Economies of scale and scope in publicly funded biomedical and health research: evidence from the literature.

BACKGROUND: Publicly funded biomedical and health research is expected to achieve the best return possible for taxpayers and for society generally. It is therefore important to know whether such research is more productive if concentrated into a small number of 'research groups' or dispersed across many. METHODS: We undertook a systematic rapid evidence assessment focused on the research question: do economies of scale and scope exist in biomedical and health research? In other words, is that research more productive per unit of cost if more of it, or a wider variety of it, is done in one location? We reviewed English language literature without date restriction to the end of 2014. To help us to classify and understand that literature, we first undertook a review of econometric literature discussing models for analysing economies of scale and/or scope in research generally (not limited to biomedical and health research). RESULTS: We found a large and disparate literature. We reviewed 60 empirical studies of (dis-)economies of scale and/or scope in biomedical and health research, or in categories of research including or overlapping with biomedical and health research. This literature is varied in methods and findings. At the level of universities or research institutes, studies more often point to positive economies of scale than to diseconomies of scale or constant returns to scale in biomedical and health research. However, all three findings exist in the literature, along with inverse U-shaped relationships. At the level of individual research units, laboratories or projects, the numbers of studies are smaller and evidence is mixed. Concerning economies of scope, the literature more often suggests positive economies of scope than diseconomies, but the picture is again mixed. The effect of varying the scope of activities by a research group was less often reported than the effect of scale and the results were more mixed. CONCLUSIONS: The absence of predominant findings for or against the existence of economies of scale or scope implies a continuing need for case by case decisions when distributing research funding, rather than a general policy either to concentrate funding in a few centres or to disperse it across many.

Genetic variation among world populations: inferences from 100 Alu insertion polymorphisms.

We examine the distribution and structure of human genetic diversity for 710 individuals representing 31 populations from Africa, East Asia, Europe, and India using 100 Alu insertion polymorphisms from all 22 autosomes. Alu diversity is highest in Africans (0.349) and lowest in Europeans (0.297). Alu insertion frequency is lowest in Africans (0.463) and higher in Indians (0.544), E. Asians (0.557), and Europeans (0.559). Large genetic distances are observed among African populations and between African and non-African populations. The root of a neighbor-joining network is located closest to the African populations. These findings are consistent with an African origin of modern humans and with a bottleneck effect in the human populations that left Africa to colonize the rest of the world. Genetic distances among all pairs of populations show a significant product-moment correlation with geographic distances (r = 0.69, P < 0.00001). F(ST), the proportion of genetic diversity attributable to population subdivision is 0.141 for Africans/E. Asians/Europeans, 0.047 for E. Asians/Indians/Europeans, and 0.090 for all 31 populations. Resampling analyses show that approximately 50 Alu polymorphisms are sufficient to obtain accurate and reliable genetic distance estimates. These analyses also demonstrate that markers with higher F(ST) values have greater resolving power and produce more consistent genetic distance estimates.