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COVID‐19 and Ethnic Inequalities in England and Wales

Abstract The economic and public health crisis created by the COVID‐19 pandemic is exposing existing inequalities between ethnic groups in England and Wales, as well as creating new ones. We draw on current mortality and case data, alongside pre‐crisis labour force data to investigate the relative vulnerability of different ethnic groups to adverse health and economic impacts. After accounting for differences in population structure and regional concentration, we show that most minority groups have suffered excess mortality compared to the white British majority group. Differences in underlying health conditions such as diabetes may play a role; so too may occupational exposure to the virus, given the very different labour market profiles of ethnic groups. Distinctive patterns of occupational concentration also highlight the vulnerability of some groups to the economic consequences of social distancing measures, with Bangladeshi and Pakistani men particularly likely to be employed in occupations directly affected by the UK's ‘lockdown’. We show that differences in household structures and inequalities in access to savings mean that a number of minority groups are also less likely to be able to weather short‐term shocks to their income. Documenting these immediate consequences of the crisis reveals the potential for inequalities to become entrenched in the longer term. This article is protected by copyright. All rights reserved


I. Introduction
There is a growing body of evidence that deaths from COVID-19 are not equally distributed across the population, with men, older people and those in more densely populated, and more deprived areas more severely affected (Williamson et al. 2020). Those with underlying health conditions, such as diabetes, heart disease, dementia and Alzheimer's are also more at risk if they contract the disease (ONS 2020d). The economic effects of the coronavirus crisis have also not been equally distributed, with those subject to loss of employment or reduced hours more likely to be young, female and low earners (Andrew et al. 2020; Joyce and Xu 2020).
While those in some occupations are able to work from home and others are deemed essential workers who may still go in to work, some sectors of the economy have been almost entirely shutdown.
In this paper we investigate the extent to which different ethnic groups are more or less affected by the immediate impact of the COVID-19 crisis, both in terms of exposure to infection and health risks, including mortality, and in relation to their exposure to economic impacts. Given well-documented ethnic inequalities in health (e.g. Karlsen and Nazroo 2011) and in the labour market (e.g. Longhi and Brynin 2017), we might expect to find unequal consequences of COVID-19 for ethnic minority groups. Yet, we would not necessarily expect these consequences to be similar across all groups. One of the defining characteristics of the ethnic minority population of the UK is its diversity (Modood et al. 1997). The UK's main ethnic groups differ in their demographic profiles, area of residence, migration history, educational attainment, labour market outcomes (including occupational concentration), household and family structure, savings and resources, and health (Platt 2019).
This renders it important to consider potential differential impacts on specific ethnic groups, taking into consideration the characteristics that put them more or less at risk. While the generally youthful profile of most minority groups might be expected to reduce mortality risk from COVID-19 in those populations as a whole, we explore whether this is the case and estimate disproportionality in deaths adjusted for age. We also take account of the geography of overall fatalities and the residence of each ethnic group. Beyond this, we focus in particular on occupational concentration in terms of both occupations that put some groups at greater risk of exposure to COVID-19 and those which place them more at risk of short-and This article is protected by copyright. All rights reserved.
long-term economic pressures. We also consider other relevant risk factors that differ across ethnic groups, including health conditions, family structure, savings levels and selfemployment. Being able to identify the potential role of such factors is crucial for developing informed policy responses and for providing meaningful insight into emerging COVIDrelated inequalities.
We concentrate on the six largest minority groups in England and Wales -white other, Indian, Pakistani, Bangladeshi, black African and black Caribbean -and compare their mortality and economic vulnerability with the White British majority. Our analysis focuses on a limited but crucial set of risk factors that are relevant to both infection risk and economic vulnerability in the short term. To understand the full extent to which different ethnic groups have fared relatively better or worse during this crisis will, however, require a longer term perspective, encompassing a more comprehensive understanding of infection, morbidity and mortality, as well as evaluating realised economic impacts and the extent of recovery.

