The impact of the coronavirus (COVID-19) pandemic on the retirement plans of households in the United States varied greatly across the generations considered. As of 2020, approximately one-quarter of the millennial surveyed (24 to 38 years of age) declared to have withdrawn from their emergency fund or savings account because of the coronavirus pandemic. On the other hand, this impact was reported by only *** percent of the respondents aged between 55 to 73 years (boomers).

When surveyed in **********, ** percent of Americans felt declined confidence in retiring comfortable, due to the coronavirus pandemic. When surveyed again in *************, a lower share, only ** percent, felt declined confidence to retire. Meanwhile, a higher share (** percent) felt increased confidence in **********. This share was lower in December that year, when only ** percent had improved confidence to retire comfortably.

Reasons for leaving work and those that have returned to work during the coronavirus (COVID-19) pandemic, broken down by retirement status. Includes information on whether those looking for paid work or have looked for paid work experienced age discrimination. Data from the Over 50s Lifestyle Study, Great Britain.

Most non-retired individuals worldwide wanted to save more towards their retirement after the outbreak of the coronavirus compared to what they planned before, as of 2021. Only around ********* of non-retirees wanted to save the same amount as planned before the pandemic.

In 2023, nearly *** in **** nurses said that they would retire from nursing due to the COVID-19 pandemic. According to this 2023 survey, ** percent of surveyed nurses stated they would likely retire from nursing as a consequence of the pandemic, of which ***** percent said it to be extremely likely. Nonetheless, most responding nurses stated it was unlikely for them to retire due to COVID-19.

Suppl. 1. Manuscript before English proofreading by ChatGPT. Suppl. 2. Manuscript after English proofreading by ChatGPT. Suppl. 3. Fifty-eight terms on digital standards of journal publishing (queried via ChatGPT) and the acceptability of its answers. Suppl. 4. Answer of ChatGPT (2023 Jan 9 ver.) to 58 topics on digital standards of journal publishing (cited January 19, 2023, 8:30 PM–January 21, 2023, 21:00 PM [Seoul time]).

IntroductionThis study examines the digital divide among older adults in Switzerland within the rapidly evolving digital environment. It investigates changes in internet usage among this population, focusing on the proportion of users, frequency, and the intensity of their internet usage during the COVID-19 pandemic.MethodsDrawing on Swiss data from the Survey of Health, Aging, and Retirement (SHARE), conducted in 2021, the study analyzes a sample of 1,205 older adults.ResultsThe findings indicate a growing proportion of internet users over time. It also highlights that gender differences persist but are decreasing. Notably, around 9% of individuals in this study had never used the internet, while recent users exhibited high activity levels, spending an average of approximately two and a half hours online daily. The study identified age, education, employment, living arrangements, and attitudes toward technology as influential factors shaping internet usage among older adults. Importantly, the COVID-19 pandemic did not have a significant impact on internet adoption among this demographic.DiscussionThese findings shed light on the complex dynamics that shape internet usage among older adults and underscore the need to promote digital inclusion and engagement within this population.

Main estimates from the Over 50s Lifestyle Study for Great Britain, wave 2: reasons for leaving and returning to work during the coronavirus (COVID-19) pandemic. Includes data covering future plans, caring responsibilities, savings and sources of retirement funding, cost of living and partner working status.

Most retired people would have retired the same age as they did, even if they would have known in advance about the outbreak of the coronavirus pandemic in 2020 and its impact on the world economy. The share was slightly lower among Asian retirees though, where one fifth stated they would have retired later if they would have known, and ** percent would have retired earlier.

