CHAPTER 12

Disaster Multiplied: COVID-19 Bereavement

Emily Smith-Greenaway, Ashton M. Verdery,
Rachel Margolis, and Haowei Wang

The severity of disasters is typically quantified by the number of lives lost—a single statistic that helps us to immediately scale the amount of suffering. Sometimes researchers expand the enumeration of “casualties” to count others at the periphery of the deceased—those injured or displaced by a disaster, alive but measurably affected. The stories of survivors and those who lost loved ones are often told in the media, literature, and film, but only rarely do researchers take stock of or scale those whose lives have been upended by disaster-induced bereavement—the experience of losing a loved one to death.

Although bereavement from disasters is rarely quantified, there is strong evidence of its importance. Bereavement generally is strongly associated with adverse health impacts on the affected,1 operating through a host of biopsychosocial mechanisms and stress processes,2 and corresponds with a range of other social challenges, such as reduced educational attainment and long-lasting health disadvantages.3 Disaster-induced bereavement is particularly detrimental. Studies of those exposed to disasters routinely find that the bereaved have among the worst outcomes.4 Theoretical5 and empirical works both highlight that disaster-induced bereavement is likely to be more detrimental than bereavement under typical circumstances.6

As such, without an understanding of the scale of bereavement a disaster induces, the totality of its population health impacts cannot be known. Unfortunately, quantifying disaster-induced bereavement is empirically difficult because of the challenges inherent in identifying those affected. When social scientists have studied bereavement in the context of disaster, they typically turn to standard data collection approaches; although some of these approaches are well suited for select disasters, they often have shortcomings, making them a poor match depending on the magnitude, toll, and duration of a disaster. The first contribution of this essay is to describe our efforts to expand the repertoire of approaches to studying bereavement in the context of disasters through a multiplier approach. A second contribution is that we highlight the practical and theoretical value of disaster studies that focus on those whose lives have been intimately altered by the death of others by discussing recent research on COVID-19 bereavement and its secondary population health effects. Research that quantifies the scale and scope of disaster-induced bereavement can also help to ground narratives portrayed in other media (e.g., journalism, poetry, and film), expanding awareness of the challenges facing bereaved populations. There is great potential for studies of disaster-induced bereavement to wed previously siloed literature in ways that make new theoretical advancements and to fundamentally expand our dimensional perspectives of disasters.

Tracking Disaster-Induced Bereavement Burden

Although few studies have addressed disaster-induced bereavement more broadly, many studies have focused on a specific form of loss, namely orphanhood. Arguably the most widely used approach to study orphanhood induced by disasters is through representative surveys. Survey-based approaches have been used widely in the case of the HIV/AIDS epidemic, which meets the parameters of the United Nation’s definition of a disaster in many sub-Saharan African countries,7 allowing researchers to estimate what percentage of the child population or households have been affected. The sheer scale of the HIV/AIDS crisis in many sub-Saharan African countries made it alarmingly easy for representative household surveys to “capture” the orphan population and study its outcomes relative to the nonorphan population. For instance, using data from the Demographic and Household Survey, Bicego and colleagues documented the varying extent of the crisis in seventeen sub-Saharan African countries.8

Many disasters are more geographically localized than the HIV/AIDS crisis and also geographically displace affected people. These issues complicate efforts to field a probability sample of bereaved survivors. In such scenarios, those who remain in the disaster zone are a select and potentially biased subsample of those who experienced the event, and any effort to sample those who migrated after the disaster is challenging without knowledge of who they are and where they might have gone—akin to finding a needle in a haystack. Some surveys have still proven useful for studying localized disasters but only in cases wherein well-established predisaster research infrastructure was already in place, thus offering a serendipitous opportunity for researchers to use their existing samples to understand how households and families were affected. The following events, for example, allowed researchers to use existing research infrastructure to offer insights postdisaster: the Indonesian Family Life Survey in the case of the Indian Ocean Tsunami,9 the Chitwan Valley Family Study in the case of the Nepalese Civil War,10 the Japanese Gerontological Evaluation Survey in the case of 2011 Japanese Earthquake and Tsunami,11 and the Demographic and Health Survey in the case of the 2010 Haiti earthquake.12 In many cases, however, such pre- and postdisaster designs are limited to select subpopulations. For instance, research on Hurricane Katrina survivors in the United States draws heavily from samples of community college students who were participating in a preexisting study when the hurricane made landfall13 or those displaced to a specific location.14

