A GeoFactsheet Review written by Philip Lendorff on the effect of Covid-19 on the UK.

As of the 1st of June 2020, the UK has the second highest number of deaths from the coronavirus pandemic in the world. Following the USA with over one hundred thousand deaths, the United Kingdom has had over 38,000 casualties making it (as of yet)the ’worst hit’ country in Europe. With new data and statistics being revealed by the day it is hard to precisely analyse the figures. However, patterns are emerging with the continuous research. This geo factsheet looks at the distribution of the Covid-19 pandemic and the causes thereof, within the UK.

Therefore, in order to analyse the distribution of the virus in the UK, it would be more representative of reality to study the mortality rates in various locations across the UK, seeing as almost all deaths in the UK are accounted for.

Figure 1 shows the broad spread of virus deaths within the earlier weeks of the outbreak. Despite the data being obtained during a time when less was known about the virus and a smaller amount of deaths had happened, it is evident that the virus is more prevalent in urban areas. For example, the only areas with over 100 deaths per 100,000 people at this time are found in England’s largest cities: Manchester, Birmingham and London.

This general trend can be explained by the increase of transmissibility of the virus as its environment becomes more urban. Urban areas tend to be much more crowded. The virus is a respiratory disease transmitted from person-person proximity making crowded streets and public transport a hotspot for its spread. However, more recent maps show a more unsystematic and random set of data.

Figure 2 shows the number of the virus deaths to correlate less with how urban the area is. This map is showing the number of deaths per 100,000. However, if the graph were showing total deaths, it would look rather different, once again depicting the highest numbers to be in the most urban areas. To exemplify this, the darkest area in figure 2 is South Lakeland which has the highest deaths per 100,000 (121.9/100,000). However, areas in London such as Newham which has a lesser 82.7 deaths per 100,000 has a total coronavirus death toll of over twice that of South Lakeland. This is due to the fact that Newham is one of the most densely populated districts in England with 9,723 people per km².Nevertheless, one would not expect an area such as South Lakeland to be so badly hit. However, South Lakeland has an old population in comparison to the rest of the UK, with 30% of its population being over 65 rather than the UK’s 18%.

The severity of one’s response to the coronavirus has various causes, many of which are unknown. A suppressed or weakened immune system however is one of the main contributing factors. Many countries have experienced over 80% of their Covid-19 related deaths to be over 65 year olds (88% in the UK). Therefore, it can be concluded that old age is a crucial reason as to why more rural areas from which young people tend to migrate leaving an old demographic, such as South Lakeland have very high Covid-19 deaths per 100,000, However, as seen from in figure 2 there are many areas with equally high proportions of elderly people that have been less affected. For example, 33% of North Norfolk’s population is over the age of 65 and yet they have one of the lowest mortality rates in the UK at 37.3 deaths per 100,000. This shows that old age is not the only factor with others such as deprivation and attitude. In this case, North Norfolk’s rural nature and distance from major cities might have an impact (Lakeland has close links to Manchester).

We have established old age as being one of leading causes for high Covid-19 mortality rates, but some of the highest rates are still found in certain London districts. For example, the borough of Harrow has 148.3 deaths per 100,000. This is higher than South Lakeland, yet only 16% of its population is over 65. Increased transmissibility in denser populations is likely a factor that differentiates South Lakeland and Harrow. However, it does not explain the distribution of virus deaths across London.

Once we analyse a city itself in more detail the difference in population density is not significant enough to have a distinctive effect on the mortality rates. To show this, Kensington and Chelsea has a density of 12,884 people per km² and Newham has a density of 9,723 people per km². Their mortality rates are 75.5 and 148.3 respectively. This shows that there must be other much more discerning factors:•Level of deprivation•Ethnic diversity•Level of inequality To begin with, there is a big difference between levels of deprivation between Harrow and Kensington and Chelsea. The average salary in Harrow is less than half that of Kensington and Chelsea (£40,300 and £94,400 respectively). The difference in salary is characteristic of inequality between the two boroughs. Much research into levels of deprivation and Covid-19 mortality rates has shown that in the most deprived areas in England the mortality rate is roughly twice as high as less deprived areas. Those living in poorer areas are more likely to work unstable and lower paying jobs many of which are seen of as essential during the quarantine period. This means that these people are more likely to become infected as they have an increased exposure to the virus. Moreover, poorer families are more likely to be living in more crowded conditions where the risk of transmission is much higher.

Furthermore, ethnicity has been proven to be a deciding factor for many deaths due to the coronavirus. This can be primarily linked to various social factors previously mentioned. People from BAME (black, asian and minority ethnic) backgrounds are overrepresented in the proportion of England’s population on lower incomes. As a result ethnic minorities are more likely to live in more deprived conditions. For example, 30% of Bangladeshi people in the UK are living in overcrowded conditions compared to the 2% of white people. They are also overrepresented in the service industry, of which many jobs are deemed ‘key’ during the quarantine. For example, 25% of TFL’s workers come from a BAME background.

Figure 4 shows that the borough of Kensington and Chelsea is predominantly white, with only 21% of its population being ethnic minorities. Conversely, Harrow is a much more diverse borough with 63.8% of its population being members of the BME communities (Black and Minority Ethnic). Extensive studies have shown that black people are twice as likely to die from Covid-19 as white people. Bangladeshi, Pakistani and Indian (who make up the majority of Harrow’s population) are 1.8 times as likely to die from the virus.

This can be predominantly attributed to the before mentioned social factors which cause people of BAME backgrounds to be more likely to be exposed to the virus. However, out of the total Covid-19 fatalities of medical staff working throughout the pandemic, 63% have been BAME, showing how perhaps BAME people are at higher risk of a life threatening Covid-19 infection as a result of other factors.

It is still unclear as to why ethnic minorities are at a higher risk of death; however, possible explanations include a increased pre-existing susceptibility to diseases such as diabetes, heart disease, liver and kidney disease which have been proven to worsen the effects of the coronavirus. Moreover, as mentioned previously, a weakened or suppressed immune system is strongly linked to the severity of one’s reaction to the virus. Vitamin D has been shown to boost one’s immune response. Ethnic minorities due to higher melanin levels, absorb less vitamin D from the sun compared to white people which could be a potential factor in more life threatening virus symptoms, although little research is has yet been done.

In conclusion, it is evident that there is no one single factor that one can be used to explain the distribution of Covid-19 deaths across the UK. In a time where data and statistics, both inaccurate and accurate, are being released continuously, it is difficult to assess them effectively. Nonetheless, correlations can be formed. One can see that many factors are responsible for the mortality rates of coronavirus across the UK, such as age, population density and poverty. However, many aspects of the pandemic are yet to be studied in depth and consequently many questions remain unanswered.

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(Featured Image: © Simon Dawson)