The differential effect of the free maternity services policy in Kenya

Background: The Government of Kenya introduced the free maternity services (FMS) policy to enable mothers deliver at a health facility and thus improve maternal health indicators. Aim: The aim of this study was to determine if there was a differential effect of the policy by region (sub-county) and by facility type (hospitals vs. primary healthcare facilities [PHCFs]). Setting: The study was conducted in Nyamira County in western Kenya. Methods: This was an interrupted time series study where 42 data sets (24 pre- and 18 post-intervention) were collected for each observation. Monthly data were abstracted from the District Health Information System-2, verified, keyed into and analysed by using IBM-Statistical Package for the Social Sciences (SPSS-17). Results: The relative effect of thepolicy on facility deliveries in the county was an increase of 22.5%, significant up to the 12th month (p < 0.05). The effect of the policy on deliveries by region was highest in Nyamira North and Masaba North (p < 0.001 up to the 18th month). The effect was larger (46.5% vs. 18.3%) and lasted longer (18 months vs. 6 months) in the hospitals than in the PHCFs. The increase in hospital deliveries was most significant in Nyamira North (61%; p < 0.001). There was a medium-term effect on hospital deliveries in Borabu (up to 9months) and an effect that started in the sixth month in Manga. The relative effect of the policy on facility deliveries in PHCFs was only significant in Nyamira North and Masaba North (p < 0.001). Conclusion: The effect of the FMS policy was varied by region (sub-county) and by facility type

Malaria hotspot areas in a highland Kenya site are consistent in epidemic and non-epidemic years and are associated with ecological factors

"Background: Malaria epidemics in highland areas of East Africa have caused considerable morbidity and mortality in the past two decades. Knowledge of ""hotspot"" areas of high malaria incidence would allow for focused preventive interventions in resource-poor areas; particularly if the hotspot areas can be discerned during non-epidemic periods and predicted by ecological factors. Methods:To address this issue; spatial distribution of malaria incidence and the relationship of ecological factors to malaria incidence were assessed in the highland area of Kipsamoite; Kenya; from 001-2004. Results: Clustering of disease in a single geographic ""hotspot"" area occurred in epidemic and non-epidemic years; with a 2.6 to 3.2-fold increased risk of malaria inside the hotspot; as compared to outside the area (P 0.001; all 4 years). Altitude and proximity to the forest were independently associated with increased malaria risk in all years; including epidemic and non-epidemic years. Conclusion: In this highland area; areas of high malaria risk are consistent in epidemic and non-epidemic years and are associated with specific ecological risk factors. Ongoing interventions in areas of ecological risk factors could be a cost-effective method of significantly reducing malaria incidence and blunting or preventing epidemics; even in the absence of malaria early warning systems. Further studies should be conducted to see if these findings hold true in varied highland settings."