Without such predisaster infrastructure, however, surveys are often ill-equipped to identify those affected, including the bereaved. Creating a sampling frame and fielding surveys to a representative population requires an enormous amount of human and material resources. As such, survey efforts can result in a notable lag between the time of the disaster and the tracking of the population affected by it—a lag that can prevent researchers from offering an immediate perspective of the number and outcomes of individuals affected. Moreover, survey data on family deaths can suffer recall biases associated with social network data collection,15 making a lag between the disaster and the collection of data of further concern.

Additionally, using surveys to track disaster-induced bereavement is difficult in the case of slow-moving disasters with small or still climbing death tolls. For instance, in the context of COVID-19 bereavement, identifying people affected by bereavement in a representative framework or subsets of bereaved people, such as children orphaned by the pandemic, would be incredibly difficult given the relatively rare nature of COVID-19 bereavement even for countries with relatively high death tolls. Moreover, surveys often provide only a single snapshot of a population’s bereavement burden—a moment in time. As such, they are particularly ill-suited for capturing disaster-induced bereavement in the contexts of evolving disasters. The prolonged nature of the COVID-19 pandemic, for example, quickly rendered survey-based estimates of bereavement irrelevant, offering neither contemporaneous insights nor a framework to help understand where things were headed.

Given these limitations, other researchers have relied on generating estimates of disaster-induced bereavement indirectly by relying on other existing population data. For instance, demographers and epidemiologists have used United Nations Population Division data, including mortality and fertility rates as well as HIV prevalence rates, to estimate the incidence and prevalence of HIV/AIDS parental bereavement in the case of sub-Saharan Africa.16 Unlike surveys, these indirect estimation strategies not only provide current estimates of bereavement but also can make use of projection data to project the future burden of bereavement.

Although indirect estimation approaches provide notable advantages over survey-based ones, including their cost effectiveness and their potential to generate projections, they also come with notable shortcomings, including that the existing data is often not available for local, disaster-affected populations. Moreover, although indirect methods creatively identify bereaved populations based on other related population rates, they are, correspondingly, often constrained in the types of bereavement that they can capture. That is, given the availability of mortality and fertility schedules, we can typically only study child17 or parental bereavement18 with these approaches. Thus, the lack of flexibility to study other relational losses is a notable limitation of indirect approaches, especially given the robust evidence that losing all manner of family members can be detrimental to the bereaved.19

Advancing Efforts to Track Disaster-Induced Bereavement: A Multiplier

The shortcomings of these approaches, which made them especially ill-suited to study bereavement in the context of COVID-19—a disaster of great magnitude yet an initially small but slowly rising death toll—led our team to pursue computational methods. In the spring of 2020, we set out to generate a flexible tool that overcame the pitfalls of other strategies and would allow us to track what was a relatively rare phenomenon in the large US population, COVID-19 bereavement, and do so in lockstep fashion with the rising death toll. We thus made use of computational analysis of COVID-19 mortality using kinship networks estimated from demographic microsimulations20 and validated against empirical data.21 Simulated kinship networks enabled us to identify how many of each type of kin are alive at different ages so that we could estimate how many close family members might experience the unexpected loss of kin due to COVID-19 overall and by race, age group, and kin type.

In many ways, the building blocks of microsimulations are comparable to those of indirect estimation techniques. Both make use of existing population data and computational techniques to infer new findings about the present and the future. As such, these simulations allowed us to provide future projections of the total number of individuals anticipated to be bereaved by COVID-19 under various epidemiological scenarios. However, recognizing the value of tracking bereavement during the unfolding disaster of the pandemic, we conceptually and empirically went one step further to create an additional indicator, coined a “bereavement multiplier.” We estimated the ratio of the number of close relatives who are bereaved by each single COVID-19 death.22 Specifically, these estimates included only those who lost a spouse or a biological parent, child, sibling, or grandparent and did not include an even wider net of those potentially affected, such as those who lost cousins, aunts and uncles, step-family, and others. We expressed the multiplier with a simple rounded number: nine total bereaved for each death in the United States. The multiplier gained considerable media attention with thousands of print, television, radio, and podcast references to it. Our research scaling the burden of bereavement afforded journalists with a clear hook for motivating the more personal narratives and intimate stories of loss that they told during the pandemic, allowing them to emphasize the sheer scale of loss that our country was experiencing. Although much of the interest in our work owed to COVID-19’s importance to the public, we suspect that the ease by which the public could interpret and recall our scientific findings also raised the profile of our work.23