II. Data
We draw on multiple sources of data. For the analysis of vulnerability to infection risks we use data published weekly by NHS England on registered hospital deaths as well as daily data on confirmed cases of COVID-19 infections from Public Health England and Public Health Wales. We combine this with data published weekly by the Office for National Statistics (ONS) on all deaths (including those in care homes and elsewhere in the community) in which COVID-19 was mentioned on the death certificate (see further ONS 2020a). Since these deaths cover England and Wales only, and given that the coding of ethnic group differs from that used in England and Wales in Scotland and Northern Ireland, we focus our analysis on England and Wales, which account for over 90 per cent of the UK's non-white minorities.
Information on the residential and demographic profile of each ethnic group comes from the ONS

III. Vulnerability to infection risks
Concerns that ethnic minority groups in the UK are being disproportionately harmed by the spread of COVID-19 were first triggered by findings from the Intensive Care National Audit and Research Centre (ICNARC 2020) indicating that the shares of critically ill patients from black, Asian and other ethnic groups were greater than their respective population shares.
Since then, data published by NHS England on registered hospital deaths by ethnic group have confirmed stark inequalities between ethnic groups, as shown in Figure 1. These data also show the importance of distinguishing between different ethnic groups, rather than considering all non-white groups as one, which can obscure significant and informative differences.

FIGURE 1
Total registered hospital deaths from COVID-19 per 100,000 in England by ethnic group This article is protected by copyright. All rights reserved.
The unequal effects of the COVID-19 crisis across ethnic groups are likely to be the result of a complex set of economic, social and health-related factors. Understanding the role of each of these will require a better understanding of the virus itself, more data than are currently available, and additional research. However, there are important differences between the characteristics of the UK's main ethnic groups -in terms of their geography, age, overall health, and occupational exposure -that are relevant for understanding why inequalities in vulnerability to infection may arise and for understanding the degree of disproportionality in health outcomes, including mortality. These include substantial differences between the country's main minority ethnic groups, and thus it is important not simply to contrast ethnic minorities as a whole with the white British majority, and not only to compare population shares of all minority or immigrant groups with shares of deaths.

People and Place
Compared with the white British majority, most minority ethnic groups are on average younger ( Figure 2). Around a quarter of the white British population in England and Wales are over 60 years of age, compared with 17% of the black Caribbean population, 12% of Indians, and just 6% of Pakistanis and 4% of black Africans. Given the striking concentration of COVID-19 deaths in older age brackets -with fewer than 10% of COVID-19 deaths in England and Wales occurring among those aged under 60 (as shown in the right-hand bar of Figure 2) -on their own, such age profiles would be expected to reduce the vulnerability of most minority ethnic groups to the virus relative to the older white British population.
However, there are also substantial differences in the age profiles of different minority groups. The black Caribbean ethnic group -which has suffered a notably high number of hospital deaths per capita -has a comparable age profile to the white British majority, whereas those of mixed ethnicity are overwhelmingly young, which may go a long way in explaining the comparatively few numbers of deaths in this category so far.

FIGURE 2
Age distributions of selected ethnic groups in England and Wales and share of overall COVID-19 deaths by age band COVID-19 cases have not been evenly distributed across the country. Therefore, the geographic distribution of ethnic groups is likely to be important in explaining between-group inequalities in COVID-19 exposure and health outcomes. The connectivity and population density of Britain's major urban centres have made people in these parts of the country particularly vulnerable to the spread of the virus, as shown in Figure 3. This was especially true in the early stages of the crisis: Birmingham, for instance, was a particular 'hotspot' for transmission, and London accounted for close to a third of confirmed cases in England by the end of March. Minority ethnic groups are disproportionately likely to reside in urban areas such as these, making them particularly likely to be exposed to the virus itself. In England and Wales, 60% of the overall black population and 50% of the Bangladeshi population live in London. This is in contrast to 8% of the white British majority, while 13% of the total Pakistani population live in the local authority of Birmingham.
A more complete mapping of the geographic distribution of ethnic group populations to where cases have been reported so far confirms that minority groups typically reside in parts of the country where more cases have been confirmed ( Figure 4) Two important factors -age and geography -appear, then, to push in opposite directions in terms of the vulnerability of most minority ethnic groups to infection from COVID-19. While the ethnicity of fatalities is not available in the ONS data, which include deaths outside of hospitals, comparisons of these projections with actual hospital deaths by ethnicity can provide an indication as to which ethnic groups are suffering the most excess fatalities. That is,the extent to which the number of recorded fatalities looks disproportionate for each group given their population size, age and sex distribution, and location. Because of aggregate differences arising from both coverage and reporting processes and periods, actual and predicted deaths are normalised against the white British group within each data set to facilitate comparisons. This article is protected by copyright. All rights reserved. Caribbeans, but lower rates for all other minority ethnic groups.