Footnotes:1Gender refers to an individual's personal and social identity as a man, woman or non-binary person (a person who is not exclusively a man or a woman). Gender includes the following concepts: gender identity, which refers to the gender that a person feels internally and individually; gender expression, which refers to the way a person presents their gender, regardless of their gender identity, through body language, aesthetic choices or accessories (e.g., clothes, hairstyle and makeup), which may have traditionally been associated with a specific gender. A person's gender may differ from their sex at birth, and from what is indicated on their current identification or legal documents such as their birth certificate, passport or driver's licence. A person's gender may change over time. Some people may not identify with a specific gender.2Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses provided. In these cases, individuals in the category “non-binary persons” are distributed into the other two gender categories and are denoted by the “+” symbol.3Age' refers to the age of a person (or subject) of interest at last birthday (or relative to a specified, well-defined reference date).4This category includes women and girls, as well as some non-binary persons.5The median income of a specified group is the amount that divides the income distribution of that group into two halves, i.e., the incomes of half of the units in that group are below the median, while those of the other half are above the median. Median incomes of individuals are calculated for those with income (positive or negative).6Average income of a specified group is calculated by dividing the aggregate income of that group by the number of units in that group. Average incomes are calculated for those with income (positive or negative).7Total income refers to the sum of certain incomes (in cash and, in some circumstances, in kind) of the statistical unit during a specified reference period. The components used to calculate total income vary between: – Statistical units of social statistical programs such as persons, private households, census families and economic families; – Statistical units of business statistical programs such as enterprises, companies, establishments and locations; and – Statistical units of farm statistical programs such as farm operator and farm family. In the context of persons, total income refers to receipts from certain sources, before income taxes and deductions, during a specified reference period. In the context of census families, total income refers to receipts from certain sources of all of its family members, before income taxes and deductions, during a specified reference period. In the context of economic families, total income refers to receipts from certain sources of all of its family members, before income taxes and deductions, during a specified reference period. In the context of households, total income refers to receipts from certain sources of all household members, before income taxes and deductions, during a specified reference period. The monetary receipts included are those that tend to be of a regular and recurring nature. Receipts that are included as income are: * employment income from wages, salaries, tips, commissions and net income from self-employment (for both unincorporated farm and non-farm activities); * income from investment sources, such as dividends and interest on bonds, accounts, guaranteed investment certificates (GICs) and mutual funds; * income from employer and personal pension sources, such as private pensions and payments from annuities and registered retirement income funds (RRIFs); * other regular cash income, such as child support payments received, spousal support payments (alimony) received and scholarships; * income from government sources, such as social assistance, child benefits, Employment Insurance benefits, Old Age Security benefits, COVID-19 benefits and Canada Pension Plan and Québec Pension Plan benefits and disability income. Receipts excluded from this income definition are: * one-time receipts, such as lottery winnings, gambling winnings, cash inheritances, lump-sum insurance settlements and tax-free savings account (TFSA) or registered retirement savings plan (RRSP) withdrawals; * capital gains because they are not by their nature regular and recurring. It is further assumed that they are more relevant to the concept of wealth than the concept of income; * employers' contributions to registered pension plans, Canada Pension Plan, Québec Pension Plan and Employment Insurance; * voluntary inter-household transfers, imputed rent, goods and services produced for barter and goods produced for own consumption.8The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.9The sum of employment income (wages, salaries and commissions, net self-employment income from farm or non-farm unincorporated business and/or professional practice), investment income, private retirement income (retirement pensions, superannuation and annuities, including those from registered retirement savings plans [RRSPs] and registered retirement income funds [RRIFs]) and other money income from market sources during the reference period. It is equivalent to total income minus government transfers. It is also referred to as income before transfers and taxes.10The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.11All income received as wages, salaries and commissions from paid employment and net self-employment income from farm or non-farm unincorporated business and/or professional practice during the reference period.12The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.13Gross wages and salaries before deductions for such items as income taxes, pension plan contributions and employment insurance premiums during the reference period. While other employee remuneration such as security options benefits, board and lodging and other taxable allowances and benefits are included in this source, employer's contributions to pension plans and employment insurance plans are excluded. Other receipts included in this source are military pay and allowances, tips, commissions and cash bonuses associated with paid employment, benefits from wage-loss replacement plans or income-maintenance insurance plans, supplementary unemployment benefits from an employer or union, research grants, royalties from a work or invention with no associated expenses and all types of casual earnings during the reference period.14The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.15Net income (gross receipts minus cost of operation and capital cost allowance) received during the reference period from self-employment activities, either on own account or in partnership. In the case of partnerships, only the person's share of income is included. Net partnership income of a limited or non-active partner is excluded. It includes farming income, fishing income and income from unincorporated business or professional practice. Commission income for a self-employed commission salesperson and royalties from a work or invention with expenses associated are also included in this source.16The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.17All cash benefits received from federal, provincial, territorial or municipal governments during the reference period. It includes: * Old Age Security pension, Guaranteed Income Supplement, Allowance or Allowance for the Survivor; * retirement, disability and survivor benefits from Canada Pension Plan and Québec Pension Plan; * benefits from Employment Insurance and Québec parental insurance plan; * child benefits from federal and provincial programs; * social assistance benefits; * workers' compensation benefits; * Canada workers benefit (CWB); * Goods and services tax credit and harmonized sales tax credit; * other income from government sources. For the 2021 Census, this includes various benefits from new and existing federal, provincial and territorial government income programs intended to provide financial support to individuals affected by the COVID-19 pandemic and the public health measures implemented to minimize the spread of the virus.18The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars.19Refers to the sum of payments received from COVID-19 - Emergency and recovery benefits and Employment Insurance (EI) benefits.20The reference period for this variable is calendar year 2019. The variable is intended for comparison with its 2020 equivalent and other 2019 income variables. Income for 2019 is presented in 2020 constant dollars. In 2019, earning replacement benefits is equal to Employment Insurance (EI) benefits.21All Employment Insurance (EI) benefits received during the reference period, before income tax deductions. It includes benefits for unemployment, sickness, maternity, paternity, adoption, compassionate