Beyond providing a backdrop for numerous journalistic accounts, the multiplier approach allowed us to extend the study of disaster-induced bereavement in ways that surveys and indirect estimation techniques would not. First, we were able to track the rise in bereavement without any lag or delay, allowing us to track the burden of the COVID-19 pandemic as it grew heavier by the day. The multiplier approach also allowed us to step out of the framework so commonly constraining scholars interested in the bereavement toll of a disaster. We were able to offer not only in-the-moment estimates or potential projections but also an estimation approach that would allow us to track the growing bereavement burden in real time.

Second, we were able to expand beyond very specific “proximate others” to consider bereavement among a wider kinship network, including grandparents, parents, siblings, spouses, and children, without administering an exhaustive family history module. This proved especially useful for recognizing a group experiencing a hitherto unseen burden of COVID-19 bereavement: children under the age of eighteen. Attesting to the value of emphasizing the burden of COVID-19 bereavement on children, our JAMA-Pediatric article,24 which used the multiplier to quantify the number of children who lost parents, received more media attention than any other article in that journal in 2021.

Third, our computational approach allowed us to track inequalities between subpopulations. Whereas indirect approaches often rely on aggregated data for a single geopolitical population, collected for the purpose of generating country-wide estimates, our approach provided (some) flexibility to understand within-population differences in the burden of bereavement. With race-disaggregated data, our multiplier approach allowed us to produce race-specific estimates of the total number of bereaved individuals using the current death toll and simple multiplication. Subsequent work extended our methods to consider differences between countries in the excess bereavement caused by COVID-19.25

The Need to Track Disaster-Induced Bereavement

A rich bereavement literature emphasizes the need to track disaster-induced bereavement from public health, social well-being, and equity frameworks. Long before the world experienced COVID-19, a burgeoning literature outlined the implications of family bereavement for individuals’ social, economic, physical, and mental well-being.26 Given the toll of COVID-19 bereavement that our multiplier documented in the United States, we offered some of the first insights into the implications of COVID-19 bereavement for those affected. We made use of data from twenty-seven countries to study the consequences of COVID-19 bereavement for older adults’ well-being specifically. This research showed that COVID-19 bereavement is associated with significantly higher probabilities of both reporting depression and its worsening among older adults.27 Moreover, net of one’s own personal loss, living in a country with a higher COVID-19 mortality rate is associated with older women’s reports of worsened depression but not for men.

Given the lingering mental health implications of COVID-19 bereavement, we grew interested in whether these results could signal that COVID-19 bereavement is even worse than pre–COVID-19 bereavement. As many readers of this volume are aware, there is a vibrant literature outlining the societal implications of disasters and their many faces. Motivated by this literature, we were interested in understanding whether the layering of the disaster and the bereavement could correspond with distinctions in the implications of COVID-19 bereavement for survivors. On the one hand, COVID-19 bereavement could be less consequential given its disaster dimension. That is, COVID-19 bereavement may be a less lonely death because so many families were simultaneously grappling with the horrors of the pandemic. On the other hand, COVID-19 losses could be distinctly difficult for individuals to navigate. That is, sociologists have demonstrated how disasters can strain social systems28 and have emphasized that COVID-19 deaths are especially “bad” deaths;29 thus, the simultaneous implications of dying and mourning amid social upheaval could be distinctly harmful.