Note: Predictions based on demographics and geography are for COVID-19 fatalities in England and
In reality, the available information on hospital deaths by ethnic group suggests higher percapita mortality for all ethnic minorities in Figure 5 than can be explained by demographics and geography alone, as can be seen by comparing the third and fourth bars for each group.
The ratio of these two provides an estimate of excess mortality beyond what can be explained  Figure 5) the ratio is 0.5, suggesting disproportionately few fatalities in that population given their age profile and where they live.
However, it is likely that non-hospital deaths, for which a breakdown by ethnicity is not currently available, will have implications for overall inequalities in mortality. Such fatalities have accounted for an increasing proportion of total deaths as the crisis has unfolded, with the majority of non-hospital deaths occurring in care homes ( Figure 6). In total so far, care home deaths account for 28% of registered COVID-19 deaths, while deaths at home account for 5%.

FIGURE 6
Share of total registered COVID-19 deaths occurring outside of hospitals in England and Wales, by week This article is protected by copyright. All rights reserved.
In 2011, 94% of the care home population were white British, and 97% were in a white ethnic group overall. Thus, it is likely that compared with deaths occurring in hospitals, disproportionately more care home deaths will come from white ethnic groups. However, as shown in Figure 7, such deaths are currently not able to account for the disproportionalities in hospital deaths (given geography, age and sex) between minority ethnic groups compared with the white British majority. The graph shows the same predicted (based on geography and demographics) and actual hospital mortality results as in Figure  are reduced, the gap remains large for most ethnic minority groups. The ratio of actual to expected mortalities is reduced to 2.9 for black Africans, 1.8 for Pakistanis and 1.5 for black Caribbeans, for instance.

FIGURE 7
Accounting for care home deaths in relative mortality of ethnic groups This article is protected by copyright. All rights reserved. Understanding how other COVID-19 fatalities, including deaths at home, may vary across ethnic groups is challenging with the data that are currently available. However, the geographic distribution of deaths at home suggests they are disproportionately happening in areas with large populations of ethnic minorities (Figure 8). This may suggest that deaths at home will go in the other direction to deaths in care homes in terms of their effect on overall ethnic inequalities in COVID-19 deaths. It is not possible, however, to draw strong conclusions on the basis of this evidence, since it may be the case that a white British person is more likely than an ethnic minority person to die at home rather than in a hospital in a given area.  It is crucial to note that the ONS data suggest that, based on trends observed in previous years, there have also been a large number of additional 'excess deaths' in recent weeks that have not been officially attributed to COVID-19 but are likely to be the direct or indirect result of the virus. Such deaths equate to around 30% of the official total reported so far, and an increasing proportion are taking place in care homes. We do not have much detailed information about these deaths at this time -who is dying, and why and where exactly. The consequences of these for ethnic inequalities will become clearer over time.

