Malaria paediatric hospitalization between 1999 and 2008 across Kenya

Abstract

Background: Intervention coverage and funding for the control of malaria in Africa has increased in recent years, however, there are few descriptions of changing disease burden and the few reports available are from isolated, single site observations or are of reports at country-level. Here we present a nationwide assessment of changes over 10 years in paediatric malaria hospitalization across Kenya.

Methods: Paediatric admission data on malaria and non-malaria diagnoses were assembled for the period 1999 to 2008 from in-patient registers at 17 district hospitals in Kenya and represented the diverse malaria ecology of the country. These data were then analysed using autoregressive moving average time series models with malaria and all-cause admissions as the main outcomes adjusted for rainfall, changes in service use and populations-at-risk within each hospital's catchment to establish whether there has been a statistically significant decline in paediatric malaria hospitalization during the observation period.

Results: Among the 17 hospital sites, adjusted paediatric malaria admissions had significantly declined at 10 hospitals over 10 years since 1999; had significantly increased at four hospitals, and remained unchanged in three hospitals. The overall estimated average reduction in malaria admission rates was 0.0063 cases per 1,000 children aged 0 to 14 years per month representing an average percentage reduction of 49% across the 10 hospitals registering a significant decline by the end of 2008. Paediatric admissions for all-causes had declined significantly with a reduction in admission rates of greater than 0.0050 cases per 1,000 children aged 0 to 14 years per month at 6 of 17 hospitals. Where malaria admissions had increased three of the four sites were located in Western Kenya close to Lake Victoria. Conversely there was an indication that areas with the largest declines in malaria admission rates were areas located along the Kenyan coast and some sites in the highlands of Kenya.

Conclusion: A country-wide assessment of trends in malaria hospitalizations indicates that all is not equal, important variations exist in the temporal pattern of malaria admissions between sites and these differences require more detailed investigation to understand what is required to promote a clinical transition across Africa.

Figure 1

Map showing the Location of District hospital sites in Kenya colour coded according to region; Coast (red dots), Western/Lakeside (blue dots), Highlands (green dots) and Semi-Arid areas (yellow dots) and the catchment area for each hospital (light grey areas around each hospital).

Figure 2

Plots of paediatric admission data for malaria (blue line) and non-malaria (red line) and all-cause admissions (black line) at three hospitals in Western/Lakeside Region (Busia, Bungoma and Bondo) expressed per 1,000 children aged 0 to 14 years at risk per annum and 95% confidence intervals presented as aggregated data in three time periods: 1999 to 2002, 2003 to 2005 and 2006 to 2008 (Left panels). Model predictions of all-cause rates controlling for lagged rainfall (dotted blue line) and malaria hospitalization rates controlling for lagged rainfall and non-malaria cases and controlling for autoregressive and moving average effects (solid black line). Fitted lines illustrate the linear trends from model predictions (dashed line) (right panel).

Figure 3

Plots of paediatric admission data for malaria (blue line) and non-malaria (red line) and all-cause admissions (black line) at three hospitals in Western/Lakeside Region (Homa Bay, Kisumu, Siaya) expressed per 1,000 children aged 0 to 14 years at risk per annum and 95% confidence intervals presented as aggregated data in three time periods: 1999 to 2002, 2003 to 2005 and 2006 to 2008 (Left panels). Model predictions of all-cause rates controlling for lagged rainfall (dotted blue line) and malaria hospitalization rates controlling for lagged rainfall and non-malaria cases and controlling for autoregressive and moving average effects (solid black line). Fitted lines illustrate the linear trends from model predictions (dashed line) (right panel).

Figure 4

Plots of paediatric admission data for malaria (blue line) and non-malaria (red line) and all-cause admissions (black line) at three hospitals in the Highlands (Kericho, Kisii, Kitale) expressed per 1,000 children aged 0 to 14 years at risk per annum and 95% confidence intervals presented as aggregated data in three time periods: 1999 to 2002, 2003 to 2005 and 2006 to 2008 (Left panels). Model predictions of all-cause rates controlling for lagged rainfall (dotted blue line) and malaria hospitalization rates controlling for lagged rainfall and non-malaria cases and controlling for autoregressive and moving average effects (solid black line). Fitted lines illustrate the linear trends from model predictions (dashed line) (right panel).

Figure 5

Plots of paediatric admission data for malaria (blue line) and non-malaria (red line) and all-cause admissions (black line) at three hospitals in on the Kenya coast (Kilifi, Malindi, Msambweni) expressed per 1,000 children aged 0 to 14 years at risk per annum and 95% confidence intervals presented as aggregated data in three time periods: 1999 to 2002, 2003 to 2005 and 2006 to 2008 (Left panels). Model predictions of all-cause rates controlling for lagged rainfall (dotted blue line) and malaria hospitalization rates controlling for lagged rainfall and non-malaria cases and controlling for autoregressive and moving average effects (solid black line). Fitted lines illustrate the linear trends from model predictions (dashed line) (right panel).

Figure 6

Plots of paediatric admission data for malaria (blue line) and non-malaria (red line) and all-cause admissions (black line) at three hospitals in the Arid/Semi Arid Region (Narok, Hola, Voi) expressed per 1,000 children aged 0 to 14 years at risk per annum and 95% confidence intervals presented as aggregated data in three time periods: 1999 to 2002, 2003 to 2005 and 2006 to 2008 (Left panels). Model predictions of all-cause rates controlling for lagged rainfall (dotted blue line) and malaria hospitalization rates controlling for lagged rainfall and non-malaria cases and controlling for autoregressive and moving average effects (solid black line). Fitted lines illustrate the linear trends from model predictions (dashed line) (right panel).

Figure 7

Plots of paediatric admission data for malaria (blue line) and non-malaria (red line) and all-cause admissions (black line) at two hospitals in the Arid/Semi Arid Region (Makueni, Wajir) expressed per 1,000 children aged 0 to 14 years at risk per annum and 95% confidence intervals presented as aggregated data in three time periods: 1999 to 2002, 2003 to 2005 and 2006 to 2008 (Left panels). Model predictions of all-cause rates controlling for lagged rainfall (dotted blue line) and malaria hospitalization rates controlling for lagged rainfall and non-malaria cases and controlling for autoregressive and moving average effects (solid black line). Fitted lines illustrate the linear trends from model predictions (dashed line) (right panel).