In our analysis, we found the latter to be true: COVID-19 deaths are distinctly harmful to those bereaved by them. To document this, we took advantage of a survey that was in the field when COVID-19 stay-at-home orders went into effect, analyzing Wave 8 of the longitudinal Survey of Health, Aging, and Retirement in Europe. This wave of the survey began in November 2019 and had interviewed about half of its intended respondents (a mix of longitudinal cases followed from prior rounds and new refresher cases) when it had to pause data collection in March 2020 because of the accelerating pandemic (Pre-COVID Round). The Survey of Health, Aging, and Retirement in Europe resumed interviews between June and August 2020, interviewing the remaining intended respondents and reinterviewing those who participated in the November 2019–March 2020 data collection (COVID Round). Using a novel pseudo experimental design and the unique timing of the survey, we tested whether those whose spouse died in the three months prior to the respondents’ interview in the Pre-COVID Round experienced worse, comparable, or less depression, loneliness, and trouble sleeping than those whose spouses died of COVID-19 in the three months prior to the COVID Round interviews. Under a variety of specifications that controlled for different attributes, exposures, and other relevant features, we found that those who lost their loved ones to COVID-19 had more depression and loneliness than comparable peers who lost loved ones to other diseases prior to the pandemic.30 We have extended this study with a new analysis that examines whether these differences are a feature of losing someone to this specific disease (COVID-19) or losing someone to any disease during such a difficult time (the pandemic).31

The Future of Disaster-Induced Bereavement Studies

Going forward, we see many innovative and useful avenues for disaster-induced bereavement studies to shape how society thinks about and responds to disasters and to advance two parallel literatures: research on bereavement and research on disasters.

Beginning with the potential for this work to shape the social experience of a disaster, we first suspect that by providing a framework to estimate the burden of COVID-19 bereavement, our research helped shape discourse about this otherwise hidden toll of the pandemic—a toll that would have been abstractly acknowledged yet otherwise have been obscured by a lack of estimates or biased ones. As Soden, Wernimont, and Knowles aptly state in Chapter 15: “if we don’t count care work, it is difficult to see.” With bereavement, what we do not count may go entirely unseen. By studying those directly affected by the death that occurs within the context of a catastrophic event, bringing studies of disaster-induced bereavement to the foreground of disaster research will allow us to expand on historically narrow understandings of who is affected within the rubric of a disaster, rescaling our understanding of the survivors’ toll of a death toll. As Stehrenberger notes in Chapter 5, we see great potential in disaster research as a transformative enterprise. Quantification such as the bereavement multiplier can directly complement media reporting the stories of those who lost loves ones and literature, film, and art that commemorates the deceased, as we found in our own work.

Disaster-induced bereavement studies have the potential to also make theoretical headway in understanding bereavement. Sociologists have increasingly taken on the study of bereavement, which is rooted deeply in psychology, working to attend to the potential differential consequences of loss or their differential implications for individuals. In effect, sociologists have tried to infuse bereavement studies with recognition that social structures and institutions matter. An example is a study that examines how racism affects who is bereaved, creating a feedback loop to racial disparities in health across the life course.32 Another example is research that has examined the consequences of bereavement for more sociological mechanisms such as educational derailment.33

Efforts to shed light on the particularities of disaster-induced bereavement will further encourage bereavement studies to advance our understanding of the social patterning of losses and how they affect individuals’ well-being. Often social scientists treat disasters uniformly as shocks, unexpected exogenous events that have adverse consequences for the populations they affect. However, disaster studies could help advance an understanding of their particularities. For example, disaster research often emphasizes the capacity for community resilience as a moderating factor in the pace and success of recovery. The high-trust community context of Japan enabled greater resilience to the Fukushima disaster, for instance. Although it has long been acknowledged that losing relatives to violent events or natural disasters can produce specific difficulties, more case-specific studies will allow researchers to build a more comprehensive theoretical model of disaster-induced bereavement and its potential variability. Bereavement research has much to gain by considering the ways embeddedness in different social structures might amplify or suppress bereavement effects; an example of this, albeit one still at the microsociological level, is recent work examining whether widowhood effects differ by the connections the bereaved had to their deceased spouse’s social network contacts.34 Ultimately, the availability of multiple case studies of different disasters could allow us to develop a more nuanced understanding of the distinctions in disaster-induced bereavement.