Occupational risks
While geography and demographics clearly have a role to play, and can reconcile some differences across ethnic groups, fatalities from COVID-19 among many minority ethnic groups are clearly much higher than would be expected given their age, sex and location.
Other ongoing research has reached similar conclusions using either publicly available data on deaths (e.g. Aldridge et al. 2020) (as in this paper), or using individual data from hospital records (Williamson et al. 2020;Holman et al. 2020). There are, of course, a range of other factors that could be at play. The risk of transmission may vary for different individuals and groups within the same community, and the nature of people's jobs -or the occupation of those that they live with -is likely to be an important factor for their risk of infection. While This article is protected by copyright. All rights reserved.
workers' face continuing risks from contact with contagious individuals. While the current evidence does not allow us to unpick the relative importance of occupational risk and other correlated factors, the different labour market profiles of ethnic groups appear crucial to consider in terms of exposure to the virus. Figure 9 show the shares of working age populations across seven selected ethnic groups who are key workers, and among those, the shares who are health and care workers, since the latter may be particularly likely to risk contact with those infected with the virus. Some -but not all -minority ethnic groups may well face greater infection risks because of the types of work that they do. Pakistanis, black Africans and black Caribbeans are over-represented among key workers overall. This is particularly striking for the black African ethnic group, where almost a third of the working age population is employed in key worker roles and one in five in health and social care jobs specifically. This translates to a working age black African being 50% more likely to be a key worker than a white British working age person, and nearly three times as likely to be a health and social care worker.
For some groups who are highly concentrated in particular health care occupations it is possible to look in even more detail. For example, those of Indian ethnicity make up only 3.2% of the working age population, but over 14% of doctors. While 37% of the UK's doctors are foreign-born (despite the fact that only 18% of the working age population are foreign-born), nearly one in ten are from India. Black Africans, meanwhile, make up a smaller share (2.2%) of the working age population but account for 7% of nurses. Nurses accounted for the largest share of deaths among NHS staff in a recent analysis and a majority of them were from minority groups (Cook, Kursumovic and Lennane 2020).

FIGURE 9
Share of key workers among those of working age in each of seven ethnic groups This article is protected by copyright. All rights reserved.
Note: key workers are identified based on government guidance from 19 March using fourdigit SOC codes to identify key worker jobs in health and social care, education, public services, food, public order and transport. For further details, see Farquharson, Rasul and Sibieta (2020). Shares represent the proportion of the working age population (16-64) (excluding students) of each group that are in the identified occupations. Source: Quarterly Labour Force Survey, quarter 1 2016 to quarter 4 2019.
Given the mounting evidence that men are particularly vulnerable to the virus, it is also important to understand whether there are further differences when broken down by sex. Figure 10 reveals substantial differences between men and women in the prevalence of key workers. For all ethnic groups, women are much more likely to work in a key occupation, and particularly in healthcare roles. In terms of differential vulnerability to infection between ethnic groups, it is notable that compared to white British men, in many cases minority ethnic men are relatively more likely to work in key occupations (bottom panel of Figure 10).. This is not the case for minority group women. The higher relative chances of minority group men working in a key worker occupation are particularly marked for health and social care workers (top panel of Figure 10). For instance, Indian and black African men are 150% and 310% respectively more likely to work in health or social care than white British men,. In contrast, Indian women are 25% more likely and black African women 130% more likely than white British women to work in these roles. This implies the sex-adjusted occupational risk is likely to be higher for these minority groups.

FIGURE 10
Share of key workers in each of seven ethnic groups relative to white British, by sex

Men Women
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been reduced by the lockdown, those men with jobs in public facing roles such as sales and retail assistants, bus and coach drivers, also had higher mortality risks, as did chefs, who often operate in confined settings. These are all occupations in which minority groups are overrepresented. For example, black African men work in social care roles at seven times the rate of white British men, and black African women are four times as likely as their white British counterparts. Nearly six per cent of black African men of working age work as security guards, alongside three per cent of black Caribbean and Pakistani men, with minorities together accounting for forty per cent of all security guards despite making up less than a quarter of the working age population. Meanwhile, eight per cent of Bangladeshi men are chefs. Further analysis of occupation-specific death rates will therefore shed more light on the drivers of the overall gaps in mortality we observe. 5

Other relevant factors
Research from the ONS has shown a clear gradient in age-standardised mortality from

