By Randall Burson II and Angela Ross Perfetti §
“If you have an R0 of 2 — two more cases on average for every person infected — the math tells you that if it is not impeded in any way, that fire burns through the forest, and in the end it will have burned half of the forest — half of the world population or half of the U.S. population will be infected,” explains Nick Jewell, an infectious disease statistician at UC Berkeley, in an email to his daughter, Britta Jewell, an infectious disease epidemiologist at Imperial College London (Roberts 2020). The father-daughter pair recently co-authored an Annals of Internal Medicine piece cautioning policy-makers about important limitations of the Institute for Health Metrics and Evaluation (IHME) COVID-19 model, which has been used by federal and state governments to guide pandemic response in the US (Jewell et al. 2020). Epidemiologic curves like those produced by the IHME model most commonly project the estimated number of COVID-19 cases or deaths over linear time. The temporal axes of these curves become one of the main dimensions through which the pandemic is portrayed and understood, bringing the pandemic into a form that can be acted upon through “flattening practices:” social distancing and working from home, to name a few. Attention to how curves change as functions of time Models like the IHME model are created to answer the question, “when will this end?” Yet, they do not answer the questions “how will this end,” “how will we get through this,” or “what comes after the curve?”
We consider how projections of “the curve,” as an organizing logic of response, have shaped possibilities for response within the pandemic’s temporal unfolding. Thinking with Adriana Petryna’s concept of “horizoning,” we seek to spatialize “the curve” as a means to draw attention both to uncertainties and to forms of structural racism and violence hidden in the curve. We highlight tactics of spatializing and radical care that bring COVID horizons closer, within the space and time of human intervention (Petryna 2015: 2018).
Making Space in Models
We consider space to be “an abstract scientific, mathematical, or measurable conception” (Lawrence-Zúñiga 2017), a concept relating to dimensionality rather than geography. We propose spatializing as a process of reconfiguring the dimensions of that abstract technical and measurable conception. This reconfiguration is an intervention on the fixity of objects like the curve in order to redirect attention from unilinear projections of the future to the multidimensional spaces of response in the present. Spatialization involves attending to the multidimensionality of projections, such as measures of statistical uncertainty, as well as to the social, political, and epistemological conditions that produce the curve. Spatialization, then, becomes a way of retrofitting tools and techniques, like mathematical models, for horizoning work, or “local and highly practical forms of research that attempt to bring an unknown or runaway future into the present as an object of knowledge and intervention” (Petryna 2018: 573). This process of reconfiguring and retrofitting facilitates the responses and interventions that embrace uncertainty and provide necessary moments of pause that “give people just enough room so that they can move” (Petryna 2015: 164).
Through the curve’s circulation as projection and “fact,” these statistics offer a reassuring vantage point that appeals to objectivity. Curves create a “god trick” that renders the scope and scale of COVID-19 knowable (Haraway 1988) while obscuring the contingencies and positionalities of their origins and originators. Using projections to mobilize political action requires crafting an image of them as the pandemic, erasing the conditions of their construction (Caruth 2010). In other words, curves without context can be granted greater predictive ability, and, therefore, condense authority to narrate the pandemic’s trajectory. For example, the curve’s line is often flanked by confidence intervals, estimates of statistical certainty. Many of the models used to predict COVID-19 continue to have relatively wide confidence intervals, signaling the substantial uncertainty of their parameters (Bui et al. 2020) (Figure 1, Left). Yet, as these curves travel through the news media, the confidence intervals are lost along the way (Figure 1, Right). What the viewer ultimately sees is a curve without space or context; the only way forward is along a solid line tracing ascent and descent over a single, fixed peak. This new, decontextualized form of the curve-as-solid-line naturalizes the curve as fact and future, offering a singular story about how the pandemic will progress. How then can we unmake this teleology that the curve has created for us? The first step in spatializing the curve as an effort to mitigate death and disease requires firmly reattaching confidence intervals in order to transform the curve’s line to a two-dimensional plane of possible (even if less probable) options.
