Engaging multisector stakeholders to identify priorities for global health innovation, change and research: an engagement methodology and application to prosthetics service delivery in Cambodia.

PURPOSE: While innovation is known to catalyse solutions to global sustainable development challenges, lack of engagement from stakeholders during conceptualisation and development may influence the degree of success of implementation. METHODS AND MATERIALS: This paper presents a complete and novel engagement methodology, developed from value led business modelling approaches, for working with multi-sector stakeholders. The methodology can be used to determine barriers and facilitators to clinical practice innovations or translational research, within a country-specific context. The approach has then been applied in the Cambodian prosthetics and orthotics sector to provide a practice-based exemplar application of the framework. RESULTS: This approach seeks to ensure the suitability and sustainability of clinical practice and research programmes being implemented within a complex ecosystem. A theoretical basis, drawn from academic and business innovation sectors, has been consolidated and adapted for practical application to design, direct, and inform initiatives in low resource settings. CONCLUSIONS: The methods presented provide a way to both develop and articulate the mission, vision, and goals of any proposed change, and to effectively communicate these with stakeholders in a way that engages the personal and professional values that exist in their ecosystem. It provides a structured process through which meaningful conversations can happen, and a basis for relationship management with key stakeholders; intrinsic to enable a sustained legacy from research and development.

The engagement from stakeholders during conceptualisation and throughout development can determine the success, or not, of any implementation and scale of innovation.This paper presents a conceptual stakeholder-led engagement methodology, developed from value led business modelling approaches, for determining barriers and facilitators to translational global healthcare research in a country-specific context, in this case the Cambodian prosthetics and orthotics sector.Subsequent research and development work in this area needs to carefully manage and negotiate influencing factors identified through the application of the described methodology, to ensure initiatives (whether research or wider national development work) are sustainable and successful.

Human population genetic structure and diversity inferred from polymorphic L1(LINE-1) and Alu insertions.

BACKGROUND/AIMS: The L1 retrotransposable element family is the most successful self-replicating genomic parasite of the human genome. L1 elements drive replication of Alu elements, and both have had far-reaching impacts on the human genome. We use L1 and Alu insertion polymorphisms to analyze human population structure. METHODS: We genotyped 75 recent, polymorphic L1 insertions in 317 individuals from 21 populations in sub-Saharan Africa, East Asia, Europe and the Indian subcontinent. This is the first sample of L1 loci large enough to support detailed population genetic inference. We analyzed these data in parallel with a set of 100 polymorphic Alu insertion loci previously genotyped in the same individuals. RESULTS AND CONCLUSION: The data sets yield congruent results that support the recent African origin model of human ancestry. A genetic clustering algorithm detects clusters of individuals corresponding to continental regions. The number of loci sampled is critical: with fewer than 50 typical loci, structure cannot be reliably discerned in these populations. The inclusion of geographically intermediate populations (from India) reduces the distinctness of clustering. Our results indicate that human genetic variation is neither perfectly correlated with geographic distance (purely clinal) nor independent of distance (purely clustered), but a combination of both: stepped clinal.

Ethnogenomic diversity of Caucasus, Daghestan.

Autosomal short-tandem repeats (STRs) were typed in ethnic populations of Kubachians, Dargins, Avars, Lezgins, Kumiks, and Nogais of the Caucasus (Daghestan, Russia) at the University of Utah. Daghestan ethnic populations demonstrated differences in STR allele frequency distributions, but these differences were much lower among these ethnic groups compared to worldwide ethnic groups. The observed genetic diversity was low while F(ST) values were high, both of which provided supporting evidence for small population sizes and high levels of isolation among the ethnic groups. An analysis of genetic distance from the three major continents, encompassing Daghestan populations and groups, reveals three distinct clusters: all populations of African affiliation, European and Daghestan populations except the Nogais, and Asian populations with ethnic Nogais.

[STR polymorphism in populations of indigenous Daghestan ethnic groups]. / STR-polimorfizm v populiatsiiakh korennykh narodov Dagestana.

Genomic diversity of 21 STR loci has been studied in six ethnic populations of Daghestan (the Caucasus), namely, Avars, Dargins, Kubachians, Lezgins, and Nogais, and the results have been compared with these data for European, African, and East Asian ethnic groups. Daghestan is unique in its ethnic diversity, which is the greatest in the Caucasus: 26 out of approximately 50 autochthonous ethnic groups of the Caucasus live there. The genetic origin of this wide ethnic diversity of Daghestan and the Caucasus as a whole is still obscure. The genetic heterogeneity of Daghestan populations has been found to be lower than that of most other populations in the world. This is explained by a prolonged isolation and gene drift in their demographic history. Generalized genetic distances between ethnic groups calculated for the whole set of loci studied allow differentiating Asian populations from African ones, with European populations occupying intermediate positions. All Daghestan ethnic populations form a distinct common group together with some European populations (Finnish, Polish, and French). Nogais are genetically close to Southeast Asian populations. The genetic closeness and the apparently equal genetic diversity of Daghestan and European populations suggest that the ethnic differentiation of the ancestral populations of Daghestan and European ethnic groups occurred in the earliest populations of modern humans.