CHAPTER 15

Accounting for Care in Times of Crisis

Robert Soden, Jacqueline Wernimont, and Scott Gabriel Knowles

At the height of the COVID-19 pandemic, we were awash in numbers. Numbers counted the sick, the dead, and the vaccinated. News media solemnly reported updated projections daily. Online dashboards doused in red text and foreboding graphics held many of us transfixed to the slightest change in trajectory of the counts. The numbers that we rely on to make sense of crises like the pandemic matter. They matter because they tell us what the crisis is and what its impacts are and gauge the effectiveness of our response. Numbers influence public policy, legitimating some forms of action over others.1 And numbers shape how an event will be remembered and what it will mean in the future.2 We measure and count in response to disasters as a way to ensure that the losses are not forgotten, to put down a mark when it is too hard to tell a story, and to preserve the possibility of accountability. From those numbers, we rebuild memories fragmented by trauma, and we design strategies needed to mitigate or even avoid the next catastrophe.

We place heavy responsibility on these numbers, but they often fail us. Sometimes, as documented by Carroll et al.’s writing on the lack of disaggregated COVID-19 data for the Navajo Nation,3 numbers fail because they are gathered from places of relative privilege. In these situations, lack of data becomes another source of inequity, one that often aligns with other forms of marginalization. Other times, we have the wrong disaster data telling us the wrong story. Take, for example, the 2012 superstorm Hurricane Sandy that hit New York. As Max Liboiron observes, news media and government officials cast storm impacts as an effect of extreme natural disaster, while grassroots organizations struggled to convey how the storm exacerbated a “chronic crisis of poverty.”4 For all their confidence, the numbers we used to count the COVID-19 crisis were wrong. They were wrong in three ways. First, they were often simply incorrect. They were partial estimates, best guesses, and honest attempts to gain purchase on a situation that was moving too fast and at a scale to which our systems were unprepared to respond. Second, the narrow focus on numbers failed to capture all of the various ways in which the pandemic negatively affected society in both the immediate moment and its lasting impacts. Third, and maybe most importantly, the numbers did not account for the ways in which we sought to take care of each other and to keep our communities safe from COVID-19.

In this chapter we look at the numbers surrounding COVID-19—the data trail of a global disaster. After further discussion of the limits of this data, we turn to history to locate the causes for these failures in the genesis of approaches to counting in emergency and disaster management, which flows from two traditions: military preparedness and the insurance and actuarial sciences. In both cases the system we rely on today to describe disasters is heavily tilted toward simplified mortality counts and monetary damage estimates. We then closely examine one particular story that data about COVID-19 failed to tell: the many ways in which we took care of each other during the pandemic. We provide examples of this care work, such as local mutual aid organizing, that went uncounted and evaluate the narrative impacts of this gap. We then describe what it might look like to attempt to account for care during disasters and reckon with both the benefits and the drawbacks and challenges that may accompany such an effort.

Disaster studies scholars, we argue, should advance two strands of emerging research in light of the COVID-19 pandemic. First, important new work at the convergence of epidemiology and social science allows us to more rigorously track the impact of disease beyond the real-time dashboard of case and death totals. Second, the prosocial response to the pandemic by mutual aid groups and communities of grief and memorialization have shaped the lived realities of the COVID era, far outstripping the willingness or ability of public officials to account for these broader forms of social care. This recognition is not a call to give up on measurement. Abandoning numbers entirely seems unlikely or even counterproductive in the technocratic world of disaster response. Even so, disaster studies scholars have the ability to demand more from the numbers, to “account for care,” and to suggest new domains of research in which the qualitative should compete with the quantitative as a form of vital intervention in the service of disaster victims. Ultimately through such efforts we can become more thoughtful and skillful in the choices we make about how and what to measure and the meaning we ascribe to the results.

The Count Is Never the Real Count

In the midst of the pandemic, even our best COVID tracking numbers—the ones to which school officials, medical officers, and governmental decision-makers turn—are incomplete at best and misleading at worst. On the news and in our conversations with our families and friends, we mourn the latest death tolls: nearly 7 million globally and 1.14 million in the United States as of this writing. We speculate about overall infection rates, long COVID cases, and the ongoing global economic impacts of the pandemic. Nevertheless, these kinds of statistics only tell part of the story of how the pandemic has changed and continues to change the world.

