An analysis of the food system landscape and agricultural value chains for nutrition: A case study from Sierra Leone

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An Analysis of the Food System Landscape and Agricultural Value Chains for Nutrition: A Case Study from Sierra Leone

This paper summarizes a qualitative case study conducted in Sierra Leone to explore the programmatic challenges of linking nutrition and agriculture nationally through a food system landscape analysis, and the implementation of nutrition-sensitive value chains of two commodities – rice and vegetables. The research undertaken in this project aimed to understand the role markets and value chains play in improving dietary diversification both directly, through an increase in the production of nutritious foods sourced from smallholders in Sierra Leone, and indirectly, through an increase in income for smallholder farmers. Much of the analyses done in this study examined the supply side of the value chain. The study highlights the importance in engaging women in value chains, and their potential role as “change agents” to ensure that nutrition is better integrated along the value chains as producers and consumers (IFPRI/ILRI, 2010). The study also identified various pathways through which rice and vegetables production, processing and marketing could contribute to improving nutritional status and health. Agriculture and health actors would benefit from jointly developing nutrition indicators to insert into the value chain that address both nutrition and agriculture. While a single intervention targeting only one component of the value chain is likely to have a limited impact, addressing all the identified issues, with several interventions at different levels of the chain can make a real difference

Microeconometrics with Partial Identification

This chapter reviews the microeconometrics literature on partial identification, focusing on the developments of the last thirty years. The topics presented illustrate that the available data combined with credible maintained assumptions may yield much information about a parameter of interest, even if they do not reveal it exactly. Special attention is devoted to discussing the challenges associated with, and some of the solutions put forward to, (1) obtain a tractable characterization of the values for the parameters of interest which are observationally equivalent, given the available data and maintained assumptions; (2) estimate this set of values; (3) conduct test of hypotheses and make confidence statements. The chapter reviews advances in partial identification analysis both as applied to learning (functionals of) probability distributions that are well-defined in the absence of models, as well as to learning parameters that are well-defined only in the context of particular models. A simple organizing principle is highlighted: the source of the identification problem can often be traced to a collection of random variables that are consistent with the available data and maintained assumptions. This collection may be part of the observed data or be a model implication. In either case, it can be formalized as a random set. Random set theory is then used as a mathematical framework to unify a number of special results and produce a general methodology to carry out partial identification analysis

The ratio of cardiac troponin T to troponin I may indicate non-necrotic troponin release among COVID-19 patients

Background: Although cardiac troponin T (cTnT) and troponin I(cTnI) are expressed to similar amount in cardiac tissue, cTnI often reach ten-times higher peak levels compared to cTnT in patients with myocardial necrosis such as in acute myocardial infarction (MI). In contrast, similar levels of cTnT and cTnI are observed in other situations such as stable atrial fibrillation and after strenuous exercise.Objective: Examine cTnT and cTnI levels in relation to COVID-19 disease and MI. Methods: Clinical and laboratory data from the local hospital from an observational cohort study of 27 patients admitted with COVID-19 and 15 patients with myocardial infarction (MI) that were analyzed with paired cTnT and cTnI measurement during hospital care.Results: Levels of cTnI were lower than cTnT in COVID-19 patients (TnI/TnT ratio 0.3, IQR: 0.1-0.6). In contrast, levels of cTnI were 11 times higher compared to cTnT in 15 patients with MI (TnI/TnT ratio 11, IQR: 7-14). The peak cTnI/cTnT ratio among the patients with MI following successful percutaneous intervention were 14 (TnI/ TnT ratio 14, IQR: 12-23). The 5 COVID-19 patient samples collected under possible necrotic events had a cTnI/ cTnT ratio of 5,5 (IQR: 1,9-8,3).Conclusions: In patients with COVID-19, cTnT is often elevated to higher levels than cTnI in sharp contrast to patients with MI, indicating that the release of cardiac troponin has a different cause in COVID-19 patients