The number of publicly reported deaths from coronavirus disease 2019 (COVID-19) may underestimate the pandemic's death toll. Such estimates rely on provisional data that are often incomplete and may omit undocumented deaths from COVID-19. Moreover, restrictions imposed by the pandemic (eg, stay-at-home orders) could claim lives indirectly through delayed care for acute emergencies, exacerbations of chronic diseases, and psychological distress (eg, drug overdoses). This study estimated excess deaths in the early weeks of the pandemic and the relative contribution of COVID-19 and other causes. Methods | Weekly death data for the 50 US states and the District of Columbia were obtained from the National Center for Health Statistics for January through April 2020 and the preceding 6 years (2014-2019). 1,2 US totals excluded Connecticut and North Carolina because of missing data. The analysis included total deaths and deaths from COVID-19, influenza/pneumonia, heart disease, diabetes, and 10 other grouped causes (Supplement). Mortality rates for causes other than COVID-19 were available only for underlying causes. Death data with any mention of COVID-19 on the death certificate (as an underlying or contributing cause) were used to capture all deaths attributed to the virus. Population counts for calculating mortality rates were obtained from the US Census Bureau. 3,4 Observed deaths for the 8 weeks between March 1, 2020, and April 25, 2020, were taken from provisional data released on June 10, 2020. 2 Expected deaths (and 95% CIs) for these same weeks were estimated by fitting a hierarchical Poisson regression model to the weekly death counts for the period of
Confirmatory factor analyses were conducted of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) symptoms of common mental disorders derived from structured interviews of a representative sample of 4,049 twin children and adolescents and their adult caretakers. A dimensional model based on the assignment of symptoms to syndromes in DSM-IV fit better than alternative models, but some dimensions were highly correlated. Modest sex and age differences in factor loadings and correlations were found that suggest that the dimensions of psychopathology are stable across sex and age, but slightly more differentiated at older ages and in males. The dimensions of symptoms were found to be hierarchically organized within higher-order "externalizing" and "internalizing" dimensions, which accounted for much of their variance. Major depression and generalized anxiety disorder were substantially correlated with both the "externalizing" dimension and the "internalizing" dimension, however, suggesting the need to reconceptualize the nature of these higher-order dimensions.
The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer:The analyses described are the responsibility of the authors and do not necessarily reflect the views or policies of the US Department of Health and Human Services. The mention of trade names, commercial products, or organizations does not imply endorsement by the US government.
This Viewpoint uses CDC data to compare the COVID-19 mortality rate in 2020 with prior leading causes of death (heart disease, cancer, lung disease, and injury) to put into context the cost of the infection in loss of life in the United States.
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