COVID-19 according to local deprivation, with the most deprived parts of England and
Wales suffering deaths at more than twice the rate of the least deprived areas (ONS 2020e).
Although the excess fatality estimates in this paper account for geography at the local authority level, deprivation can vary substantially within a local authority and is correlated with ethnic composition. However, further ONS research has considered ethnic differences in COVID-19 mortality up to April 10 th by linking death registrations with census records (ONS 2020f). This finds that neither local deprivation (as measured by decile of Index of Multiple Deprivation according to residence) nor proxies for socioeconomic status can explain much of the difference between ethnic groups.
Apart from infection risk at work, some ethnic groups may be more at risk of community transmission due to different family and household structures. South Asian ethnic groups are much more likely to live in larger households for instance, which all else equal will make transmission more likely. Taking London as an example, just under a third of households are single person, but among households where the household head is Bangladeshi, Indian and Pakistani, the figures are 11%, 17% and 13%, respectively. 5 Note that we cannot say whether it is the occupation per se that is driving the occupational disparities in COVID-19 deaths. It is possible that the over-representation of ethnic minorities in these jobs might be linked to the occupational death rates via other channels that increase minorities' risks of mortality.
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Related to this, compared to white British households, minority ethnic groups also tend to be more likely to live in overcrowded accommodation -even after controlling for region of the There are also notable inequalities in underlying health conditions and physical health that are likely to be crucial. Data on COVID-19 deaths in hospitals from NHS England have shown a striking concentration of fatalities in individuals with pre-existing health conditions.
As of 19 th May, 95% of all deaths had at least one attributable pre-existing health condition.
More than a quarter of fatalities have been suffered by individuals with diabetes, and the prevalence of kidney disease, dementia and respiratory and circulatory problems are also high.
Being overweight or obese has been identified as a potential risk factor, and 74% of England's adult black population is overweight or obese -11 percentage points more than the white British population and 18 percentage points more than the Asian population overall (Cabinet Office 2020). Black and south Asian ethnic groups have been found to have much higher rates of diabetes than the population as whole, and older Pakistani men have been found to have particularly high levels of cardiovascular disease (Health and Social Care Information Centre 2005). Figure 11 shows the proportion of individuals from different ethnic groups in each age band who report having a long-term, 'at-risk' health problem. Particularly in older age brackets, Indian, Pakistani, Bangladeshi and black Caribbean individuals are much more likely than white British people to report one or more of these health problems which are likely to increase their mortality risk from COVID-19. It may well be that underlying health This article is protected by copyright. All rights reserved.
conditions such as these can explain part of the disproportionality in hospital death figures across ethnic groups so far.
In sum, there is clear evidence for disproportionality in COVID-19 mortalities for a number of ethnic groups, after accounting for their age profiles and places of residence. While it is difficult to say definitively with the data that are currently available, the clustering of some minority groups in key worker occupations -and in care key worker roles in particularalongside greater susceptibility to relevant long-term conditions, are likely to be contributing factors to the observed disparities.
The consequences of COVID-19 on health will also find expression in the longer term through economic impacts (Jones, Davies and Drinkwater 2018). The next section considers which groups are more or less likely to have suffered from the recent lockdown.

FIGURE 11
Rates of long-term health conditions comprising risks for COVID-19, by ethnic group and age in England and Wales, relative to white British

IV. Economic vulnerability
In order to confront the public health crisis, the government has implemented unprecedented social distancing measures. This has created a unique type of economic crisis, the effects of which are likely to be experienced unequally as different sectors and household types are more or less exposed to the effects of the restrictions put in place. In this section, we consider how the economic characteristics of the main ethnic groups in England and Wales may result in different risks from the short-run effects of the current crisis. We focus on those of working age given they are potentially most at risk from the economic crisis. This covers larger shares of some groups than others given differing age profiles (Figure 2). In the medium-and long-term, additional unequal impacts are likely to arise through disruption to education, occupational and geographical mobility, and from policy responses to the crisis.
These are crucial to understand but are beyond the scope of this paper.

