Bringing public attention to disease into global health priority-setting

Background: A central concern in global health priority-setting is whether the supply of scientific knowledge aligns with health needs and demands. This alignment is usually assessed by comparing research effort with disease burden, overlooking other type of “social demand” of disease, in particular whether diseases are socially visible and generate public attention. We develop an analytical framework that treats public attention and epidemiological burden as complementary dimensions of health demand and examines their alignment with knowledge supply. Methods: We combine data on publications indexed in OpenAlex, disability-adjusted life years from the Global Burden of Disease, and Wikipedia pageviews for 2016 to 2023, as indicators of research effort, disease burden, and public attention, respectively. We map 19 disease groups and 138 specific diseases across these three dimensions. Ternary plots are used to position diseases according to their relative balance across dimensions and to identify diseases that are over- or under-represented in research effort relative to epidemiological burden and public attention. We compare Global North-South patterns using German, Persian, Swahili, and Vietnamese language areas to assess how these relationships vary across territories. Results: The three dimensions show limited alignment. At the disease group level, cardiovascular diseases account for the largest share of disease burden, mental disorders attract the largest share of public attention, and neoplasms concentrate the largest share of research effort. Public attention and disease burden are weakly correlated at both group and specific disease levels, indicating that Wikipedia pageviews and DALYs capture distinct dimensions of health demand. Ternary plots reveal different forms of misalignment, with some diseases showing plots dominated by burden, others by research effort, and others by public attention. Territorial analyses add a further layer by showing that diseases follow disparate patterns of supply-demand (mis)alignment across different linguistic territories. Conclusions: Public attention provides a complementary dimension for mapping global health needs and demands. Our approach identifies where scientific knowledge supply fails to match epidemiological and/or public attention, supporting more nuanced global health analysis that may be useful for priority-setting.