress, it will be essential to improve mother and child health services, increase community-level interventions, address social injustices and employ more focused county-specific strategies. Using additional high-quality data and improved modelling tools could enhance child mortality monitoring and prediction in the future.