By calibrating infectious disease models to disease ecology, modelers are engaged in horizoning work to “steer” the curve in an empirically-grounded manner that can redress critical uncertainties. Michael Levy, an infectious disease ecologist, specifies that “a model isn’t a crystal ball to make predictions;” rather, models help “get our head around what’s already going on and what we can do about it” (Ingeno 2020). Levy signals how the model and modeler do not pre-exist each other’s becoming; rather, modeling enacts intellectual labor as a way of iterating the model to better capture and respond to the pandemic. These kinds of horizoning work do not deny the temporal dimension of models even as they open important spatial and conceptual possibilities for “mitigating complex futures” (Petryna 2015: 150). By accepting mathematical uncertainty while devising new methods to “get [their] heads around” pandemic conditions, modelers enact horizoning work that brings epidemics within the realm of human intervention.Additionally, spatialization requires interrogating how technical figurations like epidemiologic models are produced. Modelers are aware of and explicit about models’ uses and limitations (Fujii and Henderson 2020). Classic techniques like the widely-used SIR model assume homogeneous “compartments” of human-units, which have equal probability of interacting with each other. More recent techniques have attempted to account for uneven distributions of interaction in subjects’ social worlds. So-called “agent-based” models simulate disease spread by calculating the movements of potentially millions of independently acting “agents” (LANL COVID-19 Team 2020; Begley 2020). Network-based models recognize relation and connectivity as the focus of disease transmission (Ingeno 2020). Modelers are also accounting for plastic parameters by incorporating ever-recalibrating R values, which change depending on the strength of interventions like social distancing (Children’s Hospital of Philadelphia, PolicyLab 2020). Other modelers are moving beyond bounded viral-human configurations to incorporate new variables that impact disease ecology, such as city density, public transportation use, temperature, and humidity (Children’s Hospital of Philadelphia, PolicyLab 2020), even though commonly used spatial models of disease ecology are not yet able to reliably predict viral spread across both “natural” and human built environments (Carlson et al. 2020). These models adjust for the stochastic quality of natural phenomenon as a necessary “practice of continuous self-correction vis-à-vis changing baselines of safety and knowable risk” (Petryna 2015: 155).
Spatialization further challenges the logics by which the curve is used to inform intervention, creating dimensional possibilities for its production, interpretation, and action. The dimensions of the curve have been embodied in a set of “flattening” practices like social distancing and shelter-in-place orders. Now, space is conceived in six-foot increments and new modes of physically-separate sociality. Ironically, these flattening practices leave the mathematically-produced space under the curve intact. In other words, these flattening practices reduce the peak of the curve, literally flattening it, but are not intended to have an effect on the cumulative cases and deaths that constitute the space under the curve. Rather than challenge the singularity of the curve, these flattening practices shape the curve into a unidimensional line that cannot be diminished, only prolonged. Recognizing the spatial dimensions of the curve as a site of intervention, Joia Mukherjee of Partners of Health has called for a new goal of “shrinking” the curve (Mukherjee 2020). Flattening, she notes, does not ultimately change the number of cases, even though it is useful in buffering an already-strained healthcare system from reaching hospital max capacities (Baker and Fink 2020; Emanuel et al. 2020). Shrinking, on the other hand, serves to ultimately decrease the number of cases and deaths through intensive investments in testing and contact tracing (Kim 2020). Shrinking, therefore, represents a second form of spatializing the curve, in addition to indicators of statistical uncertainty. Shrinking would betray the curve’s flexibility, showing us that models can be recalibrated and curves remade into new forms that preserve the future through actions taken in the present. By thinking about the curve as multidimensional and changeable, we create handles with which to maneuver new physical and social possibilities. Shrinking practices intervene on the space under the curve—a site of constant becoming in the midst of an ongoing pandemic—as a site of intervention. We take this intervention further to ask, what becomes hidden in the “empty” space under the curve?
