Jane Chuma

Treatment-seeking behaviour, cost burdens and coping strategies among rural and urban households in Coastal Kenya: an equity analysis.

Ill‐health can inflict costs on households directly through spending on treatment and indirectly through impacting on labour productivity. The financial burden can be high and, for poor households, contributes significantly to declining welfare. We investigated socio‐economic inequities in self‐reported illnesses, treatment‐seeking behaviour, cost burdens and coping strategies in a rural and urban setting along the Kenyan coast. We conducted a survey of 294 rural and 576 urban households, 9 FGDs and 9 in‐depth interviews in each setting. Key findings were significantly higher levels of reported chronic and acute conditions in the rural setting, differences in treatment‐seeking patterns by socio‐economic status (SES) and by setting, and regressive cost burdens in both areas. These data suggest the need for greater governmental and non‐governmental efforts towards protecting the poor from catastrophic illness cost burdens. Promising health sector options are elimination of user fees, at least in targeted hardship areas, developing more flexible charging systems, and improving quality of care in all facilities. The data also strongly support the need for a multi‐sectoral approach to protecting households. Potential interventions beyond the health sector include supporting the social networks that are key to household livelihood strategies and promoting micro‐finance schemes that enable small amounts of credit to be accessed with minimal interest rates.

Rethinking the economic costs of malaria at the household level: Evidence from applying a new analytical framework in rural Kenya

BackgroundMalaria imposes significant costs on households and the poor are disproportionately affected. However, cost data are often from quantitative surveys with a fixed recall period. They do not capture costs that unfold slowly over time, or seasonal variations. Few studies investigate the different pathways through which malaria contributes towards poverty. In this paper, a framework indicating the complex links between malaria, poverty and vulnerability at the household level is developed and applied using data from rural Kenya.MethodsCross-sectional surveys in a wet and dry season provide data on treatment-seeking, cost-burdens and coping strategies (n = 294 and n = 285 households respectively). 15 case study households purposively selected from the survey and followed for one year provide in-depth qualitative information on the links between malaria, vulnerability and poverty.ResultsMean direct cost burdens were 7.1% and 5.9% of total household expenditure in the wet and dry seasons respectively. Case study data revealed no clear relationship between cost burdens and vulnerability status at the end of the year. Most important was household vulnerability status at the outset. Households reporting major malaria episodes and other shocks prior to the study descended further into poverty over the year. Wealthier households were better able to cope.ConclusionThe impacts of malaria on household economic status unfold slowly over time. Coping strategies adopted can have negative implications, influencing household ability to withstand malaria and other contingencies in future. To protect the poor and vulnerable, malaria control policies need to be integrated into development and poverty reduction programmes.

Reviewing the literature on access to prompt and effective malaria treatment in Kenya: implications for meeting the Abuja targets

BackgroundEffective case management is central to reducing malaria mortality and morbidity worldwide, but only a minority of those affected by malaria, have access to prompt effective treatment.In Kenya, the Division of Malaria Control is committed to ensuring that 80 percent of childhood fevers are treated with effective anti-malarial medicines within 24 hours of fever onset, but this target is largely unmet. This review aimed to document evidence on access to effective malaria treatment in Kenya, identify factors that influence access, and make recommendations on how to improve prompt access to effective malaria treatment. Since treatment-seeking patterns for malaria are similar in many settings in sub-Saharan Africa, the findings presented in this review have important lessons for other malaria endemic countries.MethodsInternet searches were conducted in PUBMED (MEDLINE) and HINARI databases using specific search terms and strategies. Grey literature was obtained by soliciting reports from individual researchers working in the treatment-seeking field, from websites of major organizations involved in malaria control and from international reports.ResultsThe review indicated that malaria treatment-seeking occurs mostly in the informal sector; that most fevers are treated, but treatment is often ineffective. Irrational drug use was identified as a problem in most studies, but determinants of this behaviour were not documented. Availability of non-recommended medicines over-the-counter and the presence of substandard anti-malarials in the market are well documented. Demand side determinants of access include perception of illness causes, severity and timing of treatment, perceptions of treatment efficacy, simplicity of regimens and ability to pay. Supply side determinants include distance to health facilities, availability of medicines, prescribing and dispensing practices and quality of medicines. Policy level factors are around the complexity and unclear messages regarding drug policy changes.ConclusionKenya, like many other African countries, is still far from achieving the Abuja targets. The government, with support from donors, should invest adequately in mechanisms that promote access to effective treatment. Such approaches should focus on factors influencing multiple dimensions of access and will require the cooperation of all stakeholders working in malaria control.

