Preliminary Results from the HRS COVID-19 Project
In response to the COVID-19 pandemic, the Health and Retirement Study (HRS) added new questions related to the impact of the pandemic on respondents' health and well-being. These questions were administered to a random half of the study's nationally representative sample of older Americans beginning in June 2020. Topics covered include respondents' level of concern about the virus; direct experience of the virus, including diagnostic testing; foregone or deferred health care; attitudes toward vaccines; economic effects, including effects on work, income, and spending; receipt of economic stimulus payments; care given/received; residential or household composition changes in response to the pandemic; and respondents' social contacts and psychological and emotional wellbeing. Additional COVID-related items from the 2020 HRS core data collection are forthcoming, including open-ended responses to a query about the pandemic's impact. Collection of these data is ongoing; an early release version of the data from 3,266 respondents is already available here. Preliminary analysis of the available data show that while very few respondents (about 2 percent) report that they or someone in their household has had COVID, 38 percent say they know someone who has had it and 17 percent know someone who has died. Close to 18 percent of the respondents had a doctor's visit delayed or canceled because of the pandemic; most of these visits were for managing an ongoing condition, a routine checkup, or screening. Respondents who had forgone a doctor's visit reported worse health and scored higher for depression. Concern about the virus is high overall and for subgroups defined by education or race/ethnicity. Among respondents who were still working (less than half), nearly a quarter stopped working entirely because of the pandemic, with much larger effects for respondents with lower levels of education. Income went down for almost one-fifth of respondents, including those with a college education or more. Spending changed as well, with highly educated respondents more likely to report spending went down rather than up and less-educated respondents more likely to report spending went up rather than down. About a quarter of respondents reported some kind of material hardship, including both economic hardships and having trouble buying food even though they had enough money. Economic hardships - the most common of which was not having enough money to buy food - were much more likely among respondents with low levels of education. These data, combined with the wealth of longitudinal data on HRS respondents' health and well-being, provide a rich resource for researchers interested in studying the pandemic's many impacts in a national sample of older Americans.
Many public health crises, including the COVID-19 pandemic share three features: (1) geo-spatial spread, (2) mismeasurement of prevalence, and (3) a coevolution of the condition and economic outcomes, so that a full accounting of the health impacts can only be assessed by accounting for economic impacts. This paper develops and estimates a model with these features. The estimates are then used to simulate trajectories of outcomes under a range of policy alternatives and trace out the health-economic possibilities frontier.
In most recessions, deaths due to motor vehicle accidents fall. In the COVID-19 recession, however, deaths due to motor vehicle accidents have increased slightly. This paper documents the difference between the COVID-19 recession and typical recessions and explores the reasons for this difference. Miles driven have fallen markedly in the COVID-19 recession; the major discrepancy from past recessions is that deaths per mile driven have increased. One hypothesis, which finds some support, is that because the roads are so clear, people are driving a lot faster. Thus, accidents that formerly did not involve death now are more likely to. Work on this question is ongoing.
Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes--and the role these connections serve in spreading a highly contagious respiratory infection--is currently unknown given the lack of centralized data on cross-facility employment. Chen, Chevalier, and Long perform the first large-scale analysis of nursing home connections via shared staff and contractors using devicelevel geolocation data from 50 million smartphones, and find that 5.1 percent of smartphone users who visit a nursing home for at least one hour also visit another facility during our 11-week study period--even after visitor restrictions were imposed. The researchers construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7 other facilities. Controlling for demographic and other factors, a home's staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Multivariate regressions comparing demographically and geographically similar nursing homes suggest that 49 percent of COVID cases among nursing home residents are attributable to staff movement between facilities.
This paper was distributed as Working Paper 27608, where an updated version may be available.
It's clear that the pandemic is disproportionately impacting communities of color. In this study, Grooms, Ortega, and Rubalcaba investigate mental health distress among essential workers during the Coronavirus pandemic across race and ethnicity. They evaluate individual responses to the Patient Health Questionnaire and General Anxiety Disorder Questionnaire using unique, nationally representative, data set. Their findings suggest that Black essential healthcare workers disproportionately report symptoms of anxiety; while, Latino essential health-care workers disproportionately report symptoms of depression. Additionally, Grooms, Ortega, and Rubalcaba find that being a Black or Latino essential non-health care worker is associated with higher levels of distress related to anxiety and depression. These findings highlight the additional dimensions to which Black and Hispanic Americans are disproportionately being affected by the Coronavirus pandemic. Furthermore, it calls into question how essential worker classifications, compounded by US unemployment policies, is potentially amplifying the mental health trauma experienced by workers.