Under the Curve Lies an Uneven Risk Terrain
Taking the spatialization of the curve as our departure point, we consider how space under the curve—as the number of new cases or deaths over time—is so often left blank and empty. In reality, this space “might not be so empty after all, but rather an elaborately staged absence, more like a vacuum, in which certain knowledge of the thing itself…continually disappears” (Petryna 2018, 571). In the case of COVID, that which disappeared—or is hidden—is an uneven risk terrain produced through forms of structural racism and violence. Weeks after the pandemic began, alarming data were published regarding stark racial disparities in COVID-19’s morbidity and mortality, especially among Black (Taylor 2020; Guerra and Glanz 2020) and Indigenous communities (Nagle 2020). These early reports suggest that the curve has smoothed over structural vulnerability and racism that distribute excess burden of COVID risk and disease. As physician Shreya Kangovi states, “the epidemic is not COVID, it’s poverty,” and racism, ableism, and other forms of intersecting oppression that are at once historically structured and individually inscribed on bodies (Figure 2) (South et al. 2020). Spatializing the curve is not simply metaphor or thought experiment; spatializing the curve creates the “fleshy evidence” to see, witness, and intervene, even and especially when we are mandated to stay apart, inside, and at home (Davis and Todd 2017).
Burrowing Our Way to Radical Care
Narrating the curve as a two-dimensional projection of population-level proportions only allows for some expert to comment on when and how this pandemic might end. This forecloses alternative possibilities from within. By spatializing the curve as a dynamic, uncertain, and textured fabric of human-viral relations occurring in space and time, gaps are created that reveal, “a host of underappreciated social and technical activities—the very material of ethnographic concept work that might, in turn, produce a different sort of projection,” (Petryna 2018: 587). Spatializing in this way opens opportunity for response by people and knowledges excluded and neglected in the process of projection. These activities, we argue, are forms of radical care (Hobart and Kneese 2020); they remake the curve, not through flattening, but through acting on the very space where those lines are drawn. Spatializing the injustice under the curve necessitates tracing its substance as a project of mismanagement and neglect, a project that is amplifying a future in which some lives are expendable (Agamben 1998), a project that requires more than epidemiological tools to address. What if we break the curve and burrow below into that space that is so often rendered as blank, empty, absent? By immersing ourselves in that space to look for ways to remake it, we can see that this is no empty two-dimensional space after all. Instead, we are reawakened to the processes by which disease is transmitted because of projects of biopolitical control and necropolitical neglect being carried out within uneven and unjust terrains of risk (Mbembe 2019) (Figure 3). In this uneven terrain, the space under the curve becomes the grounds for sickness and burial. But these are not the only projects here. Ruha Benjamin reminds us “there is a lot happening underground. Not only coffins, but seeds, roots and rhizomes. And maybe even tunnels and other lines of flight to new worlds” (Benjamin 2018). The capacity to act is not solely in the hands of those with this particular kind of intellectual (epidemiological) expertise. Where can we look for forms of action that can hold uncertainty while still making livelihoods within those neglected spaces of curve-worlds?
At the same time, we do not intend to suggest that “good” COVID citizens (Weil 2020), vague references to communities’ “tools” (Taylor 2020), nor individual behavior change like cutting off cigarettes and alcohol (CNN Newsroom 2020) are all that is needed to address the pandemic. We do not pretend calling essential workers “heroes,” flying jet-fighters overhead, or clapping for healthcare workers are the actions that will get us through this pandemic in light of stark material disparities and urgent needs. These needs include addressing the structures that produce the space underneath the curve by finding new configurations for how people can come together, funding public health infrastructures (Davis 2016; Kangovi 2020), and reducing barriers to accessing social safety nets and healthcare. This approach to the COVID horizon lays the groundwork to grow these forms of radical care. As “kind[s] of contemporary equipment for monitoring, managing, and sometimes mitigating complex futures,” (Petryna 2015: 150) forms of horizoning work offers a frame for remaking the world beyond the COVID horizon. By attending to the myriad tactics that infectious disease modelers, healthcare workers, activists, and others use to take incremental actions “amid multidimensional uncertainty,” we may find new intellectual, affective, and relational horizoning techniques that allow for “movement forward, or prevent a crash (or disappearance) of an entire system” during these world-defining events (Petryna 2015: 156).We focus on two interconnected practices of radical care that have proliferated despite (and