Covid-19 and its effects on inequality

By George Carney, Lancaster Royal Grammar School


Carney, G. (2021) Covid-19 and its effects on inequality. Routes 2(1): 23-29


This essay explores how Covid-19 has affected inequality and looks at how inequalities play out at three different scales. Using an analytical approach and with the aid of various examples I conclude that Covid-19 is experienced differently across our societies and that, although Covid-19 may not have exacerbated inequality, it has certainly highlighted it. 

1. Introduction

Covid-19 is a disease, possibly originating from Wuhan, China, that has claimed the lives of 900,000 people worldwide and has infected almost 28 million as of the 6th September 2020 (John Hopkins University and Medicine, 2020). During the course of the pandemic there have been arguments to suggest that Coronavirus is an inequality virus – that the impacts of the disease are felt differently between ethnic groups, genders and social classes within our societies. It is clear that Covid-19 has highlighted inequality in our world and threatens to further widen the gap between rich and poor.  This essay reviews the literature concerning the impacts of the Coronavirus and comments on the different inequalities that have been exposed and exacerbated throughout the pandemic. Firstly, I will look at the impacts of Covid-19 on an international scale and discuss the argument that some countries have been affected more severely than others. Secondly, I will explain how the virus has affected the UK, both locally in North West England and nationally. Thirdly, I will argue that the BAME community in the UK has been more affected by Covid-19 compared to other ethnic groups. Finally, I will look at the differing effects that Coronavirus has on males and females and argue whether one gender has been affected more adversely.

2. International effects

Globally the coronavirus has changed the world completely. Low Income Countries (LICs), Newly Emerging Economies (NEEs) and High-Income Countries (HICs) have all been impacted differently by Covid-19. Countries that are more developed have been affected more severely than many LICs and NEEs. This is due to several reasons, firstly that many LICs have low connectivity to the virus’ origin, China.  As stated by Harvard University epidemiologist Megan Murray (2020) when talking to Voice of America, ‘Travel to sub-Saharan Africa, while it’s pretty brisk, it’s much less than travel between Europe the U.S. and China.’ There is also the argument, however, that the virus has not spread as easily in continents like Africa because of the climate. Researchers from the University of Maryland have found a correlation between climate and the spread of Covid-19 with ‘The virus [having] an easier time spreading in lower temperatures and humidity’ (Sajadi, 2020). Another reason for the difference in impacts is the population density and age of the population. In many LICs, although there are some megacities and highly densely populated areas, the majority of the population live rurally where social distancing is more a way of life. To add to this the age of the population in many developed countries is relatively old with 24% of people being over 60 in Europe for example (World Bank, 2019). In many developing countries, for example, across the continent of Africa, the population is relatively young with 60% of Africa’s population being under 25 years old. These younger people are more likely to survive than those who are older. However, in some countries like the US where health care is not free, there is a greater chance that young people will be severely affected by the virus as families struggle to afford health care and insurance. This is also seen in many LICs as many people/families live on low incomes.

3. Effects in the UK

In the North West of England we have seen the effects of Covid-19 very clearly as it has been one of the worst affected areas of the UK with deaths in Greater Manchester alone reaching 1,800 (Scheerhout, 2020). After the capital city of London, the North West has been the most affected area of the UK with low-income groups being worst affected. This is mainly due to the nature of most low-income jobs as many involve significant amounts of human contact e.g., taxi drivers. The death rate of male taxi drivers and chauffeurs from Covid-19 is 36.4 deaths per 100,000 (Office for National Statistics, 2020). This is significantly higher than the total death rate for males from coronavirus which stands at 9.9 deaths per 100,000 (Office for National Statistics, 2020). 

Another group worst affected is those with pre-existing health conditions as they were left shielding for weeks, many without work, during lockdown. Many people with severe health conditions usually work on low-income jobs and so struggled financially during lockdown and a large proportion were left unemployed and not receiving pay from the government’s furlough scheme. Those on higher income jobs in the region were not affected as much due to them being able to comfortably work from home on good salaries. This meant that they could significantly reduce their human contact without facing any negative impacts – this is not possible for those who work in low-income jobs. For example, the death rate for chartered and certified accounts was 19 per 100,000 and for architects it was 4 per 100,000 (Office for National Statistics, 2020).            

