Paper short abstract:

This paper draws on ethnographic research around sickle cell disease in Tanzania to highlight the ways that categories of “global” and “local” are remade through the new prioritization of Pan-African genomic medicine. It argues for attention to the ethics of scale in contemporary genetic research.

Paper long abstract:

This paper reflects roughly a decade of ethnographic engagement with the growing infrastructure for sickle cell disease research and care in Tanzania. As part of the expanding Pan-African research collaborations around genetic medicine in Africa since the early 2010s, Tanzania has emerged as a hub for knowledge production around sickle cell both by and for Africans. Across the country, Tanzanian medical researchers continually break earlier, more extractive patterns of Global Health by creating sickle cell disease collaborations that strive to center local expertise and local needs. In this paper, however, I suggest that “local” is an unstable and incomplete signifier. Indeed, the various (especially financial) pressures of Global Health continue to privilege claims to extractable, abstract, and universal knowledge that can serve the greatest number of people. Meanwhile, new collaborations must move through existing political and social alliances that predate the present moment, figuring "the local" in particular ways. This can often risk rendering other, more hyperlocal needs and forms of expertise less visible. How might efforts toward globally inclusive learning and global health outcomes resist the familiar tropes of postcolonial Global Health, and instead privilege the expertise of diverse local experiences? How are these categories of “global” and “local” themselves (re)made in different ways through growing sickle cell disease infrastructure? Rather than proposing any single answer to these questions, this paper uses ethnographic stories of Tanzanian biomedicine, activism, and community care to invite different perspectives and forms of labor into the work of expanding genetic disease infrastructure.