Increasing coverage and decreasing inequity in insecticide-treated bed net use among rural Kenyan children

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Study Justification:
– The study aims to address the limited access to insecticide-treated bed nets (ITNs) among rural Kenyan children, especially those in the poorest sectors.
– It investigates the effectiveness of different delivery models in increasing ITN coverage and reducing socioeconomic inequity.
Highlights:
– The study found that ITN coverage increased from 7.1% in 2004 to 67.3% in 2006 through mass distribution campaigns, heavily subsidized clinic distribution, and commercial social marketing.
– Each subsequent survey showed a decrease in socioeconomic inequity in net coverage, with near-perfect equality achieved in 2006.
– The mass distribution method achieved the highest coverage among the poorest children, while the heavily subsidized clinic nets program slightly favored the least poor, and the commercial social marketing favored the least poor.
Recommendations:
– Rapid scaling up of ITN coverage among Africa’s poorest rural children can be achieved through mass distribution campaigns.
– Efforts should focus on making ITN interventions free to ensure equitable access among those least able to afford even heavily subsidized nets.
– Mass distribution campaigns should be complemented by regular access to ITNs through clinics.
Key Role Players:
– Kenya Ministry of Health
– Private sector retailers
– Non-governmental organizations
– Research teams
– PSI-Kenya (implementing the PSI Coverage Plus program)
– Maternal and Child Health clinics
– Kenya Expanded Programme on Immunization
– The Global Fund to Fight AIDS, TB and Malaria
Cost Items for Planning Recommendations:
– Costs associated with mass distribution campaigns (e.g., procurement and distribution of ITNs)
– Costs of heavily subsidized clinic distribution
– Costs of social marketing and creating a “net culture”
– Costs of providing free ITNs to pregnant women and children under 5 years old
– Costs of research and monitoring programs
– Costs of training and capacity building for healthcare providers and community workers

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it presents repeat observations of ITN coverage among rural Kenyan homesteads exposed to different delivery models. The study includes a cohort of 3,700 children aged 0-4 years in four districts of Kenya and examines changes in coverage across socioeconomic groups. The study provides data on ITN coverage from 2004 to 2006, coinciding with the introduction of different delivery approaches. The study also analyzes the degree of equity in each delivery approach. To improve the evidence, the abstract could include information on the methodology used for data collection and analysis, as well as the limitations of the study.

Background: Inexpensive and efficacious interventions that avert childhood deaths in sub-Saharan Africa have failed to reach effective coverage, especially among the poorest rural sectors. One particular example is insecticide-treated bed nets (ITNs). In this study, we present repeat observations of ITN coverage among rural Kenyan homesteads exposed at different times to a range of delivery models, and assess changes in coverage across socioeconomic groups. Methods and Findings: We undertook a study of annual changes in ITN coverage among a cohort of 3,700 children aged 0-4 y in four districts of Kenya (Bondo, Greater Kisii, Kwale, and Makueni) annually between 2004 and 2006. Cross-sectional surveys of ITN coverage were undertaken coincidentally with the incremental availability of commercial sector nets (2004), the introduction of heavily subsidized nets through clinics (2005), and the introduction of free mass distributed ITNs (2006). The changing prevalence of ITN coverage was examined with special reference to the degree of equity in each delivery approach. ITN coverage was only 7.1% in 2004 when the predominant source of nets was the commercial retail sector. By the end of 2005, following the expansion of heavily subsidized clinic distribution system, ITN coverage rose to 23.5%. In 2006 a large-scale mass distribution of ITNs was mounted providing nets free of charge to children, resulting in a dramatic increase in ITN coverage to 67.3%. With each subsequent survey socioeconomic inequity in net coverage sequentially decreased: 2004 (most poor [2.9%] versus least poor [15.6%]; concentration index 0.281); 2005 (most poor [17.5%] versus least poor [37.9%]; concentration index 0.131), and 2006 with near-perfect equality (most poor [66.3%] versus least poor [66.6%]; concentration index 0.000). The free mass distribution method achieved highest coverage among the poorest children, the highly subsidised clinic nets programme was marginally in favour of the least poor, and the commercial social marketing favoured the least poor. Conclusions: Rapid scaling up of ITN coverage among Africa’s poorest rural children can be achieved through mass distribution campaigns. These efforts must form an important adjunct to regular, routine access to ITNs through clinics, and each complimentary approach should aim to make this intervention free to clients to ensure equitable access among those least able to afford even the cost of a heavily subsidized net. © 2007 Noor et al.