Researchers from the London School of Economics (2020) have calculated that those who were earning less than £151 per week in February 2020 were nearly three times more likely to be placed on furlough schemes or have hours cut compared to those who earned more than £600 per week (53.7 per cent compared to 18 per cent). 

On a national scale we saw that those living in more built-up areas and major cities were affected more than those living in rural areas. An exception to this was in places like the Lake District where many people travelled to self-isolate in their holiday homes. The reasons for this difference in rural and urban areas is again partly income based as many people living in urban areas work on lower incomes than those living in rural places. As mentioned previously lower income jobs usually involve increased human contact which puts them more at risk. Another possible reason for the difference is living arrangements, in urban areas conditions are usually more cramped with a large proportion living in large apartment/flat blocks. The common perception is that high population density leads to high infection rates. However, after analysing infection and death rates across the USA, researchers at the John Hopkins Bloomberg School of Public Health claim that ‘the infection rate is not linked with population density (2020), whereas the death rate is inversely related to population density (Hamidi et al. 2020) except for metropolitan areas where higher infection and death rates have been noted’. The main reason for the inverse relation between death rates and population density is due to the increased availability of healthcare systems in highly populated areas. 

3.1 Effects on the BAME community in the UK

It is clear that Covid-19 has affected everyone differently, with certain groups within our society being more adversely affected. During the pandemic we have seen that the number of positives tests in the BAME community has been proportionally higher than in other minor ethnic groups (Public Health England, 2020). In the 2011 census 7.9 million people identified themselves as being in a BAME group – this is equivalent to 14% of the UK population.  A review by McQuillan et al. (2020) identified ‘housing, occupational risk, and the low socioeconomic status as social and structural risks that could potentially impact BAME groups and lead to an increased risk of Covid-19 transmission, morbidity, and mortality.’ A survey by the national Royal College General Practitioners surveillance programme found that those of a black ethnicity had 4.75 times the odds of a positive Covid-19 test than those of a white ethnicity.  

The reason for this increased likelihood of a positive test is, in my opinion, twofold. Firstly, a report from the Public Health England (2020) found that 28% of BAME respondents classified themselves as key workers. It is clear that people who identify as being part of a BAME group are more likely to find themselves in a workplace with a significant amount of human contact. To add to this, they continued to work throughout the pandemic and thus were more likely to come into contact with the virus. Another possible reason is that many people in these groups find themselves living in overcrowded houses/flats. It has been stated that by 2016 48% of black households found themselves living in social housing (Barton, 2017). This contributes to the increased number of positive tests as it allows the virus to spread more easily. However, without sophisticated data and reports it is difficult to clearly state whether those in BAME groups are more likely to contract Covid-19. There are arguments that counter the points made above. One of these being that due to the high proportion of medical staff in the UK (Indians account for 14% of doctors and Black Africans make up 7% of the nursing workforce) being from BAME groups more people have been tested compared to those from other ethnic groups. As such, there has been an increased quantity of positive tests.

4. Gender effects

It is possible that Covid-19 has affected males and females differently. There is evidence to suggest that males are more likely to contract Covid-19 than women with ‘twice as many men dying from the virus as women’ in the US (Henriques, 2020). This is similar in Europe with 69% of coronavirus deaths in the west of the continent being male. One reason for this difference is biological. “The immune response throughout life to vaccines and infections is typically more aggressive and more effective in females compared to males,” (Goulder, 2020). Another possible reason for the contrast is the difference in lifestyle and behaviour of the sexes. For example, in China 50% of men smoke compared to the 5% of women (Henriques, 2020). Smoking can lead to chronic lung cancer and other health conditions which can make someone more likely die from the virus. Without extensive evidence and data, it is difficult identify which of these two elements is the major contributing factor or if they have equal weight. 

Covid-19 has not just affected people on a health scale but also on a financial one. Females have been worse affected by the pandemic financially. This is unusual as males are usually more affected as many of their jobs are tied closely with economic cycles. One reason for the contrast is that males are more likely to have jobs that are telecommutable – 28% of men work in telecommutable jobs compared to 22% of women (Tertilt et al., 2020). To add to this, Tertilt et al. (2020) also found that a larger proportion of men work in ‘critical worker’ roles and thus were more likely to keep working during the pandemic and have good job security after national lockdowns ended. To add to this, it is possible that women may have received greater cuts in nominal earnings ‘as a result of women’s weak labour market attributes as well as outright gender discrimination’ (Kristal and Yaish 2020).