Data about disasters is always incomplete as events unfold and remains so for some time after. Deaths caused by disasters go undercounted for many reasons: the limited time and resources available to the public health experts tracking them; complications in categorizing and counting deaths, which is a complex phenomenon when we think about comorbidities and inequality; and outright governmental misdirection. Even when accurate, data is rhetorical—politicians and pundits tip the scales in one direction or another depending on where they stand. Notable examples have included COVID-19 data from Florida, where the data seems to have been sequestered by Governor Ron DeSantis, and New York, where nursing home death undercounts were reported at 50 percent or more.5 Furthermore, since the first cases of COVID-19 were detected in December 2019, data were fundamentally flawed due to human and technological errors. For example, on October 5, 2020, news outlets started reporting that Public Health England missed 15,871 positive test results in its tracing due to human and technical errors.6 Neil Pearce and colleagues have cataloged several early errors in epidemiological tracking, noting that routine health system data was insufficient in the case of a global pandemic.7

In addition to being incomplete, mortality and morbidity numbers are insufficient to capture all of the many ways that disasters wreak havoc on the health of communities both immediately and over the long term. How do we calculate the impacts on those of us who remain—the changed life trajectories, broken families, and lasting trauma that will endure long after the pandemic? A 2020 study estimates that for every person who dies of COVID-19, there are nine close family members who are deeply affected.8 This means that over ten million people in the United States alone have profoundly experienced the loss of a family member or close relation. Understanding the mental health impacts for survivors and family members must also comprise an important metric as we calculate the costs of COVID. Building on the bereavement approach, a 2021 study estimates that in the first year of the pandemic, 1,562,000 children around the world lost a parent or primary caregiver, concluding that “orphanhood and caregiver deaths are a hidden pandemic resulting from Covid-19–associated deaths.”9

Mortality counts also miss the occupational and chronic illness ramifications of COVID, both of which are only beginning to come into focus. For example, consider health care workers impacted by the crisis. In a survey conducted between May and October 2020, 38 percent of US health care workers reported feeling anxiety and depression, while 49 percent had burnout.10 Meanwhile, the American Nursing Association referred to the nursing staff shortage as a national crisis.11 From devastated family members to burnt-out medical staff, COVID-19 has transformed the lives of so many who simply aren’t accounted for in our regular disaster metrics. The consequences of this absence were clear in real time in the United States, where a focus on decreased mortality led many to overlook the worker shortages hobbling health care and other industries, especially during the fourth wave of COVID with the Omicron variant. Only very recently have researchers begun to model the impacts of long COVID on disease survivors. One study finds that more than 50 percent of COVID survivors—thus over twenty-five million in the United States alone—suffer from long COVID symptoms, including “fatigue, dyspnea, chest pain, persistent loss of taste and/or smell, cognitive changes, arthralgias, and decreased quality of life” at least six months after recovery from acute illness. According to the researchers, “there is a dire need to better understand the lasting and emergent effects of Covid-19.”12 The alarm bell is sounding for a wave of chronic illness that we barely understand.

Dashboards as Tools for Tracking and Reporting the Data

The dashboard has become the iconic interface through which people in digitally connected communities have tried to understand the pandemic. Online dashboards reported infections, hospitalizations, vaccinations, vaccine trials, and genetic mapping. The dashboards presented information at local, state, national, and global levels and were created by government agencies, local and national news organizations, nonprofits, and in some cases citizen and academic collaboratives. Most importantly, these visual displays purported to give us the information we needed in order to act.

Of course, the COVID-19 dashboards are not the first example of visualizations of pandemic data. Early modern plague bills—paper sheets—collated and communicated information about the scale and spread of outbreaks throughout Europe, first for royal and religious governments and later for purchase. Government officials used these resources to drive quarantine, policing, and closures, while ordinary individuals used the local information to create or revise their own sense of how to safely navigate their cities (rural areas often had and still have to depend on other information pathways). The information from these handbills and reports were quickly reproduced in newly popular newspapers, and the modern outbreak dashboard was born. Over time, national and international dashboards have served to share the most up-to-date data about disease outbreaks, and newspapers have expanded their publication of mass casualty events to include counts of deaths in armed conflict, ranging from drug overdoses and gun violence to vehicular accidents and climate events.

Some dashboards and journalistic counters persist for a long time, and others emerge for a short while and then close down. For example, the widely celebrated Johns Hopkins Coronavirus Research Center dashboard stopped collecting and reporting COVID data on March 10, 2023, two months before the United States ended the federal public health emergency. While the World Health Organization (WHO) announced on May 5, 2023, that the COVID-19 international public health emergency had ended, the WHO dashboard remains active, as does its mortality tracking, and the Our World in Data dashboard switched its time series data to WHO data in order to maintain a consistent source.13 While historical use of dashboards in vehicles, mortality bills, and US war rooms was for decision support, governments and international organizations have also deployed data dashboards for reporting and public accountability purposes.