through) social distancing to attend to other forms of horizoning work beyond spatializing techniques of modeling (Figure 4). Here, we extend another dimension of horizoning work as “a distinct kind of intellectual labor undertaken in conditions in which the fate of entire systems is at stake” (Petryna 2015: 155) to acknowledge other forms of relational and affective labor that are likewise concerned with maintaining social worlds. First, there is surging interest in mutual aid. Mutual aid constitutes “voluntary reciprocal exchange[s] of resources and services for mutual benefit,” (Piepzna-Samarasinha 2018: 33). Those who are at a decreased risk of serious complications and have access to healthcare can undertake necessary activities for elderly, chronically ill, and disabled people if there is a need to leave shelter. The second facet of radical care we wish to draw attention to are care webs (Piepzna-Samarasinha 2018). Care webs or collective care are models of relationality that work by “showing up for each other in mutual aid and respect,” (Piepzna-Samarasinha 2018: 32). Importantly, the underlying ethics and politics of these networks of exchange and care is solidarity, not charity. Models of mutual aid and collective care have long been practiced by marginalized communities as a way to access the care and resources that are otherwise denied by the state. Under COVID, mutual aid and collective care have the potential to remake the risk terrain, thereby intervening on the curve itself. It is through these networks of care and concern aimed toward preserving structurally-precarious systems that these communities have been able to build the kinds of “handles” necessary to conduct horizoning work, as work necessary to protect one another. These forms of radical care constitute horizoning practices that challenge state projects of neglecting the structurally vulnerable and refuse division by the curve that marks the line between who lives and who dies. Radical care stakes claims on the future through direct actions in the present that remake the everyday conditions of existence.
After the Curve Comes the Horizon
As the novel coronavirus has spread through space and time along webs of relations, it has rendered this new terrain visible. The process of understanding and relating to the virus does not occur uniformly over time, but rather, takes on multiple dimensions in space-time as we accelerate and decelerate together (Ross Perfetti and Burson II 2020). So, what can be done beyond physical separation, washing hands, and wearing a mask in the hopes that one’s actions can decrease the velocity of infection? Here, we have argued for forms of radical care that challenge curves without context and the production of that inequitable space underneath them. Those practicing these forms of care are reaching out in this pandemic to assemble care webs, redistribute material resources to mitigate risk, and ultimately engage in a different kind of horizoning work, one that creates possibility for a future in the present for those told not yet, your time will come.
Where the curve stops, horizons continue. Even as the curve will trail off towards the baseline and the pandemic may be declared “over,” the governmental and interpersonal networks of care and support we have highlighted will continue to be essential. The first wave has already begot the “second wave” (Pérez Ortega 2020; Gavin 2020). The second wave may be COVID, economic lockdown, runaway climate change, mental health crises, or collective and individual grief. Spatializing these projected futures opens possibilities for interventions within neglected and excluded peoples and practices, those areas which lie under the curve. Horizons, not curves, we have argued, will guide us as we find new ways to come together, not as an epidemiologically-determined apolitical aggregate, but as engaged collectives who arise out of seemingly insurmountable disconnection.
Special thanks to Colin Hoag for his editorial input, to Adriana Petryna for her insightful feedback and encouragement, and to the Engagement staff for the opportunity to write this piece. This research is supported by the University of Pennsylvania Medical Scientist Training Program.
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Randall Burson II an MD-PhD student in the Department of Anthropology at the University of Pennsylvania. His research is situated at the intersections between anthropology and health services research. He focuses on how health policy and scientific evidence are operationalized and “peopled” in health services, and how patients and providers navigate these services in the US and Latin America. In particular, his long-term ethnographic fieldwork is focused on how biomedical practitioners and indigenous Mapuche healers/leaders enact care and articulate knowledge in Southern Chile’s intercultural health services. He can be found on Twitter at @RandyBurson2.
Angela Ross Perfetti is an MD-PhD student at Harvard University and the Department of Anthropology at the University of Pennsylvania. Her research interests are in sensory worlding and its intersection with knowledge-producing practices of the body and disease in the context of hospital critical care. Also on twitter @pluralperfect.
This post is part of our thematic series: The Event, the Horizon.