Along these same lines, studying the differential impact of loss in the context of slow-moving disasters would further offer insights into our understanding of the experiences of disasters and bereavement. For example, efforts to parcel out bereavement effects caused by a disaster from bereavement effects that would have been expected to occur even in the absence of the disaster could be instructive. Recent work offers some approaches for thinking about constructing these baselines35 and for quantifying whether they differ in their effects.36

Finally, we anticipate that a concerted effort to advance research on disaster-induced bereavement will also advance disaster research itself. In the context of particularly violent or traumatizing disasters, studies often emphasize the lingering psychological consequences for the surviving population, outlining the rates, expressions, and possible treatment for post-traumatic stress disorder. Although trauma and bereavement often coincide in disaster-affected populations, they are not mutually exclusive.37 More effort to expand the strong tradition of studying trauma to also consider bereavement will recognize the even larger population of survivors that are measurably affected.

Notes

1. 1.  Margaret Stroebe, Henk Schut, and Wolfgang Stroebe, “Health Outcomes of Bereavement,” The Lancet 370, no. 9603 (2007): 1960–73.
2. 2.  Debra Umberson, “Black Deaths Matter: Race, Relationship Loss, and Effects on Survivors,” Journal of Health and Social Behavior 58, no. 4 (2017): 405–20.
3. 3.  Michelle Livings, Emily Smith-Greenaway, Rachel Margolis, and Ashton M. Verdery, “Bereavement & Mental Health: The Generational Consequences of a Grandparent’s Death,” SSM-Mental Health 2 (2022): 100100; and Sarah E. Patterson, Ashton M. Verdery, and Jonathan Daw, “Linked Lives and Childhood Experience of Family Death on Educational Attainment,” Socius 6 (2020): 2378023120975594.
4. 4.  Elizabeth Frankenberg et al., “Mental Health in Sumatra after the Tsunami,” American Journal of Public Health 98, no. 9 (2008): 1671–77; Elizabeth Frankenberg, Cecep Sumantri, and Duncan Thomas, “Effects of a Natural Disaster on Mortality Risks Over the Longer Term,” Nature Sustainability 3, no. 8 (2020): 614–19; Ethan J. Raker, Sarah R. Lowe, Mariana C. Arcaya, Sydney T. Johnson, Jean Rhodes, and Mary C. Waters, “Twelve Years Later: The Long-Term Mental Health Consequences of Hurricane Katrina,” Social Science & Medicine 242 (2019): 112610; and Ethan J. Raker, Meghan Zacher, and Sarah R. Lowe, “Lessons from Hurricane Katrina for Predicting the Indirect Health Consequences of the COVID-19 Pandemic,” Proceedings of the National Academy of Sciences 117, no. 23 (2020): 12595–97.
5. 5.  Deborah Carr, “A ‘Good Death’ for Whom? Quality of Spouse’s Death and Psychological Distress Among Older Widowed Persons,” Journal of Health and Social Behavior 44, no. 2 (2003): 215–32; and Margaret Stroebe, Susan Folkman, Robert O. Hansson, and Henk Schut, “The Prediction of Bereavement Outcome: Development of an Integrative Risk Factor Framework,” Social Science & Medicine 63, no. 9 (2006): 2440–51.
6. 6.  Haowei Wang, Emily Smith-Greenaway, Shawn Bauldry, Rachel Margolis, and Ashton M. Verdery, “Mourning in a Pandemic: The Differential Impact of COVID-19 Widowhood on Mental Health,” Journals of Gerontology: Series B 77, no. 12 (2022): 2306–16.
7. 7.  Lara Stabinski, Karen Pelley, Shevin T. Jacob, Jason M. Long, and Jennifer Leaning, “Reframing HIV and AIDS,” BMJ 327, no. 7423 (2003): 1101–3.
8. 8.  George Bicego, Shea Rutstein, and Kiersten Johnson, “Dimensions of the Emerging Orphan Crisis in sub-Saharan Africa,” Social Science & Medicine 56, no. 6 (2003): 1235–47.