The Coronavirus has highlighted the inequality between men and women and has clearly exposed the gender pay gap within our societies. When looking ahead we can see that the future is bleak and that ‘those still in work report a perceived likelihood of losing their job within the next few months of 32% in the UK’ (Adams et al., 2020). It is definite that there is a need for ‘immediate policy responses that target [certain] groups in the population that are most affected by this crisis’ (Adams et al., 2020). 

5. Conclusions

To judge whether the virus is an inequality virus is difficult as many countries in the developing world have not got access to testing equipment and so testing has been minimal compared to countries like the UK. Without this data it is difficult to come to a definitive conclusion.

Looking forward we will begin to see mass unemployment as government schemes (e.g. furlough schemes) come to an end and businesses struggle financially. Many of those that find themselves jobless will most likely have been working in low-income roles, again highlighting inequality. Those on higher income jobs, with better qualifications and education, will be more likely to keep their jobs. It is predicted by the World Bank (2020) that almost half of the world’s workforce will be left unemployed as economies try to rebuild. 

To conclude, as the pandemic continues to cause devasting impacts to our world it is beginning to highlight inequality and in certain areas affect some groups more than others. There is the risk that the gap between rich and poor will widen in the coming months as vaccines are introduced. Given all this information I believe that the coronavirus is an inequality virus to some extent as although it affects everyone, certain groups of people have been worse affected.

6. References

Adams A., Boneva T., Rauh C. & Golin M. (2020) ‘ Inequality in the impact of the coronavirus shock: Evidence from real time surveys’

Baragona, S.B. (2020) ‘Why COVID-19 Hit High-Income Countries Harder’, Voice of America [online]. Available at:

Barton C. (2017) ‘Home ownership and renting deomographics’ Research briefing, House of Commons. Availabe at:

Boyd, C.B. (2020) Interactive map of Covid-19 deaths in the UK [online] Available at: DOUBLE-London-June.html

Chapman, B.C. (2020) ‘Low-income workers three times more likely to have hours cut during pandemic then high-income workers’ The Independent. Available at:Low-income workers three times more likely to have hours cut during pandemic then high-income workers | The Independent | The Independent

Hamidi, S., Sabouri, S. and Ewing, R. (2020) ‘Does density aggravate the COVID-19 pandemic? Early findings and lessons for planners’. Journal of the American Planning Association86(4), pp.495-509.

Henriques M. (2020) ‘Why Covid-19 is different for men and women’. BBC Online Avaiable at: women

John Hopkins University (2020) Data showing global Covid-19 Deaths. Available at: COVID-19 Map – Johns Hopkins Coronavirus Resource Center (

Kristal, T. and Yaish, M. (2020). Does the coronavirus pandemic level the gender inequality curve?(It doesn’t). Research in Social Stratification and Mobility68, p.100520.

Office for National Statistics (2020) ‘Covid-19 deaths by job sector’ Available at:

Public Health England (2020) ‘Disparities in the risk and outcomes of Covid-19′ Available at: 

Scheerhout, J.S. (2020) ‘Leaked report ‘blames deprivation and poor housing for the spike in COVID-19 19 in parts of Greater Manchester’ Manchester Evening Post. Available at:

Soy, A.S. (2020) ‘Coronavirus in Africa: Five reasons why Covid-19 has been less deadly than elsewhere’ BBC News. Available at: Coronavirus in Africa: Five reasons why Covid-19 has been less deadly than elsewhere – BBC News

Tertilt M., Alon T., Doepke M., Olmstead-Rumsey J. (2020) ‘The impact of Covid-19 on gender equality’ National Bureau Of Economic Research. Available at: 

UK Government (2020) ‘COVID-19: understanding the impact on BAME communities’ Available at: COVID-19: understanding the impact on BAME communities – GOV.UK (

United Nations Development Programme (2020) ’ Coronavirus vs Inequality’ Available at: A (2020) ‘Coronavirus pandemic exacerbates inequalities for women, UN warns’. The Guardian pandemic-gender-inequalities-women  

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