Retirement is a pivotal life transition that often changes routines, identity, and objectives. With increasing life expectancies and evolving societal norms, examining the interplay between retirement anxiety and life satisfaction is vital. This study delves into this relationship, recognising the complexities of retirement. A systematic review and meta-analysis followed PRISMA guidelines. Research from 2003 to 2023 was sourced from databases like CINAHL, PubMed/Medline, PsycINFO, ERIC, and Google Scholar, focusing on diverse methodologies and outcomes related to retirement registered in Prospero database (CRD42023427949). The quality assessment used an eight-criterion risk of bias scale, and analyses included qualitative and quantitative approaches, such as random-effects meta-analysis and moderator analyses. After reviewing 19 studies with varied geographical and demographic scopes, a mixed relationship between retirement and life satisfaction emerged: 32% of studies reported a positive relationship, 47% were negative, and 21% found no significant correlation. Meta-analysis indicated high heterogeneity and non-significant mean effect size, suggesting no consistent impact of retirement on life satisfaction. Moderator analyses highlighted the influence of measurement tools on outcomes. The findings reveal a complex interplay between retirement anxiety and life satisfaction, stressing the need for holistic retirement policies that encompass mental health, social integration, and adaptability, focusing on cultural sensitivity. Challenges include potential biases in data sources, methodological diversity, the scarcity of longitudinal studies, and difficulties in addressing recent societal shifts, like the COVID-19 pandemic. Variability in measurement tools and possible publication bias may have also influenced results. This study contributes to understanding retirement, emphasising the relationship between retirement anxiety and life satisfaction. It advocates for ongoing, detailed, culturally informed research to grasp retirement’s multifaceted aspects fully.

The outbreak of the COVID-19 pandemic in early 2020 introduced new challenges to social cohesion across Europe. Epidemiological control measures instituted in almost all European countries have impacted the possibility to provide help to others. In addition, individual characteristics contributed to whether individuals were able and willing to provide help to or receive help from others. Against this background, we focus on how private support networks of individuals aged 50 years and older across Europe were directly or indirectly affected by the COVID-19 pandemic. The focus of the paper is on the supply side. While the older population has been mainly perceived as recipients of instrumental help in the COVID-19 pandemic, the paper examines the patterns of providing instrumental help to others by the older generations and their changes during the pandemic. Has the provision of instrumental help increased or decreased in the course of the COVID-19 crisis? Have the groups of recipients changed during the pandemic? What were key determinants for helping others in 2021 as compared to the first phase of the pandemic 1 year before? And how did this differ across countries with different degrees of affectedness by COVID-19? To answer these questions, we analyzed representative data from the Survey of Health, Aging and Retirement in Europe (SHARE) and, in particular, the two waves of the SHARE Corona Survey, fielded in 27 European countries and Israel in 2020 and 2021. Results based on data from more than 45,000 respondents aged 50+ showed that help from children to parents has strongly increased in the first phase of the pandemic, while the opposite (parents helping their children) has decreased–especially in countries that have been hit hardest by the pandemic in 2020. This changed with the continuing crisis. Instrumental help provided to non-kin that was common in Western Europe in the first phase of the pandemic, yielding an optimistic view of increasing solidarity after the outbreak of COVID-19, strongly decreased 1 year later. Our findings provide a contribution to comparative research on micro- and macro-determinants that are crucial for the understanding of intergenerational support in times of crisis.

