Why we need political values in epidemic modelling: parameters, populations, and public health policy goals

The article undertakes a conceptual analysis of background assumptions in mathematical modelling of epidemics, and how political values shape scientific reasoning, findings and subsequent policy applications. Drawing examples from the influential work of Robert M. May and Roy M. Anderson in the 1980s and 1990s, the analysis highlights how parameters and population categories, as cognitive tools, mediate between empirical observation and normative commitments. (1) Parameters such as transmission and recovery rates are not merely biological descriptors but epistemic constructs that embed social and political assumptions. They point out what can and has to be modified, and what actors are legitimate to explain the phenomenon; (2) Population categories involve moral judgments about who should be considered alike, who is harmed and who ought to know more about their situation; (3) Political views are necessary in modelling reasoning, albeit implicitly or unconsciously; And (4) it is part of researchers' responsibility to reflect upon them and accept this irreducible part of normativity in the production of scientific facts. Acknowledging the necessary political dimensions of modelling does not undermine its legitimacy. Modellers should move away from a default value-free view of science to adopt a critical and pragmatist stance, that better accounts for what they actually do and want to achieve. It highlights the need to align modelling not only with predictive success but also with justifiable normative goals. Left unquestioned, modelling does not end up value-free, but implicitly valued-laden. It is the responsibility of scientists to make these issues visible.