Family characteristics
As well as substantial differences in age profiles, the main ethnic groups also have very different characteristics in terms of household structure and labour market participation, both of which are important for understanding how changes in individual employment and earnings may affect overall between-group inequalities. Fewer Pakistani and Bangladeshi individuals are in paid work than other groups, largely owing to lower labour market participation amongst women. This might suggest that on aggregate these groups are less exposed to changes in economic circumstances resulting from the crisis; however, alongside black Africans and black Caribbeans, they are especially likely to reside in families where only one person is in paid work (Table 1), implying greater household-level exposure.  Caribbeans who are lone parents with dependent children is particularly high, and such groups may well be especially vulnerable to any loss of income due to absence of a withinhousehold buffer. In the context of disruption to schools and childcare facilities, even without loss of work, lone parent families may struggle to balance work and care. By contrast, couple families with dependent children with just one worker may be better placed to manage family arrangements and maintain employment (though this remains fraught with difficulties -see Andrew et al. 2020).

Employment in shutdown sectors
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Section 1 showed clear differences between ethnic groups in their likelihood of being employed in key worker roles -positions of heightened importance during this period. On the other side of the spectrum, the government-imposed lockdown has brought the majority of economic activity to a halt in sectors such as hospitality, leisure and transport. Joyce and Xu (2020) indicate that this lockdown directly affects 15% of employees but that the proportion varies significantly by age group, sex, and across the earnings distribution.
While differences in family structures imply that the effects of the crisis would vary across groups even if members of each ethnic group were equally likely to work in shutdown sectors, the chances of working in a directly affected industry are not evenly distributed. Figure 12 shows substantial differences in the share of each ethnic group working in shutdown sectors. The number of individuals working in these sectors is displayed as a percentage of the whole working age population of the group, rather than the share of those economically active or employed, in order to measure the effect on the group as a whole and to ensure estimates are not affected by differences in labour market participationparticularly among women.
While in the population as a whole women are more likely to work in sectors affected by the lockdown, this is driven by the white ethnic groups. In contrast, across many minority ethnic groups, men are more likely to work in shutdown sectors than women. This is particularly striking for the Bangladeshi and Pakistani groups, with men from the former four times as likely to work in shutdown sectors as white British men, due in large part to their concentration in the restaurant sector, and the latter nearly three times as likely, due in part to their concentration in taxi driving. Working age women from these two minority groups are no more likely to work in shutdown sectors than white British women. Black African and black Caribbean men are both 50% more likely than white British men to work in shutdown sectors.

FIGURE 12
Share of working age population in shut-down sectors in England and Wales, by ethnic group and sex This article is protected by copyright. All rights reserved. Many minority groups have younger age profiles than the white British group (see Figure 2), and younger workers are also more likely to work in shutdown sectors. Thus, Figure 13 shows the share of each ethnic group that works in a shutdown sector by age band. Within each age band, the between-group differences are indeed reduced, with few differences among those aged under 30. However, the greater share of Pakistani and Bangladeshi groups exposed to the lockdown is not driven by their age profiles. They disproportionately work in directly affected industries in older age brackets, with the rates increasing with age in contrast to the population overall. It is particularly striking that over half of Bangladeshis aged between 45 and 59 are employed in shut down sectors. This compares to just 12% of white British in the same age group.

FIGURE 13
Share of population in shut-down sectors in England and Wales, by ethnic group and age

Family circumstances of workers in shutdown sectors
Among those affected, the likelihood that they will be protected by the income of other household members varies. Joyce and Xu (2020) find that in general household incomes provide something of a buffer for those facing income losses due to working in shutdown industries. However, Table 1 shows that overall, Pakistanis, Bangladeshis, black Africans and black Caribbeans are less likely to be living in households with two or more earners.
Additionally, the extent to which children are impacted by parents' loss of work will vary by the extent to which affected workers are parents. Figure 14 shows family type by ethnic group of those in shutdown industries. While affected workers from all minority groups except black Caribbeans are more likely to be living as couples with dependent children than the white British group, black Africans and black Caribbeans are more likely to be living in lone parent families.

FIGURE 14
Family status of those employed in shut-down sectors in England and Wales, by ethnic group Focusing just on those living in couples, Figure 15 shows the employment status of partners This follows from the fact that Pakistani and Bangladeshis in shutdown sectors are more likely to be men, and women from these groups are less likely to be in paid employment. The combination of varied occupational exposure to the shut-down at different life stages and for men and women, combined with different rates of women's employment across groups means that, as Figure 16 shows, 29 per cent of Bangladeshi men both work in a shutdown sector and have a partner who is not in paid work and therefore is not able to provide an income buffer. This is the case for only one per cent of white British men.

