The Lives of ‘Facts’ in Mathematical Models: A Story of Population-level Disease Transmission of Haemophilus Influenzae Type B Bacteria

Performativity and a microbe: Exploring Mycobacterium bovis and the political ecologies of bovine tuberculosis

Mycobacterium bovis, the bacterium responsible for causing bovine tuberculosis (bTB) in cattle, displays what I call ‘microbial performativity’. Like many other lively disease-causing microorganisms, it has an agency which is difficult to contain, and there is a need for fresh thinking on the challenges of dealing with this slippery and indeterminate microbe. As a practising veterinary scientist who side-stepped mid-career into a parallel training in the social sciences to view bTB from an alternative perspective, I create an interdisciplinary coming-together where veterinary science converges with a political ecology of (animal) health influenced by science and technology studies (STS) and social science and humanities scholarship on performativity. This suitably hybridized nexus creates a place to consider the ecologies of a pathogen which could be considered as life out of control. I consider what this means for efforts to eradicate this disease through combining understandings from the published scientific literature with qualitative interview-based fieldwork with farmers, veterinarians and others involved in the statutory bTB eradication programme in a high incidence region of the UK. This study demonstrates the value of life scientists turning to the social sciences to re-view their familiar professional habitus—challenging assumptions, and offering alternative perspectives on complex problems.

Understanding and Governing Public Health Risks by Modeling

Increase in the use and development of computational tools to govern public health risks invites us to study their benefits and limitations. To analyze how risk is perceived and expressed through these tools is relevant to risk theory. This chapter clarifies the different concepts of risk, contrasting especially the mathematically expressed ones with culturally informed notions, which address a broader view on risk. I will suggest that a fruitful way to contextualize computational tools, such mathematical models in risk assessment is “analytics of risk,” which ties together the technological, epistemological, and political dimensions of the process of governance of risk. I will clarify the development of mathematical modeling techniques through their use in infectious disease epidemiology. Epidemiological modeling functions as a form of “risk calculation,” which provides predictions of the infectious outbreak in question. These calculations help direct and design preventive actions toward the health outcomes of populations. This chapter analyzes two cases in which modeling methods are used for explanation-based and scenario-building predictions in order to anticipate the risks of infections caused by Haemophilus influenzae type b bacteria and A(H1N1) pandemic influenza virus. I will address an interesting tension that arises when model-based estimates exemplify the population-level reasoning of public health risks but has restricted capacity to address risks on individual level. Analyzing this tension will lead to a fuller account to understand the benefits and limitations of computational tools in the governance of public health risks.