Employment status and reasons for leaving and returning to work during the coronavirus (COVID-19) pandemic: future plans, caring responsibilities, savings and sources of retirement funding, cost of living and partner working status. Main estimates from the Over 50s Lifestyle Study for Great Britain, wave 2, 10 to 29 August 2022.

The outbreak of the coronavirus impacted the retirement savings in the United States during spring 2020. According to a survey conducted in May 2020, ** percent stated that they were saving less than before the outbreak. Meanwhile, ***** percent stated they were saving more than before.

ObjectivesLoneliness is a major public health concern. Duration of loneliness is associated with severity of health outcomes, and further research is needed to direct interventions and social policy. This study aimed to identify predictors of the onset vs. the maintenance of loneliness in older adults before and during the pandemic using longitudinal data from the Survey of Health, Age, and Retirement in Europe (SHARE).MethodsGroupings of persistent, situational, and no loneliness were based on self-reports from an ordinary pre-pandemic SHARE wave and a peri-pandemic telephone interview. Predictors were identified and compared in three hierarchical binary regression analyses, with independent variables added in blocks of geographic region, demographics, pre-pandemic social network, pre-pandemic health, pandemic-related individual, and country level variables.ResultsSelf-reported loneliness levels for the persistent, situational, and no loneliness groups were stable and distinct through 7 years preceding the pre-pandemic baseline measure. Shared predictors were chronic diseases, female sex, depression, and no cohabitant partner. Persistent loneliness was uniquely predicted by low network satisfaction (OR: 2.04), functional limitations (OR: 1.40), and a longer country-level isolation period for older adults (OR: 1.24).ConclusionInterventions may target persons with depression, functional limitations, chronic health issues, and no cohabitant partner. The added burden of the length of isolation on those who are already lonely should be taken into account when employing social policies that target older adults. Further research should distinguish between situational and persistent loneliness, and seek to identify predictors of chronic loneliness onset.

As of 09/24/24, this dataset is being retired and will no longer be updated.

*As of 1/1/2022 3 cases are required to be considered an outbreak, previously it was 2.

The number of COVID-19 outbreaks reported in Virginia by date VDH notified of the outbreak and by facility type group. This data set was first published on May 09, 2020. The data set increases in size daily and as a result, the dataset may take longer to update; however, it is expected to be available by 12:00 noon. When you download the data set, the dates will be sorted in ascending order, meaning that the earliest date will be at the top. To see data for the most recent date, please scroll down to the bottom of the data set. Starting on September 25, 2020, the Educational Setting Outbreaks will be divided into the following categories: Child care, K-12 and Colleges/ Universities.

Changelog:

Update September 20, 2021: Data and overview updated to reflect data used in the September 15 story Over Half of States Have Rolled Back Public Health Powers in Pandemic. It includes 303 state or local public health leaders who resigned, retired or were fired between April 1, 2020 and Sept. 12, 2021. Previous versions of this dataset reflected data used in the Dec. 2020 and April 2021 stories.

Overview

Across the U.S., state and local public health officials have found themselves at the center of a political storm as they combat the worst pandemic in a century. Amid a fractured federal response, the usually invisible army of workers charged with preventing the spread of infectious disease has become a public punching bag.

In the midst of the coronavirus pandemic, at least 303 state or local public health leaders in 41 states have resigned, retired or been fired since April 1, 2020, according to an ongoing investigation by The Associated Press and KHN.

According to experts, that is the largest exodus of public health leaders in American history.