Estimating inequalities in ownership of insecticide treated nets: does the choice of socio-economic status measure matter?

Research on the impact of socio-economic status (SES) on access to health care services and on health status is important for allocating resources and designing pro-poor policies. Socio-economic differences are increasingly assessed using asset indices as proxy measures for SES. For example, several studies use asset indices to estimate inequities in ownership and use of insecticide treated nets as a way of monitoring progress towards meeting the Abuja targets. The validity of different SES measures has only been tested in a limited number of settings, however, and there is little information on how choice of welfare measure influences study findings, conclusions and policy recommendations. In this paper, we demonstrate that household SES classification can depend on the SES measure selected. Using data from a household survey in coastal Kenya (n = 285 rural and 467 urban households), we first classify households into SES quintiles using both expenditure and asset data. Household SES classification is found to differ when separate rural and urban asset indices, or a combined asset index, are used. We then use data on bednet ownership to compare inequalities in ownership within each setting by the SES measure selected. Results show a weak correlation between asset index and monthly expenditure in both settings: wider inequalities in bednet ownership are observed in the rural sample when expenditure is used as the SES measure [Concentration Index (CI) = 0.1024 expenditure quintiles; 0.005 asset quintiles]; the opposite is observed in the urban sample (CI = 0.0518 expenditure quintiles; 0.126 asset quintiles). We conclude that the choice of SES measure does matter. Given the practical advantages of asset approaches, we recommend continued refinement of these approaches. In the meantime, careful selection of SES measure is required for every study, depending on the health policy issue of interest, the research context and, inevitably, pragmatic considerations.

A cost effectiveness and capacity analysis for the introduction of universal rotavirus vaccination in Kenya : comparison between Rotarix and RotaTeq vaccines

Background Diarrhoea is an important cause of death in the developing world, and rotavirus is the single most important cause of diarrhoea associated mortality. Two vaccines (Rotarix and RotaTeq) are available to prevent rotavirus disease. This analysis was undertaken to aid the decision in Kenya as to which vaccine to choose when introducing rotavirus vaccination. Methods Cost-effectiveness modelling, using national and sentinel surveillance data, and an impact assessment on the cold chain. Results The median estimated incidence of rotavirus disease in Kenya was 3015 outpatient visits, 279 hospitalisations and 65 deaths per 100,000 children under five years of age per year. Cumulated over the first five years of life vaccination was predicted to prevent 34% of the outpatient visits, 31% of the hospitalizations and 42% of the deaths. The estimated prevented costs accumulated over five years totalled US

Does expanding fiscal space lead to improved funding of the health sector in developing countries?: lessons from Kenya, Lagos State (Nigeria) and South Africa.

1,782,761 (direct and indirect costs) with an associated 48,585 DALYs. From a societal perspective Rotarix had a cost-effectiveness ratio of US

Raising domestic resources for healthCan tax revenue help fund Universal Health Coverage

142 per DALY (US

The role of community-based organizations in household ability to pay for health care in Kilifi District, Kenya

5 for the full course of two doses) and RotaTeq US

Conducting health-related social science research in low income settings: ethical dilemmas faced in Kenya and South Africa

288 per DALY (

An increase in the burden of neonatal admissions to a rural district hospital in Kenya over 19 years

10.5 for the full course of three doses). RotaTeq will have a bigger impact on the cold chain compared to Rotarix. Conclusion Vaccination against rotavirus disease is cost-effective for Kenya irrespective of the vaccine. Of the two vaccines Rotarix was the preferred choice due to a better cost-effectiveness ratio, the presence of a vaccine vial monitor, the requirement of fewer doses and less storage space, and proven thermo-stability.