Inheritances from the Cold War

In the early years of the Cold War, the US government’s civil defense planning agencies quantitatively modeled for the first time what it might look like for the nation to face a mass casualty disaster. The disaster these planners had in mind was not a pandemic; it was a nuclear attack. Civil defense planners used the destruction wrought on Germany and Japan as documented in the United States Strategic Bombing Survey reports as a vital primary source to guide their conceptualizations of how infrastructures and bodies would be maimed and destroyed by nuclear war.14 As Jennifer Light documents in From Warfare to Welfare: Defense Intellectuals and Urban Problems in Cold War America, these models of destruction had wide influence across many domains of American life, especially in high-tech development and urban planning, where the logic of dispersal from urban cores flowed logically from the fear of atomic attack on cities.15 In these years civil defense planners in Washington designed and helped lead elaborate exercises for individual cities across the nation to practice nuclear holocaust. Tabletop exercises with estimated numbers of bombs, buildings destroyed, people injured or killed, water and electric supplies disrupted that were conducted by city and state officials and business leaders were practiced year after year from the late 1940s into the 1980s from Baltimore to Chicago to Seattle.

By the 1970s, city and state officials demanded that such planning must be more effectively tailored to meet the real disasters they faced in the communities every year: nuclear plant disasters, not nuclear war, alongside hurricanes, earthquakes, and all other types of disasters that happened in the real world. With a hiatus in the 1990s, such exercises were resumed after the September 11, 2001, attacks. Communists were replaced by terrorists, but the logic was the same: destruction must be mathematized in order to allow the nation’s leaders to effectively plan for disaster. This type of mass casualty modeling emphasized disaster planning as a tool of war readiness and as such imagines a nation of soldiers fighting for survival, living or dying—a binary mindset of preparedness. In these imaginaries there are no metrics for fear, fatigue, post-traumatic stress, and social fractures under stress. As Andrew Lakoff and Stephen Collier document in their 2021 book The Government of Emergency: Vital Systems, Expertise, and the Politics of Security, civil defense planning and its imaginaries of mass nuclear death also impacted the ways that pandemic planning developed in the United States.16 This inheritance has strongly shaped the emphasis on funding equipment over training, compensation for material loss over human stress, and a mindset that continuity of the economy and the government must be prioritized above all else.

Accounting for Care

Thinking beyond human suffering and economic impacts, we also see that the COVID numbers rarely capture another crucial aspect of the disaster: the enormous efforts people have undertaken since early 2020 to sustain, repair, and strengthen their communities. Community aid is common during disasters. Notwithstanding popular myths about helplessness, panic, and looting, people in times of acute disaster are historically prosocial.17 More often than not, we behave rationally and altruistically to address the needs left unmet by broken systems. Neighbors are a vital but too often ignored part of the network of first responders who are working to keep individuals and families safe during a crisis. In our public discourse, there is widespread knowledge of mortality and infection data, but we know woefully little about the work that our communities and neighbors performed every day to help each other through this slow disaster. During the height of the pandemic, mutual aid organizations around the country made thousands of deliveries of groceries and lifesaving medicines for their homebound and at-risk neighbors.18 Communities and activists pooled together millions of dollars so that people who lost income or were struggling to make ends meet could pay their rent and their utility bills. But we have no statistics that even begin to capture this informal but critical response to the crisis.

Despite arguments in the humanities and social sciences for greater attention to the vital, if often mundane, role that care work plays in the production of everyday life, such work remains mostly invisible.19 This work is often done by women and people of color from some of our most vulnerable communities.20 The fact that we don’t have adequate metrics of care has a great deal to do with this: those providing the care have historically seen their labor undervalued and underrepresented even in nondisaster times.21 Much of this work has gone uncounted in public narratives about COVID, and this matters if we wish to truly reckon with the impact of this pandemic and if we expect government and other preparedness institutions to be better ready for the next pandemic. In technocratic societies if we don’t count care work, it is difficult to see. The accounting and reckoning we do today are what will be preserved in the historical record, and that record informs future disaster policy and emergency management funding. Making care visible as a disaster measure in both public discourse and scholarly work also helps highlight all of the ways in which the government response is failing to serve the most vulnerable among us, and some of these ways are unknown or unexpected. Accounting for care prefigures where we need to go and how we will mend our communities and build resilience to not just COVID-19 but also the many entangled emergencies that we are facing.