Prior to the launch of Kenya’s National Malaria Strategy in April 2001 [17], access to nets was limited to the private for-profit retail sector and special project-based distributions through research- or nongovernmental organization-led community development initiatives [18]. In 2000 the Kenya Ministry of Health (MoH) developed with partners an ITN strategy paper [19] that attempted to accommodate two competing views on ways to reach the government’s target of 60% coverage of populations at risk by 2005. The first approach included ways to ensure that the ITN market is self-sustaining in the absence of long-term donor support by expanding the private sector through social marketing; the second approach, principally favoured by the MoH, was to provide ITNs free of charge to pregnant women and children under the age of 5 y to achieve rapid scale-up. In January 2002 the UK Department for International Development (DFID) awarded PSI-Kenya US$33 million over 5 y to socially market partially subsidised ITN within the existing retail sector. The programme, named PSI Coverage Plus, was the only major operational ITN distribution initiative between 2002 and 2004 and aimed to target urban and rural retail outlets with Supanet ITNs across all malaria-endemic districts in Kenya. A two-tier pricing system of 350 Kenya Shillings (KES) (equivalent to US$4.7) in urban settings versus KES100 (US$1.3) in rural settings was implemented. The programme’s aims were to increase community awareness of the value of ITNs thus creating a “net culture”; force existing retail prices down; and increase clients’ willingness to pay for nets through a sustainable, unsubsidised commercial market [20]. In June 2004, DFID approved an additional US$19 million to PSI to establish a parallel distribution system of heavily subsidised ITNs to children and pregnant women through Maternal and Child Health (MCH) clinics, recognizing that these vulnerable groups might not be able to access socially marketed commercial sector nets. The programme began in October 2004, and during the first 6 mo Supanet ITNs were bundled with separate Powertab net treatment tablets (for every 6 mo) and distributed to MCH attendees. In May 2005 an additional US$37 million was committed by DFID to PSI to procure and distribute Supanet-branded long-lasting insecticidal nets (LLINs), Olyset and Permanet. These public sector nets were heavily subsidized pretreated nets (KES50; US$0.7) and branded with the MoH logo [20]. In February 2002 the MoH responded to the first call of the Global Fund to Fight AIDS, TB and Malaria (GFATM) for funding applications to secure five million nets and net treatments to provide free of charge to children under the age of 5 y and pregnant women. This application was unsuccessful. During round four of the GFATM awards in April 2004, Kenya’s application was successful and US$17 million was approved to procure and distribute 3.4 million LLINs (Olyset and Permanet brands) free of charge to children under the age of 5 y. This represented, at the time, the largest successful award for free distribution of LLINs in Africa. The implementation of the free mass distribution of LLINs was arranged in two phases during 2006. During the first phase, 21 of Kenya’s 70 districts were selected for distribution of LLINs from 8 to 12 July 2006 and integrated with the national measles catch-up vaccination campaign. Health facilities and centralised non-health facility posts were identified by the Kenya Expanded Programme on Immunisation and used as delivery points of both measles vaccine and LLINs to each child under the age of 5 y. A second mass distribution of LLINs, not integrated with any other intervention, took place from 25 to 27 September 2006 in 24 additional districts using previous mass vaccine campaign delivery centres as distribution points. The study was carried out in four districts purposively sampled in collaboration with the MoH to provide detailed longitudinal milestone data on changing access to interventions proposed within the Kenya National Malaria Strategy between 2001 and 2006 [21,22]. The study districts represent the range of dominant malaria epidemiological situations that prevail across Kenya: Kwale on the coast with seasonal high-intensity malaria transmission; Bondo on the shores of Lake Victoria with perennial high-intensity transmission; Greater Kisii district (combining the new districts of Kisii Central and Gucha) with seasonal low transmission conditions of the Western highlands; and Makueni district, a semi-arid area with acutely seasonal low malaria transmission. Between 63% and 71% of households in the rural areas of each of the four districts were living below the poverty line (equivalent to US$1 per day) in 1999, compared to the national average of 54% [23]. The districts were also representative of rural districts in Kenya with respect to net delivery since 2001, with service providers including the full-cost commercial and social marketing retail sector; a research team in parts of Bondo district [24]; nongovernmental organization delivery to selected communities in Greater Kisii (Merlin and World Vision) and Kwale (Plan International and The Aga Khan Foundation); time-limited MoH provision of free nets to pregnant women in 2001 in all districts [25] and to children and pregnant women in Bondo and Gucha districts in 2005 [26]; and subsidized PSI clinic distribution since October 2004 and mass, free distribution in 2006 across all districts. Within each district, rural enumeration area (EA) boundaries were digitized with ARCGIS 9.0 (ESRI, http://www.esri.com/) and each polygon attributed to population totals derived from the last national census in 1999 [27]. A sample of 18 rural EA polygons, covering approximately 6,500 people per district, was randomly selected from each district to form the basis of the longitudinal community surveillance. Following community sensitisation, all homesteads within an EA polygon were mapped and heads of homesteads were given the purpose of the longitudinal study and asked whether they wished to participate. All de jure resident homestead members were enumerated, including details of date of birth and sex, and issued a unique identifier for follow-up. During December/January of 2004/5, 2005/6, and 2006/7, just after the short rains, a cohort of children under the age of 5 y was established to track, by interviewing mothers or caretakers, the ownership and use of bed nets, including details on the net brand, where and when they were obtained, and whether nets had been treated with an insecticide during the previous 6 mo. Interviewers were instructed to observe the nets and record details of the colour, imprinted logos, and shape of the net to match the net types delivered by different partners in each district at different times. All children resident in 2004 were recruited into the cohort and exited during subsequent census rounds if they had out-migrated, homesteads or guardians subsequently refused participation, they had reached their fifth birthday, or they had died. New children were recruited into the cohort if they had migrated into the homestead between census rounds or were identified through detailed birth histories of all resident women aged 15–49 y as having been born during the interval. New infants who did not survive the interval between census rounds were included in the cohort. In-migrations that out-migrated between the census rounds were not included in the cohort and were regarded as short-term visitors not permanently resident. During the 2005/6 annual census round, representing the reference midpoint of the surveillance period, details were recorded on each homestead relating to key asset indicators, including: homestead head education level and occupation; housing characteristics (type of wall, roof, and floor); source of drinking water; type of sanitation facility; homestead size; and persons per sleeping room (see Table S1). Data entry and storage were undertaken using Microsoft Access, and analysis was undertaken using STATA version 9.2 (Stata, http://www.stata.com) and ARCGIS 9.0 (ESRI). All information specific to the EA, homestead, and mother or guardian were linked to the relevant child through the use of a primary homestead identifier consistent across all data sets. To account for unequal probabilities of selection of EAs, all results were weighted (weight = 1/probability of selection) and precision of proportions (95% confidence intervals [CIs]) were adjusted for clustering with EA as the primary sampling unit. A χ2 test was performed to compare net use proportions across subgroups within and between survey years. For comparisons of socioeconomic groups within a survey year, the Pearson χ2 statistic, accounting for clustering, was used. This statistic is turned into an F-statistic using the second-order Rao and Scott correction and p-values interpreted the same way as the Pearson χ2 statistic for data without clustering [28,29]. A homestead wealth index was constructed from the asset indicators using principal component analysis. Weights (scoring coefficients) derived from the first principal component were used to construct the wealth index [30]. Weights for each asset indicator from the first principal component were then applied to each homestead record to produce a wealth index. Wealth asset indices were developed separately for each district to allow for innate differences in the meaning of different assets between districts. Each homestead was then assigned to a district-specific wealth quintile. Net ownership by children in the cohort was examined serially and by source according to wealth asset quintiles. Inequity in net coverage over time and by source was analysed using the concentration index, which gives values between −1 and 1, with a value 0 indicating an absence of wealth-related inequality in net use among children [31]. Because net use is a “good” health variable, a positive value of the index indicates net use is concentrated among the wealthy. The concentration curve was plotted to illustrate changes in wealth-related inequality [31]. Ethical approval was provided by the National Ethical Review Board IRB (Kenya Medical Research Institute SSC number 906).