Many left due to political blowback or pandemic pressure, as they became the target of groups that have coalesced around a common goal — fighting and even threatening officials over mask orders and well-established public health activities like quarantines and contact tracing. Some left to take higher profile positions, or due to health concerns. Others were fired for poor performance. Dozens retired. An untold number of lower level staffers have also left.

The result is a further erosion of the nation’s already fragile public health infrastructure, which KHN and the AP documented beginning in 2020 in the Underfunded and Under Threat project.

Findings

The AP and KHN found that:

• One in five Americans live in a community that has lost its local public health department leader during the pandemic
• Top public health officials in 28 states have left state-level departments ## Using this data To filter for data specific to your state, use this query

To get total numbers of exits by state, broken down by state and local departments, use this query

Methodology

KHN and AP counted how many state and local public health leaders have left their jobs between April 1, 2020 and Sept. 12, 2021.

The government tasks public health workers with improving the health of the general population, through their work to encourage healthy living and prevent infectious disease. To that end, public health officials do everything from inspecting water and food safety to testing the nation’s babies for metabolic diseases and contact tracing cases of syphilis.

Many parts of the country have a health officer and a health director/administrator by statute. The analysis counted both of those positions if they existed. For state-level departments, the count tracks people in the top and second-highest-ranking job.

The analysis includes exits of top department officials regardless of reason, because no matter the reason, each left a vacancy at the top of a health agency during the pandemic. Reasons for departures include political pressure, health concerns and poor performance. Others left to take higher profile positions or to retire. Some departments had multiple top officials exit over the course of the pandemic; each is included in the analysis.

Reporters compiled the exit list by reaching out to public health associations and experts in every state and interviewing hundreds of public health employees. They also received information from the National Association of City and County Health Officials, and combed news reports and records.

Public health departments can be found at multiple levels of government. Each state has a department that handles these tasks, but most states also have local departments that either operate under local or state control. The population served by each local health department is calculated using the U.S. Census Bureau 2019 Population Estimates based on each department’s jurisdiction.

KHN and the AP have worked since the spring on a series of stories documenting the funding, staffing and problems around public health. A previous data distribution detailed a decade's worth of cuts to state and local spending and staffing on public health. That data can be found here.

Attribution

Findings and the data should be cited as: "According to a KHN and Associated Press report."

Is Data Missing?

If you know of a public health official in your state or area who has left that position between April 1, 2020 and Sept. 12, 2021 and isn't currently in our dataset, please contact authors Anna Maria Barry-Jester annab@kff.org, Hannah Recht hrecht@kff.org, Michelle Smith mrsmith@ap.org and Lauren Weber laurenw@kff.org.

This study examines experiences of health and economic challenges during the COVID-19 pandemic across generations of American families and how families responded to these challenges. To do so requires knowledge of each family member's characteristics and the contexts they experienced over the pandemic. Accordingly, researchers are creating a unique dataset that enhances the rich population-representative panel data in the Health and Retirement Study (HRS) and the Panel Study of Income Dynamics (PSID) by linking comprehensive contextual data to multiple life domains of each generation. Research to date has investigated the health, economic, and wellbeing impacts of essential work on couples using employment, occupation, and industry data from PSID. For additional information and code, see Measuring Essential/Frontline Work Using PSID (ICPSR 199304). The ICPSR provides variable-level metadata for the data associated with this study. The actual data may only be available from the Principal Investigator directly. The variable descriptions available through ICPSR also include information regarding the source of each variable listed, as does the Data Source field of these metadata.

According to Cognitive Market Research, the global Retirement Home Services market is growing at a compound annual growth rate (CAGR) of 3.90% from 2023 to 2030. Rising Global Life Expectancy Is Driving The Growth of the Market

People are living longer lives than they were a few decades ago. This is due to low rates of cardiovascular and infectious disease mortality. The majority of deaths in the world were caused by three primary health conditions: ischemic heart disease, chronic obstructive pulmonary disease (COPD), and stroke.

Since the 1990s, the average number of fatalities has grown. The number of people dying from illnesses such as heart disease has increased as the world population has grown.

The decrease in age-specific mortality rates for various illnesses is evidence of the healthcare industry's success.Life expectancy increases as a result of breakthroughs in public healthcare facilities and significant developments in the healthcare business, as well as higher living standards, increased nutrition, better education, and lifestyle changes. An individual's global average age is mostly determined by living conditions and place of residence. These factors will boost market growth during the forecast period.