While such actions may seem unmeasurable, this feeling is itself an artifact of a disaster mindset that draws heavily on war and the market as frameworks for understanding the pandemic and disasters more generally. Deaths and dollars are the measures that matter in those frames. Metrics are often deployed in order to increase transparency and accountability for people and organizations with power and responsibility. While gathering metrics can be a tool of management, we can also use them in order to serve those who are impacted by the decisions and indecisions of government and large corporate entities. Yeshimabeit Milner notes that “data is a powerful tool for social change.”22 The development or extension of metrics of care within public discussions of disaster impacts and scholarly disaster research is needed to understand the scope and scale of care work that individuals and communities have undertaken in response to COVID-19.

No attempt to measure the care that communities do for each other will successfully account for all of the vital work that marks the COVID era, but that is true of all disaster data. We have resources available to us now—data from Facebook, Reddit, and NextDoor groups, for example—that might give us a glimpse. Amid the early waves of the pandemic, the TownHall Project created a national registry of local mutual aid groups.23 Hospitals and schools track overtime of their staff, but this data is rarely aggregated in ways that show us the true scope of how the labor force responded to the pandemic. Crowdfunding websites such as GoFundMe were used extensively by mutual aid groups to support their work, but to our knowledge no study has yet aggregated the full amount of these donations. Within disaster studies scholarship and disaster response practices, we can build on these data points to develop more expressive and complex methods of accounting not just for the deaths of COVID-19 but also to see more clearly how we are responding to the long-term damage being done through psychological and economic trauma. At the same time, we should be able to draw strength from efforts to reveal care in action within our communities. These indicators of care may bolster the forms of solidarity that we need to navigate toward a less catastrophic future.

In addition to developing better disaster metrics, disaster scholars should draw on tools from the humanities and social sciences to document loss and care during events such as the COVID-19 pandemic. There have been a number of recent academic studies of this kind, including an analysis of challenges and solidarities experienced by frontline medical staff in the United Kingdom and a study of the mutual aid response to the pandemic in New York City.24 Furthermore, memorialization projects such as #FacesofCOVID and the New York Times feature “Those We’ve Lost” are utilizing memorial narratives and personal storytelling to help people recognize the people behind the dashboard numbers.25 Similarly, the Covid Memorial Wall, which began as a small-scale personal expression of loss and memorialization, has grown into an official national memorial and a collective site of art therapy.26 This kind of work offers invaluable insights into the politics and lived experience of crises and a critical perspective on the limits of contemporary practices for quantifying disaster and can be useful for both the public and individual family members who are struggling to come to terms with debilitating loss. Metrics matter, but other methods of accounting for the impacts of the COVID pandemic and the breadth of ways our communities have responded are also needed.

In 2022, the authors hosted a small online workshop that brought together disaster researchers, designers, data scientists, and public health experts to examine the COVID data dashboards that for so many people have provided a view of our current crisis. Over the few hours we spent together, participants asked critical questions: Who is the audience for these tools? What assumptions about the interests and capacities of this audience do dashboard creators make? What is included in the narratives of the pandemic that these dashboards convey? What is left out? We also asked them to draw alternatives. The designs they sketched challenged notions of agency, impacts, and authority that are baked into the data we use to make sense of COVID-19 and pointed toward a much broader set of options we can consider. This is the beginning of a research process aimed toward developing alternatives for more inclusive and humane collection and communication of data about disaster.

In this chapter we have raised some areas where more work can be done in terms of both collecting data and presentations of that data for different audiences, and there is much work to do. In a very real sense, all social science research about contemporary life is disaster research. It is time that we start to draw on the breadth of this expertise in developing the data and dashboards we use to tell the story of crises.