9. 9.  John Strauss, Firman Witoelar, and Bondan Sikoki, “The Fifth Wave of the Indonesia Family Life Survey: Overview and Field Report,” Vol. 1, working paper (RAND Corporation, 2016).
10. 10.  William G. Axinn, Dirgha Ghimire, and Nathalie E. Williams, “Collecting Survey Data During Armed Conflict,” Journal of Official Statistics 28, no. 2 (2012): 153.
11. 11.  Yuri Sasaki, Jun Aida, Taishi Tsuji, Shihoko Koyama, Toru Tsuboya, Tami Saito, Katsunori Kondo, and Ichiro Kawachi, “Pre-Disaster Social Support Is Protective for Onset of Post-Disaster Depression: Prospective Study from the Great East Japan Earthquake & Tsunami,” Scientific Reports 9, no. 1 (2019): 19427.
12. 12.  Julia Andrea Behrman and Abigail Weitzman, “Effects of the 2010 Haiti Earthquake on Women’s Reproductive Health,” Studies in Family Planning 47, no. 1 (2016): 3–17.
13. 13.  Mary C. Waters, “Life After Hurricane Katrina: The Resilience in Survivors of Katrina (RISK) Project,” Sociological Forum 31 (2016): 750–69.
14. 14.  Kerrie Glass, Kate Flory, Benjamin L. Hankin, Bret Kloos, and Gustavo Turecki, “Are Coping Strategies, Social Support, and Hope Associated with Psychological Distress Among Hurricane Katrina Survivors?,” Journal of Social and Clinical Psychology 28, no. 6 (2009): 779–95.
15. 15.  Jimi Adams, Gathering Social Network Data (Sage, 2020); and Dennis M. Feehan and Gabriel M. Borges, “Estimating Adult Death Rates from Sibling Histories: A Network Approach,” Demography 58, no. 4 (2021): 1525–46.
16. 16.  Susan S. Hunter and John Williamson, Children on the Brink: Strategies to Support a Generation Isolated by HIV/AIDS (United States Agency for International Development, 2000).
17. 17.  Susan D. 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 (2021): 391–402; and Susan D. Hillis et al., “COVID-19–Associated Orphanhood and Caregiver Death in the United States,” Pediatrics 148, no. 6 (2021): e2021053760.
18. 18.  Diego Alburez-Gutierrez, Martin Kolk, and Emilio Zagheni, “Women’s Experience of Child Death over the Life Course: A Global Demographic Perspective,” Demography 58, no. 5 (2021): 1715–35; and Emily Smith-Greenaway et al., “Global Burden of Maternal Bereavement: Indicators of the Cumulative Prevalence of Child Loss,” BMJ Global Health 6, no. 4 (2021).
19. 19.  Felix Elwert and Nicholas A. Christakis, “Wives and Ex-Wives: A New Test for Homogamy Bias in the Widowhood Effect,” Demography 45, no. 4 (2008): 851–73; Jason Fletcher, Marsha Mailick, Jieun Song, and Barbara Wolfe, “A Sibling Death in the Family: Common and Consequential,” Demography 50, no. 3 (2013): 803–26; Livings et al., “Bereavement & Mental Health”; and Sarah E. Patterson, Ashton M. Verdery, and Jonathan Daw, “Linked Lives and Childhood Experience of Family Death on Educational Attainment,” Socius 6 (2020): 2378023120975594.
20. 20.  Rachel Margolis and Ashton M. Verdery, “A Cohort Perspective on the Demography of Grandparenthood: Past, Present, and Future Changes in Race and Sex Disparities in the United States,” Demography 56, no. 4 (2019): 1495–518; and Ashton M. Verdery and Rachel Margolis, “Projections of White and Black Older Adults Without Living Kin in the United States, 2015 to 2060,” Proceedings of the National Academy of Sciences 114, no. 42 (2017): 11109–14.
21. 21.  Jonathan Daw, Ashton M. Verdery, and Rachel Margolis, “Kin Count(s): Educational and Racial Differences in Extended Kinship in the United States,” Population and Development Review 42, no. 3 (2016): 491–517; and ; and Rachel Margolis and Ashton M. Verdery, “Older Adults Without Close Kin in the United States,” Journals of Gerontology Series B: Psychological Sciences and Social Sciences 72, no. 4 (2017): 688–93.
