Effect of nutrition survey 'cleaning criteria' on estimates of malnutrition prevalence and disease burden: secondary data analysis.

Tackling childhood malnutrition is a global health priority. A key indicator is the estimated prevalence of malnutrition, measured by nutrition surveys. Most aspects of survey design are standardised, but data 'cleaning criteria' are not. These aim to exclude extreme values which may represent measurement or data-entry errors. The effect of different cleaning criteria on malnutrition prevalence estimates was unknown. We applied five commonly used data cleaning criteria (WHO 2006; EPI-Info; WHO 1995 fixed; WHO 1995 flexible; SMART) to 21 national Demographic and Health Survey datasets. These included a total of 163,228 children, aged 6-59 months. We focused on wasting (low weight-for-height), a key indicator for treatment programmes. Choice of cleaning criteria had a marked effect: SMART were least inclusive, resulting in the lowest reported malnutrition prevalence, while WHO 2006 were most inclusive, resulting in the highest. Across the 21 countries, the proportion of records excluded was 3 to 5 times greater when using SMART compared to WHO 2006 criteria, resulting in differences in the estimated prevalence of total wasting of between 0.5 and 3.8%, and differences in severe wasting of 0.4-3.9%. The magnitude of difference was associated with the standard deviation of the survey sample, a statistic that can reflect both population heterogeneity and data quality. Using these results to estimate case-loads for treatment programmes resulted in large differences for all countries. Wasting prevalence and caseload estimations are strongly influenced by choice of cleaning criterion. Because key policy and programming decisions depend on these statistics, variations in analytical practice could lead to inconsistent and potentially inappropriate implementation of malnutrition treatment programmes. We therefore call for mandatory reporting of cleaning criteria use so that results can be compared and interpreted appropriately. International consensus is urgently needed regarding choice of criteria to improve the comparability of nutrition survey data

The 2011 Famine in Somalia: lessons learnt from a failed response?

The 2011 famine in Somalia was predicted and could have been mitigated or prevented if the humanitarian response had been timely and more effective. To improve responsiveness to early warnings, action is required to better insulate the humanitarian system from political agendas.Abaarta ka dhacday Soomaaliya 2011 waxay ahayd mid horay loo saadaaliyay, waana laga tabaabasheysan karay ama laga hortegi karay haddii falgalka samafalku uu ahaan lahaa mid degdeg ah oo waxtar leh. Si loo hagaajiyo falgalka habka qayladhaanta, waxaa loo baahanyahay in samafalka, gebi ahaan, laga saaro siyaasadda.La carestia del 2011 in Somalia era stata prevista e avrebbe potuto essere attenuata o evitata se la risposta umanitaria fosse stata tempestiva ed efficace. Per migliorare la risposta ai sistemi di preallarme, è necessario isolare maggiormente il sistema umanitario dall'agenda politica

Method of lines transpose: High order L-stable O(N) schemes for parabolic equations using successive convolution

We present a new solver for nonlinear parabolic problems that is L-stable and achieves high order accuracy in space and time. The solver is built by first constructing a single-dimensional heat equation solver that uses fast O(N) convolution. This fundamental solver has arbitrary order of accuracy in space, and is based on the use of the Green's function to invert a modified Helmholtz equation. Higher orders of accuracy in time are then constructed through a novel technique known as successive convolution (or resolvent expansions). These resolvent expansions facilitate our proofs of stability and convergence, and permit us to construct schemes that have provable stiff decay. The multi-dimensional solver is built by repeated application of dimensionally split independent fundamental solvers. Finally, we solve nonlinear parabolic problems by using the integrating factor method, where we apply the basic scheme to invert linear terms (that look like a heat equation), and make use of Hermite-Birkhoff interpolants to integrate the remaining nonlinear terms. Our solver is applied to several linear and nonlinear equations including heat, Allen-Cahn, and the Fitzhugh-Nagumo system of equations in one and two dimensions

Derivation of nutrient requirements for disaster-affected populations: Sphere Project 2011.

BACKGROUND: Nutritional requirements have been previously calculated for emergency-affected populations and are widely used for planning and assessing the nutritional adequacy of humanitarian food assistance. The Sphere Project is an interagency collaboration that defines minimum standards and indicators for humanitarian responses, including food and nutrition. It last published population nutritional requirements in 2004, but a revision was required due to the release of new Reference Nutrient Intakes (RNIs) by the World Health Organization and Food and Agriculture Organization (WHO/FAO). OBJECTIVE: To review and revise the list of specified nutrients and recalculate population requirements using RNIs published by WHO/FAO. METHODS: Review of published normative documents, consultation with experts and participants in the Sphere revision process, construction of a reference demographic profile, and calculation of population nutrient requirements for use in designing emergency general rations. RESULTS: Twenty-one nutrients and energy were selected for inclusion, and a demographic profile was constructed to represent a typical beneficiary population. Compared with the previous version of the Sphere Handbook, population requirements for nine vitamins and minerals were found to have increased as a result of the new WHO/FAO RNIs. CONCLUSIONS: The calculated requirements were adopted and published as part of the Sphere 2011 Handbook. The incorporation of these requirements into planning, monitoring, and evaluation practices for food assistance will help to ensure that populations receive appropriate nutritional support during crises

An explicit high-order single-stage single-step positivity-preserving finite difference WENO method for the compressible Euler equations

In this work we construct a high-order, single-stage, single-step positivity-preserving method for the compressible Euler equations. Space is discretized with the finite difference weighted essentially non-oscillatory (WENO) method. Time is discretized through a Lax-Wendroff procedure that is constructed from the Picard integral formulation (PIF) of the partial differential equation. The method can be viewed as a modified flux approach, where a linear combination of a low- and high-order flux defines the numerical flux used for a single-step update. The coefficients of the linear combination are constructed by solving a simple optimization problem at each time step. The high-order flux itself is constructed through the use of Taylor series and the Cauchy-Kowalewski procedure that incorporates higher-order terms. Numerical results in one- and two-dimensions are presented