Notes

1. 1.  Donna Haraway, Staying with the Trouble: Making Kin in the Chthulucene (Duke University Press, 2016).
2. 2.  Robert Soden and Austin Lord, “Mapping Silences, Reconfiguring Loss: Practices of Damage Assessment & Repair in Post-earthquake Nepal,” Proceedings of the ACM on Human-Computer Interaction 2, CSCW (2018): 1–21.
3. 3.  Stephanie Russo Carroll, Desi Rodriguez-Lonebear, Randall Akee, Annita Lucchesi, and Jennifer Rai Richards, “Indigenous Data in the Covid-19 Pandemic: Straddling Erasure, Terrorism, and Sovereignty,” Items, June 11, 2020, https://items.ssrc.org/covid-19-and-the-social-sciences/disaster-studies/indigenous-data-in-the-covid-19-pandemic-straddling-erasure-terrorism-and-sovereignty/.
4. 4.  Max Liboiron, “Disaster Data, Data Activism: Grassroots Responses to Representing Superstorm Sandy,” in Extreme Weather and Global Media , ed. Julia Leyda and Diane Negra (Routledge, 2015).
5. 5.  Luis Ferré-Sadurní, “Health Agency under Cuomo ‘Misled the Public’ on Nursing Home Deaths,” New York Times, March 15, 2022.
6. 6.  Gary Hampson et al., “Open Collaboration, Data Quality, and Covid-19,” IEEE Software 38, no. 3 (2021): 137–141.
7. 7.  Neil Pearce et al., “Accurate Statistics on Covid-19 Are Essential for Policy Guidance and Decisions,” American Journal of Public Health 110, no. 7 (2020): 949–51.
8. 8.  Ashton M. Verdery et al., “Tracking the Reach of Covid-19 Kin Loss with a Bereavement Multiplier Applied to the United States,” Proceedings of the National Academy of Sciences of the United States of America 117, no. 30 (2020): 17695–701.
9. 9.  Susan Hillis et al., “Global Minimum Estimates of Children Affected by Covid-19–Associated Orphanhood and Deaths of Caregivers: A Modelling Study,” The Lancet 398, no. 10298 (July 2021): 10298.
10. 10.  Sara Berg, “Half of Health Workers Report Burnout amid Covid-19,” American Medical Association, July 20, 2021, https://www.ama-assn.org/practice-management/physician-health/half-health-workers-report-burnout-amid-covid-19.
11. 11.  Ernest Grant, letter to Secretrary of Health and Human Services Xavier Becerra from the American Nurses Association, September 1, 2021.
12. 12.  Destin Groff et al., “Short-term and Long-term Rates of Postacute Sequelae of SARS-CoV-2 Infection: A Systematic Review,” JAMA Network Open 4, no. 10 (2021): e2128568.
13. 13.  World Health Organization, “Statement on the Fifteenth Meeting of the IHR (2005) Emergency Committee on the COVID-19 Pandemic,” May 3, 2023, https://www.who.int/news/item/05-05-2023-statement-on-the-fifteenth-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-coronavirus-disease-(covid-19)-pandemic.
14. 14.  United States Strategic Bombing Survey: Summary Report (Pacific War) (Washington, DC: US Government Printing Office, 1946). See also The United States Strategic Bombing Surveys (European War) (1945; repr., Air University Press, Maxwell Air Force Base, 1987).
15. 15.  Jennifer S. Light, From Warfare to Welfare: Defense Intellectuals and Urban Problems in Cold War America (Johns Hopkins University Press, 2005).
16. 16.  Stephen J. Collier and Andrew Lakoff, The Government of Emergency: Vital Systems, Expertise, and the Politics of Security (Princeton University Press, 2021).
17. 17.  Jamil Zaki, “Catastrophe Compassion: Understanding and Extending Prosociality under Crisis,” Trends in Cognitive Sciences 24, no. 8 (2020): 587–89.
18. 18.  Robert Soden and Embry Owen, “Dilemmas in Mutual Aid: Lessons for Crisis Informatics from an Emergent Community Response to the Pandemic,” Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW2 (2021): 1–19.
19. 19.  Berenice Fisher and Joan C. Tronto, “Toward a Feminist Theory of Caring,” in Circles of Care: Work and Identity in Women’s Lives, ed. Emily K. Abel and Margaret K. Nelson (SUNY Press, 1990).
20. 20.  María Puig de la Bellacasa, Matters of Care: Speculative Ethics in More Than Human Worlds (University of Minnesota Press, 2017).
21. 21.  Miriam Ticktin, Casualties of Care: Immigration and the Politics of Humanitarianism in France (University of California Press, 2011).
22. 22.  Ashoka, “Why We Need Data for Black Lives,” Forbes Magazine, December 11, 2019.
23. 23.  “TownHall Project,” Mutual Aid Hub, 2020, https://www.mutualaidhub.org/.
24. 24.  Cecilia Vindrola-Padros et al., “Perceptions and Experiences of Healthcare Workers During the Covid-19 Pandemic in the UK,” BMJ Open 10, no. 11 (2020).
25. 25.  Jeffrey A. Bennett, “Mourning and Memorializing in the COVID-19 Era,” Communication and Critical/Cultural Studies 19, no. 1 (2022): 30–36.
26. 26.  Dorian Lynskey, “Wall of Love: The Incredible Story Behind the National Covid Memorial,” The Guardian, July 18, 2021.