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.