FIGURE 16
Working in a shutdown sector and partner's economic status by ethnic group of shutdown sector worker, men only Moreover, even for those with partners in paid work there are substantial differences in average weekly earnings, as Figure 17 shows.

Partner earners as % of White British partner earnings (=100)
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Self-employment and income risks
The Coronavirus Job Retention Scheme (JRS) is intended to provide income support for many employed in shutdown sectors and in other sectors, reducing the potential income loss in the short-term at least. For self-employed individuals, the Self Employment Income Support Scheme (SEISS) provides generous support on average but applicants have faced a wait until June to receive funds and some of the self-employed will not be eligible, or will receive amounts much less than their recent earnings. Recent research has shown that those who are self-employed have been particularly severely affected by the crisis (Blundell and Machin 2020).
Among those of working age, as Figure 18 shows, Pakistani and Bangladeshi men are much more likely to be in self-employment than the overall population, meaning that these may be groups that are particularly hard hit at present. These are also among the groups who are less likely to have additional earners at home and among those more likely to have dependent children.

FIGURE 18
Share of working age in self-employment in England and Wales, by ethnic group and sex For many households, even short-term income shocks can present a serious challenge to their finances. Overall, 60% of working age individuals live in households with accessible savings sufficient to cover three months of income, but this varies substantially by ethnic group, as shown by Figure 20. Among working age Bangladeshi, black Caribbean and black African individuals, only around 30% live in households with enough saved in current accounts, savings accounts and ISAs to cover one month of household income, and around 10 per cent can cover three months of income. This latter figure is approximately a fifth of that of the Indian ethnic group, and a quarter of the white British majority. For some of those who are not supported by the JRS, who either face the five-week wait to access Universal Credit once successful applications have been made, or, if self-employed, have had to wait until June to access the SEISS, the lockdown in the UK is likely to be particularly economically challenging.

V. Conclusions
This paper paints a complex picture, with much still unknown about the unequal effects of the COVID-19 crisis on different ethnic groups in England and Wales in the short-term and in the future. Some minority groups have already been disproportionately exposed to risk of infection, and the ongoing sector shutdown also has implications for ethnic inequalities.
There is no single narrative that can describe or account for the impacts of the current crisis on all minority groups.
Overall, given demographic and geographic profiles, most minority ethnic groups are suffering excess hospital fatalities in England. Official non-hospital deaths can only account for a small part of the disparity compared to the white British majority so far. Age and location clearly play a role -and seem to explain important differences between different minority groups -but they do not tell the full story. Underlying health conditions, occupational exposure, and a range of other factors are likely to be important, with some more important for particular groups: Bangladeshi men have high rates of underlying health problems, and black Africans and Indian men are particularly exposed to the virus due to their prevalence in health and social care roles. The importance of each factor for each group will become clearer as more research is undertaken.
Ethnic groups also vary substantially in their economic vulnerability under the restrictions currently in place. White other and Indian ethnic groups face lower economic risks and are more comparable to white British in this regard. Bangladeshi and Pakistani groups, by contrast, appear to be particularly at risk due to the high percentage of either group working in shutdown sectors and/or in self-employment, combined with the prevalence of singleearner households which reduces the potential for income buffers within the household. The pervasiveness of key worker employment in other minority groups reduces their risk of income losses, while leaving them at a heightened risk of exposure to the virus itself. Both scenarios though are, in part, a consequence of the way the current labour market draws on both immigrant and ethnic minority workers to fulfil roles in care, transport and delivery sectors and in the more marginal hospitality and self-employed sectors.
Our findings draw attention to the ways in which minority and immigrant groups tend to be channelled into specific occupational niches, and the implications of that occupational segregation for individual and family vulnerability when a shock such as the current COVID-19 crisis arises. They beg the question of why and how such occupational structures are maintained, and the role of policy in mitigating the risks associated with critical but often marginalised or poorly valued roles.