At present, humanity is embarking upon the greatest experiment ever undertaken: ‘flattening the curve.’ How can we understand this experiment?
We could start by asking how it aligns with the traditional experimental method. Here, the independent variable could be conceived as quarantine, the dependent variable could be conceived as the case numbers of COVID-19 in the population, and among the many controlled variables we could identify, the current and static capacity of hospitals and the health care workforce would certainly rank among the most important.
Holding hospital capacity constant, this experiment endeavors to slow the spread of the virus in the population by minimizing contact among individuals and, in doing so, avoid deaths that would occur as a result of overwhelmed hospitals and health care workers. Much attention is paid to the independent variable: quarantine and its social, psychological and economic effects. Equal attention is given to the dependent variable – case numbers and mortality rates. But what can we say about the controlled variable?
A brief interlude: in 2016, Damian Collins, Jalene Anderson and I published a paper examining how chronic homelessness was increasingly being re-interpreted as a costly social problem. The term ‘how’ in the preceding sentence is instructive: the focus of our analysis was how chronic homelessness itself was rendered visible in a new way, as an economic cost borne by law enforcement, emergency responders and hospitals. We were interested in what steps facilitated the translation of chronic homelessness into the economic discourse of health care administration and then back into the discourse of public policy.
Our paper examined a remarkable 5-city randomized, controlled field trial called At Home/Chez Soi which tested the efficacy of the Housing First model in Canada. Counting the number of nights spent in hospital beds and the cost to the health care system was a key component of the field trial. These numbers translated patterns of chronic homelessness into costs borne by health care administrators. Moreover, these numbers facilitated political power. They rendered chronic homelessness representable as a cost, and hence ‘workable’ in a political climate valuing financial risk mitigation.
We called this chain of translation ‘bedspace’, a label we associated with rise of an influential style of political reasoning that has come to dominate contemporary homelessness policy. Bedspace, as we describe in the paper, is a space of calculability across which references to the economic costs of homelessness are made and circulate, one that brings homelessness into the domain of risk management.
In what ways can we extend the concept beyond homelessness policy to the COVID-19 pandemic, a contemporary moment in which hospital beds hold such significance?
As in the case of homelessness, bedspace could be seen as a mode of problematizing COVID-19. However, unlike the case of homelessness, where bedspace linked extreme housing insecurity to economic costs borne by society, bedspace, in our current moment, links unchecked viral transmission with the human cost of COVID-19.
In both cases, ‘beds’ – in terms of their numbers – serve as a key intermediary. But where bedspace, in the homelessness example, rendered chronic homelessness into an economic metric connected to the logic of budgetary prudence and cost containment, in the case of COVID-19, bedspace renders the spread of the virus into an estimation of preventable deaths, a calculation connected to humanitarianism and the wider legitimacy of the state itself.
While qualitatively different, both examples demonstrate the centrality of bedspace to the rationality of government. As an administrative grid of intelligibility, bedspace renders problems visible in a way that is amenable to the government of risk understood in financial terms or humanitarian terms. Both reveal an inner connection between the state, the population, and hospital medicine.
Bedspace certainly draws attention to an external referent, i.e. actual hospital beds; however, the greater theoretical purchase here, I believe, is conceiving bedspace as an epistemic geography, a kind of epistemological grid through which governing and the state is itself understood at key moments of uncertainty.