Promoting the health of marginalized populations in Ecuador through international collaboration and educational innovations

This paper examines two innovative educational initiatives for the Ecuadorian public health workforce: a Canadian-funded Masters programme in ecosystem approaches to health that focuses on building capacity to manage environmental health risks sustainably; and the training of Ecuadorians at the Latin American School of Medicine in Cuba (known as Escuela Latinoamericana de Medicina in Spanish). We apply a typology for analysing how training programmes address the needs of marginalized populations and build capacity for addressing health determinants. We highlight some ways we can learn from such training programmes with particular regard to lessons, barriers and opportunities for their sustainability at the local, national and international levels and for pursuing similar initiatives in other countries and contexts. We conclude that educational efforts focused on the challenges of marginalization and the determinants of health require explicit attention not only to the knowledge, attitudes and skills of graduates but also on effectively engaging the health settings and systems that will reinforce the establishment and retention of capacity in low- and middle-income settings where this is most needed.

The Assault on Human Rigths and the Resilience of the Andean Dream: Health Inequities in Ecuador. IV Annual Distinguished Lecture sponsored by the Center for Research on Ethnicity, Culture and Health; School of Public Health; University of Michigan

The point of departure for these reflections is life, since its protection is the central purpose encouraging the defense of human rights and of public health. Life in the Andes has an exceptional diversity. Particularly in Ecuador, my country, this diversity constitutes a characteristic sign that is expressed in two main forms: natural megadiversity and multiculturalism. Indeed, Ecuador’s small territory synthesizes practically all types of lifezones that exist on Earth, having received the gift of high average rates of solar energy and abundant nutritional sources, which have facilitated the natural reproduction of countless species that show their beautiful vitality in the variety of ecosystems that compose the Andean mountain range, the tropical plains, the Amazon humid forests, and the Galapagos Islands. But besides being a highly biodiverse country, it is also a plurinational and multi-cultural society, in which the activity of human beings, organized into social conglomerates of different historical and cultural backgrounds, have formed more than a dozen nations and peoples. Regrettably this natural and human wealth has not been able to bear its best fruits due to the violent operation of a deep social inequity – unfortunately also one of the highest in the Americas—which conspires against life and is reproduced in national and international inequitable relations. This structural inequity has changed its form throughout the centuries and currently has reached its highest and most perverse level of development.

Revisiting youden’s index as a useful measure of the misclassification error in meta-analysis of diagnostic studies

The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden’s index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel–Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden’s index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.