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      Tracking the reach of COVID-19 kin loss with a bereavement multiplier applied to the United States


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          COVID-19 has created a mortality shock throughout the world, and it may yield a second wave of population health concerns tied to bereavement and social support reductions. We created the COVID-19 bereavement multiplier, an indicator that clarifies one downstream impact of COVID-19 mortality and can be applied to different epidemiological projections of death counts: How many people are at risk for losing a grandparent, parent, sibling, spouse, or child for each COVID-19 death. In the United States, we estimate that on average, under diverse epidemiological circumstances, every death from COVID-19 will leave approximately nine bereaved. Studying how acute mortality crises reverberate through a population in the form of bereavement multipliers expands understandings of the social impacts of health crises.


          The coronavirus disease 2019 (COVID-19) pandemic has led to a large increase in mortality in the United States and around the world, leaving many grieving the sudden loss of family members. We created an indicator—the COVID-19 bereavement multiplier—that estimates the average number of individuals who will experience the death of a close relative (defined as a grandparent, parent, sibling, spouse, or child) for each COVID-19 death. Using demographic microsimulation-based estimates of kinship networks in the United States, the clear age gradient in COVID-19 mortality seen across contexts, and several hypothetical infection prevalence scenarios, we estimate COVID-19 bereavement multipliers for White and Black individuals in the United States. Our analysis shows that for every COVID-19 death, approximately nine surviving Americans will lose a grandparent, parent, sibling, spouse, or child. These estimates imply, for example, that if 190,000 Americans die from COVID-19, as some models project, then ∼1.7 million will experience the death of a close relative. We demonstrate that our estimates of the bereavement multiplier are stable across epidemiological realities, including infection scenarios, total number of deaths, and the distribution of deaths, which means researchers can estimate the bereavement burden over the course of the epidemic in lockstep with rising death tolls. In addition, we provide estimates of bereavement multipliers by age group, types of kin loss, and race to illuminate prospective disparities. The bereavement multiplier is a useful indicator for tracking COVID-19’s multiplicative impact as it reverberates across American families and can be tailored to other causes of death.

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          Estimates of the severity of coronavirus disease 2019: a model-based analysis

          Summary Background In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases. Methods We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation. Findings Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9–19·2) and to hospital discharge to be 24·7 days (22·9–28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56–3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23–1·53), with substantially higher ratios in older age groups (0·32% [0·27–0·38] in those aged <60 years vs 6·4% [5·7–7·2] in those aged ≥60 years), up to 13·4% (11·2–15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4–3·5] in those aged <60 years [n=360] and 4·5% [1·8–11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39–1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0–7·6) in those aged 80 years or older. Interpretation These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death. Funding UK Medical Research Council.
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            COVID-19 and African Americans

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              Coronavirus Disease 2019 (COVID-19) in Italy


                Author and article information

                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                28 July 2020
                10 July 2020
                10 July 2020
                : 117
                : 30
                : 17695-17701
                [1] aDepartment of Sociology and Criminology, Pennsylvania State University , University Park, PA 16802;
                [2] bDepartment of Sociology, University of Southern California , Los Angeles, CA 90089;
                [3] cDepartment of Sociology, University of Western Ontario , London, ON N6A 5C2, Canada
                Author notes
                1To whom correspondence may be addressed. Email: amv5430@ 123456psu.edu .

                Edited by Douglas S. Massey, Princeton University, Princeton, NJ, and approved June 19, 2020 (received for review April 18, 2020)

                Author contributions: A.M.V. and E.S.-G. designed research; A.M.V. performed research; A.M.V. and J.D. analyzed data; and A.M.V., E.S.-G., R.M., and J.D. wrote the paper.

                Author information
                Copyright © 2020 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                Page count
                Pages: 7
                Funded by: HHS | NIH | National Institute on Aging (NIA) 100000049
                Award ID: 1R01AG060949
                Award Recipient : Ashton M Verdery Award Recipient : Rachel Margolis
                Funded by: HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) 100009633
                Award ID: P2C-HD041025
                Award Recipient : Ashton M Verdery Award Recipient : Jonathan Daw
                Funded by: University of Southern California Center for the Changing Family
                Award ID: 0000
                Award Recipient : Emily Smith-Greenaway
                Funded by: Gouvernement du Canada | Canadian Institutes of Health Research (CIHR) 501100000024
                Award ID: MYB-150262
                Award Recipient : Rachel Margolis
                Funded by: Gouvernement du Canada | Social Sciences and Humanities Research Council of Canada (SSHRC) 501100000155
                Award ID: 435-2017-0618
                Award Recipient : Rachel Margolis
                Funded by: Gouvernement du Canada | Social Sciences and Humanities Research Council of Canada (SSHRC) 501100000155
                Award ID: 890-2016-9000
                Award Recipient : Rachel Margolis
                Social Sciences
                Social Sciences

                covid-19,demography,mortality,bereavement,social support
                covid-19, demography, mortality, bereavement, social support


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