The innovation described in the study is the implementation of different delivery models to increase coverage and decrease inequity in insecticide-treated bed net (ITN) use among rural Kenyan children. The study evaluated the impact of three different approaches: commercial sector nets, heavily subsidized clinic distribution, and free mass distributed ITNs. The findings showed that the free mass distribution method achieved the highest coverage among the poorest children, while the heavily subsidized clinic nets program slightly favored the least poor, and the commercial social marketing favored the least poor. The study highlights the importance of combining different approaches to ensure equitable access to ITNs among the most vulnerable populations.
AI Innovations Description
The study described in the provided text focuses on increasing coverage and decreasing inequity in insecticide-treated bed net (ITN) use among rural Kenyan children to improve access to maternal health. The study examines the impact of different delivery models on ITN coverage and assesses changes in coverage across socioeconomic groups.

The study found that ITN coverage was initially low at 7.1% in 2004 when the main source of nets was the commercial retail sector. However, coverage increased to 23.5% in 2005 following the introduction of heavily subsidized nets through clinics. In 2006, a large-scale mass distribution of ITNs was implemented, resulting in a significant increase in coverage to 67.3%. With each subsequent survey, socioeconomic inequity in net coverage sequentially decreased.

The study recommends that rapid scaling up of ITN coverage among Africa’s poorest rural children can be achieved through mass distribution campaigns. These efforts should be complementary to regular access to ITNs through clinics and aim to make the intervention free to ensure equitable access among those who cannot afford even heavily subsidized nets.

In summary, the recommendation to improve access to maternal health is to implement mass distribution campaigns of insecticide-treated bed nets, in addition to routine access through clinics, and ensure that the intervention is provided free of charge to reach the poorest rural populations.
AI Innovations Methodology
Based on the provided information, one potential recommendation to improve access to maternal health is to implement a mass distribution campaign for insecticide-treated bed nets (ITNs) targeting pregnant women and children under the age of 5. This recommendation is based on the findings that the free mass distribution of ITNs resulted in a dramatic increase in ITN coverage, particularly among the poorest children.

To simulate the impact of this recommendation on improving access to maternal health, a methodology could be developed as follows:

1. Define the target population: Identify the specific population group that will be the focus of the simulation, such as pregnant women and children under the age of 5 in rural areas of Kenya.

2. Collect baseline data: Gather data on the current coverage of ITNs among the target population, including information on the source of nets, socioeconomic status, and geographic distribution.

3. Develop a simulation model: Create a mathematical model that simulates the distribution and utilization of ITNs among the target population. The model should take into account factors such as population size, distribution of ITN sources, access to healthcare facilities, and socioeconomic disparities.

4. Incorporate intervention scenarios: Introduce different scenarios into the simulation model to represent the impact of the recommended intervention. For example, simulate the effects of a mass distribution campaign for ITNs targeting pregnant women and children under the age of 5, considering factors such as coverage rates, distribution strategies, and cost.

5. Analyze the results: Evaluate the outcomes of the simulation by comparing the coverage and equity in ITN use before and after the intervention. Assess the impact of the intervention on improving access to maternal health, including changes in ITN coverage rates and reductions in socioeconomic inequities.

6. Refine and validate the model: Continuously refine and validate the simulation model based on real-world data and feedback from stakeholders. Adjust the model parameters and assumptions as necessary to improve its accuracy and reliability.

7. Communicate the findings: Present the results of the simulation in a clear and concise manner, highlighting the potential benefits of the recommended intervention in improving access to maternal health. Share the findings with relevant stakeholders, such as policymakers, healthcare providers, and community organizations, to inform decision-making and implementation strategies.

By following this methodology, policymakers and stakeholders can gain insights into the potential impact of implementing a mass distribution campaign for ITNs on improving access to maternal health in rural areas of Kenya. This information can guide decision-making and resource allocation to prioritize interventions that have the greatest potential for positive impact.

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