Technological Developments Will Boost Market Expansion

During the forecast period, technological advancements in long-term healthcare are anticipated to propel market expansion. This is brought on by the increase in Internet usage, which has sparked the development of online marketplaces, mobile apps, and mHealth. There is a rising need for support services including smartphone apps, trackers, wearables, communication tools, and smart alarms. These tools allow nurses and caregivers to monitor, document, and observe patients as well as connect with medical specialists.The use of computer and mobile phone-based patient data management among these technologies is spreading throughout long-term care.

Apps that create electronic health records (EHRs) and mobile health records (MHRs) are now available, making it simpler for consumers and healthcare professionals to access and exchange health information.

(Source:health-e.in/blog/phr-apps-india/)

The main technological advancements are mHealth and mobile-based healthcare applications that produce electronic health records (EHRs) and mobile health records (MHRs). When there are medical emergencies, other technologies, like alarm integration methods, are employed to notify service providers and caregivers. As they lessen the dependency on carers, smart houses are becoming more popular in industrialized nations. Thus, the market's expansion over the course of the forecast period will be fueled by the rising acceptance of such cutting-edge technical solutions.

The Aspects of the Retirement Home Services Market are Limitingits Growth

Negative Reputation Of Retirement Homes Is A Significant Barrier To Market Growth

Though living in the comfort of one's own home is always preferable, living in an old age home has its advantages. However, just a few old age facilities provide the bare minimum of quality for a comfortable stay. The cost of services supplied by old age homes is heavily influenced by the quality of those services. Many individuals enroll in retirement homes that lack basic infrastructure and services because they cannot afford the hefty service fees. Residents at nursing facilities are rarely given privacy. The environment in certain nursing facilities frequently results in despair, boredom, neglect, and, in some cases, abuse.

Impact of COVID-19 on The Retirement Home Services Market

Due to the risk of getting the virus in communal living arrangements, the pandemic has reduced demand for retirement homes. However, the epidemic has increased demand for retirement homes that provide specialized nursing care services. Retirement homes that provide specialized services for nursing care are growing more popular as individuals seek a safe and comfortable place to live. Introduction of Retirement Home Services

A retirement home is a multi-residence living complex designed for the elderly, sometimes known as an old people's home or old age home. Everyone or a couple resides in a room or suite of rooms that is akin to an apartment. There are more facilities in the building. This will include places for gathering, eating, playing, and receiving some kind of healt...

Interacting with family members and friends from other households is a key part of everyday life and is crucial to people’s mental well-being. The COVID-19 pandemic severely curtailed face-to-face contact between households, particularly for older adults (aged 60 and above), due to their high risk of developing severe illness if infected by COVID-19. In-person contact, where possible, was largely replaced by virtual interaction during the pandemic. This article examines how inter-household contact in face-to-face and virtual forms, as well as combinations of the two forms of contact, related to older adults’ mental well-being during the pandemic. Data from two national longitudinal surveys, collected from the same respondents before (2018–2019) and during (June 2020) the pandemic, were comparatively analysed: the Health and Retirement Study in the US and Understanding Society in the UK. The findings showed a notable increase in loneliness in the US and a decline in general mental well-being in the UK following the outbreak of COVID-19. In both countries, more frequent inter-household face-to-face contact during the pandemic was associated with better general mental well-being, but inter-household virtual contact, via means such as telephone and digital media, was not associated with general mental well-being in either the US or the UK. In the US, older adults who engaged more frequently in virtual contact were more likely to feel lonely during the pandemic, particularly if their face-to-face contact was limited. In both countries, the increase in loneliness following the outbreak of the pandemic was greater for older adults who reported more virtual contact. The findings suggest that household-centred crisis management during the COVID-19 pandemic had unintended mental health implications in both the US and the UK, despite contextual differences between the two countries. Although face-to-face contact between households helped to sustain older adults’ mental well-being, virtual contact was not a qualitatively equivalent alternative. The findings also provide an important evidence base for informing policy developments and for supporting the mental health of older people during the COVID-19 pandemic and in the longer term.