22. 22.  Ashton M. Verdery, Emily Smith-Greenaway, Rachel Margolis, and Jonathan Daw, “Tracking the Reach of COVID-19 Kin Loss with a Bereavement Multiplier Applied to the United States,” Proceedings of the National Academy of Sciences 117, no. 30 (2020): 17695–701.
23. 23.  Huy Anh Nguyen, Jake M. Hofman, and Daniel G. Goldstein, “Round Numbers Can Sharpen Cognition,” Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, 2022.
24. 24.  Rachel Kidman, Rachel Margolis, Emily Smith-Greenaway, and Ashton M. Verdery, “Estimates and Projections of COVID-19 and Parental Death in the US,” JAMA Pediatrics 175, no. 7 (2021): 745–46.
25. 25.  Mallika Snyder, Diego Alburez-Gutierrez, Iván Williams, and Emilio Zagheni, “Estimates from 31 Countries Show the Significant Impact of COVID-19 Excess Mortality on the Incidence of Family Bereavement,” Proceedings of the National Academy of Sciences 119, no. 26 (2022): e2202686119.
26. 26.  Margaret Stroebe, Robert O. Hansson, Wolfgang Stroebe, and Henk Schut, eds., Handbook of Bereavement Research: Consequences, Coping, and Care (American Psychological Association, 2001); and Stroebe et al., “Health Consequences of Bereavement.”
27. 27.  Haowei Wang, Ashton M. Verdery, Rachel Margolis, and Emily Smith-Greenaway, “Bereavement from COVID-19, Gender, and Reports of Depression among Older Adults in Europe,” Journals of Gerontology: Series B 77, no. 7 (2022): e142–e149.
28. 28.  Eric Klinenberg, Heat Wave: A Social Autopsy of Disaster in Chicago (University of Chicago Press, 2022).
29. 29.  Deborah Carr, Kathrin Boerner, and Sara Moorman, “Bereavement in the Time of Coronavirus: Unprecedented Challenges Demand Novel Interventions,” Journal of Aging & Social Policy 32, nos. 4–5 (2020): 425–31.
30. 30.  Wang et al., “Mourning in a Pandemic.”
31. 31.  Haowei Wang, Emily Smith-Greenaway, Shawn Bauldry, Rachel Margolis, and Ashton Verdery, “COVID-19 Widowhood or Pandemic Widowhood: Examining the Differential Implications for Mental Health,” Innovation in Aging 6, no. S1 (2022).
32. 32.  Umberson, “Black Deaths Matter.”
33. 33.  Jason Fletcher, Marian Vidal-Fernandez, and Barbara Wolfe, “Dynamic and Heterogeneous Effects of Sibling Death on Children’s Outcomes,” Proceedings of the National Academy of Sciences 115, no. 1 (2018): 115–20; and Patterson et al., “Linked Lives and Childhood Experience of Family Death on Educational Attainment.”
34. 34.  Benjamin Cornwell and Tianyao Qu, “‘Love You to Death’: Social Networks and the Widowhood Effect on Mortality,” Journal of Health and Social Behavior 65, no. 2 (2024): 273–91.
35. 35.  Snyder et al., “Estimates from 31 Countries Show the Significant Impact of COVID-19 Excess Mortality on the Incidence of Family Bereavement.”
36. 36.  Wang et al., “Mourning in a Pandemic.”
37. 37.  Meredith A. Claycomb, Ruby Charak, Julie Kaplow, Christopher M. Layne, Robert Pynoos, and Jon D. Elhai, “Persistent Complex Bereavement Disorder Symptom Domains Relate Differentially to PTSD and Depression: A Study of War-Exposed Bosnian Adolescents,” Journal of Abnormal Child Psychology 44, no. 7 (2016): 1361–73; Annemiek de Heus, Sophie M. C. Hengst, Simone M. de la Rie, A. A. A. Manik J. Djelantik, Paul A. Boelen, and Geert E. Smid, “Day Patient Treatment for Traumatic Grief: Preliminary Evaluation of a One-Year Treatment Programme for Patients with Multiple and Traumatic Losses,” European Journal of Psychotraumatology 8, no. 1 (2017): 1375335; and Cheryl Regehr, and Tamara Sussman, “Intersections Between Grief and Trauma: Toward an Empirically Based Model for Treating Traumatic Grief,” Brief Treatment and Crisis Intervention 4, no. 3 (2004): 289–309.