The COVID-19 pandemic and its accompanying widespread public health interventions altered individual behaviors, including consumption of healthcare. Zhang studies utilization and mortality in the largest integrated healthcare system in the US, the Veterans Health Administration, and finds that between the middle of March and the beginning of May, emergency department and hospitalization visits declined by 37% and 46%, total veteran deaths increased by 15% over historic levels, yet non-COVID mortality at VA inpatient settings declined significantly. The researcher finds suggestive evidence that hospital avoidance may have resulted in higher mortality. Counties with higher hospital avoidance were associated with more deaths, even after controlling for COVID severity, public policies, and county characteristics. Extrapolating his estimate to the US population, roughly 9,500 Americans died from hospital avoidance by the end of
May, representing about 7.4% of total excess deaths. At the patient level, seniors, those with prior comorbidities, and veterans who live alone are more likely to avoid care and also die during the pandemic. Greater public efforts need to be directed at outreach and healthcare access, especially for the vulnerable.
The U.S. health care system has experienced great pressure since early March 2020 as it pivoted to providing necessary care for COVID-19 patients. But there are signs that non-COVID-19 care use declined during this time period. Ziedan, Simon, and Wing examine near real time data from a nationwide electronic healthcare records system that covers over 35 million patients to provide new evidence of how non-COVID-19 acute care and preventive/primary care have been affected during the epidemic. Using event study and difference-in-difference models we find that state closure policies (stay-athome or non-essential business closures) are associated with large declines in ambulatory visits, with effects differing by type of care. State closure policies reduced overall outpatient visits by about 15-16 percent within two weeks. Outpatient visits for health check-ups and well care experience very large declines during the epidemic, with substantial effects from state closure policies. In contrast, mental health outpatient visits declined less than other care, and appear less affected by state closure policies. Ziedan, Simon, and Wing find substitution to telehealth modalities may have played an important role in mitigating the decline in mental health care utilization. Aggregate trends in outpatient visits show a 40% decline after the first week of March 2020, only a portion of which is attributed to state policy. A rebound starts around mid April that does not appear to be explained by state reopening policy. Despite this rebound, care visits still remain below the pre-epidemic levels in most cases.
Levin, Hanage, Owusu, Cochran, and Walsh find a exponential relationship between age and IFR for COVID-19. The estimated age-specific IFR is very low for children and younger adults (e.g., 0.002% at age 10 and 0.01% at age 25) but increases progressively to 0.4% at age 55, 1.4% at age 65, 4.6% at age 75, and 15% at age 85. Moreover, their results indicate that about 90% of the variation in population IFR across geographical locations reflects differences in the age composition of the population and the extent to which relatively vulnerable age groups were exposed to the virus.
The COVID-19 pandemic in the US has been particularly devastating for nursing home residents. A key question is how have some nursing homes been able to effectively protect their residents, while others have not? Using data on the universe of US nursing homes, Cronin and Evans examine whether establishment quality is predictive of COVID-19 mortality. Higher-quality nursing homes, as measured by inspection ratings, have substantially lower COVID-19 mortality. Quality does not predict the ability to prevent any COVID-19 resident or staff cases, but higher-quality establishments prevent the spread of resident infections conditional on having one. Preventing COVID-19 cases and deaths may come at some cost, as high-quality homes have substantially higher non-COVID deaths, a result consistent with high excess non-COVID mortality among the elderly since March. The positive correlation between establishment quality and non-COVID mortality is driven entirely by nursing homes located in counties with below-median COVID-19 case rates. As a result, high-quality homes in these counties have significantly more total deaths than their low-quality counterparts. The concentration of excess death in low-risk areas suggests that future suffering could be avoided with more nuanced guidelines, such as those recently suggested by CMS that outline a role for in-person visits in lower-risk areas.
This paper was distributed as Working Paper 28012, where an updated version may be available.