Ethnicity, household composition and COVID-19 mortality: a national linked data study.

OBJECTIVE: To estimate the proportion of ethnic inequalities explained by living in a multi-generational household. DESIGN: Causal mediation analysis. SETTING: Retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 30 November 2020). PARTICIPANTS: Adults aged 65 years or over living in private households in England from 2 March 2020 until 30 November 2020 (n=10,078,568). MAIN OUTCOME MEASURES: Hazard ratios were estimated for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographic factors, socioeconomic characteristics and pre-pandemic health. RESULTS: Living in a multi-generational household was associated with an increased risk of COVID-19 death. After adjusting for confounding factors, the hazard ratios for living in a multi-generational household with dependent children were 1.17 (95% confidence interval [CI] 1.06-1.30) and 1.21 (95% CI 1.06-1.38) for elderly men and women. The hazard ratios for living in a multi-generational household without dependent children were 1.07 (95% CI 1.01-1.13) for elderly men and 1.17 (95% CI 1.07-1.25) for elderly women. Living in a multi-generational household explained about 11% of the elevated risk of COVID-19 death among elderly women from South Asian background, but very little for South Asian men or people in other ethnic minority groups. CONCLUSION: Elderly adults living with younger people are at increased risk of COVID-19 mortality, and this is a contributing factor to the excess risk experienced by older South Asian women compared to White women. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent.

A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata.

BACKGROUND: There is a lack of research investigating the confluence of risk factors in urban slums that may make them accelerators for respiratory, droplet infections like COVID-19. Our working hypothesis was that, even within slums, an inverse relationship existed between living density and access to shared or private WASH facilities. METHODS: In an exploratory, secondary analysis of World Bank, cross-sectional microdata from slums in Bangladesh we investigated the relationship between intra-household population density (crowding) and access to private or shared water sources and toilet facilities. RESULTS: The analysis showed that most households were single-room dwellings (80.4%). Median crowding ranged from 0.55 m2 per person up to 67.7 m2 per person. The majority of the dwellings (83.3%), shared both toilet facilities and the source of water, and there was a significant positive relationship between crowding and the use of shared facilities. CONCLUSION: The findings highlight the practical constraints on implementing, in slums, the conventional COVID19 management approaches of social distancing, regular hand washing, and not sharing spaces. It has implications for the management of future respiratory epidemics.

How big is your bubble? Characteristics of self-isolating household units ('bubbles') during the COVID-19 Alert Level 4 period in New Zealand: a cross-sectional survey.

OBJECTIVE: To characterise the self-isolating household units (bubbles) during the COVID-19 Alert Level 4 lockdown in New Zealand. DESIGN, SETTING AND PARTICIPANTS: In this cross-sectional study, an online survey was distributed to a convenience sample via Facebook advertising and the Medical Research Institute of New Zealand's social media platforms and mailing list. Respondents were able to share a link to the survey via their own social media platforms and by email. Results were collected over 6 days during Alert Level 4 from respondents living in New Zealand, aged 16 years and over. MAIN OUTCOMES MEASURES: The primary outcome was the mean size of a self-isolating household unit or bubble. Secondary outcomes included the mean number of households in each bubble, the proportion of bubbles containing essential workers and/or vulnerable people, and the mean number of times the home was left each week. RESULTS: 14 876 surveys were included in the analysis. The mean (SD) bubble size was 3.58 (4.63) people, with mean (SD) number of households 1.26 (0.77). The proportion of bubbles containing one or more essential workers, or one or more vulnerable persons was 45.3% and 42.1%, respectively. The mean number of times individual bubble members left their home in the previous week was 12.9 (12.4). Bubbles that contained at least one vulnerable individual had fewer outings over the previous week compared with bubbles that did not contain a vulnerable person. The bubble sizes were similar by respondent ethnicity. CONCLUSION: In this New Zealand convenience sample, bubble sizes were small, mostly limited to one household, and a high proportion contained essential workers and/or vulnerable people. Understanding these characteristics from a country which achieved a low COVID-19 infection rate may help inform public health interventions during this and future pandemics.

COVID-19 And Racial/Ethnic Disparities In Health Risk, Employment, And Household Composition.

We used data from the Medical Expenditure Panel Survey to explore potential explanations for racial/ethnic disparities in coronavirus disease 2019 (COVID-19) hospitalizations and mortality. Black adults in every age group were more likely than White adults to have health risks associated with severe COVID-19 illness. However, Whites were older, on average, than Blacks. Thus, when all factors were considered, Whites tended to be at higher overall risk compared with Blacks, with Asians and Hispanics having much lower overall levels of risk compared with either Whites or Blacks. We explored additional explanations for COVID-19 disparities-namely, differences in job characteristics and how they interact with household composition. Blacks at high risk for severe illness were 1.6 times as likely as Whites to live in households containing health-sector workers. Among Hispanic adults at high risk for severe illness, 64.5 percent lived in households with at least one worker who was unable to work from home, versus 56.5 percent among Black adults and only 46.6 percent among White adults.