Cost analysis of school-based intermittent screening and treatment of malaria in Kenya

<p>Abstract</p> <p>Background</p> <p>The control of malaria in schools is receiving increasing attention, but there remains currently no consensus as to the optimal intervention strategy. This paper analyses the costs of intermittent screening and treatment (IST) of malaria in schools, implemented as part of a cluster-randomized controlled trial on the Kenyan coast.</p> <p>Methods</p> <p>Financial and economic costs were estimated using an ingredients approach whereby all resources required in the delivery of IST are quantified and valued. Sensitivity analysis was conducted to investigate how programme variation affects costs and to identify potential cost savings in the future implementation of IST.</p> <p>Results</p> <p>The estimated financial cost of IST per child screened is US$6.61 (economic cost US$ 6.24). Key contributors to cost were salary costs (36%) and malaria rapid diagnostic tests (RDT) (22%). Almost half (47%) of the intervention cost comprises redeployment of existing resources including health worker time and use of hospital vehicles. Sensitivity analysis identified changes to intervention delivery that can reduce programme costs by 40%, including use of alternative RDTs and removal of supervised treatment. Cost-effectiveness is also likely to be highly sensitive to the proportion of children found to be RDT-positive.</p> <p>Conclusion</p> <p>In the current context, school-based IST is a relatively expensive malaria intervention, but reducing the complexity of delivery can result in considerable savings in the cost of intervention.</p> <p>(Costs are reported in US$ 2010).</p

Spectral design of signal-adapted tight frames on graphs

Analysis of signals defined on complex topologies modeled by graphs is a topic of increasing interest. Signal decomposition plays a crucial role in the representation and processing of such information, in particular, to process graph signals based on notions of scale (e.g., coarse to fine). The graph spectrum is more irregular than for conventional domains; i.e., it is influenced by graph topology, and, therefore, assumptions about spectral representations of graph signals are not easy to make. Here, we propose a tight frame design that is adapted to the graph Laplacian spectral content of a given class of graph signals. The design exploits the ensemble energy spectral density, a notion of spectral content of the given signal set that we determine either directly using the graph Fourier transform or indirectly through approximation using a decomposition scheme. The approximation scheme has the benefit that (i) it does not require diagonalization of the Laplacian matrix, and (ii) it leads to a smooth estimate of the spectral content. A prototype system of spectral kernels each capturing an equal amount of energy is defined. The prototype design is then warped using the signal set’s ensemble energy spectral density such that the resulting subbands each capture an equal amount of ensemble energy. This approach accounts at the same time for graph topology and signal features, and it provides a meaningful interpretation of subbands in terms of coarse-to-fine representations