Connective data: Markov chain models and the datafication of cervical cancer and HPV vaccination in Colombia

This article explores the role of statistical modeling in the production of sound epidemiological objects in a context in which data are perceived as fragile and precarious. It analyzes the use of Markov chain modeling in the evaluation of cost-effectiveness of HPV vaccines in Colombia. Markov chain modeling has an important role in producing a "national" cohort of women in which it is possible to test the "virtual" effectiveness of HPV vaccines, transforming information that comes from international literature into national and local data. This modeling device plays a key role in the datafication of cervical cancer and HPV vaccination. The datafication of disease and populations allows connecting the calculative domains of epidemiology and economic valuation. Drawing on studies on data production, statistics and modeling I examine the role of statistics and data dynamics in the making of HPV vaccination as a public health matter. This paper offers a juxtaposition of two analytical domains entangled by the Markov chain. On the one hand, it presents an analysis of a set of technoscientific practices showing where and how a statistical enumerated entity that purports to represent cervical cancer becomes a socio-politically agential entity in the institutional life of the State. On the other, the paper discusses how social difference is left out the model. The exclusion of social difference from data production is coherent with the socio-political workings of Colombian healthcare and vaccination policy.