Public Health England (PHE) issued its latest report on 2nd June 2020 “Disparities in the risk and outcomes of COVID-19”. This was widely expected to be a report on the impact of coronavirus on the Black, Asian and Minority Ethnic (BAME) community concluding with recommendations for action; this was not its objective.
It analysed the data from a number of dimensions ( e.g. age, sex, geography, ethnicity etc) and highlighted the complex interrelation between the results, and the shortcomings of the available data. PHE presented the data, objectively, to allow others to make interpretations and develop recommendations. This was not framed as a Government policy paper.
I have quoted key sections (in italics) from the report that describe the complexity of the data, its shortfalls and possible conclusions ( references are to the page number of the report)
The report analysed “disparities”
“The largest disparity found was by age. Among people already diagnosed with COVID-19, people who were 80 or older were seventy times more likely to die than those under 40. Risk of dying among those diagnosed with COVID-19 was also higher in males than females; higher in those living in the more deprived areas than those living in the least deprived; and higher in those in Black, Asian and Minority Ethnic (BAME) groups than in White ethnic groups.
These inequalities largely replicate existing inequalities in mortality rates in previous years, except for BAME groups, as mortality was previously higher in White ethnic groups.
These analyses take into account age, sex, deprivation, region and ethnicity, but they do not take into account the existence of comorbidities, which are strongly associated with the risk of death from COVID-19 and are likely to explain some of the differences.” (p4)
“When this data was analysed, the majority of testing had been offered to those in hospital with a medical need. Confirmed cases therefore represent the population of people with severe disease, rather than all of those who get infected.” (p4)
Age and sex:
“Working age males diagnosed with COVID-19 were twice as likely to die as females.” (p5)
“These disparities exist after taking ethnicity, deprivation and region into account, but they do not account for the effect of comorbidities or occupation, which may explain some of the differences.” (p5)
It may be that the underlying conditions (comorbities) more evident in men leave men more susceptible to the consequences of the virus. Similarly, occupations may be influential, especially in those jobs which are predominantly men and involve wider contact e.g. bus driver, taxi drivers, security guards which have seen higher rates of affection.
The conclusion isn’t that the virus targets men (because they are men, although this may be a factor) despite the much higher numbers, it is simply that other risk factors could conspire to skew the data
“Local authorities with the highest diagnoses and death rates are mostly urban. Death rates in London from COVID-19 were more than three times higher than in the region with the lowest rates, the South West. This level of inequality between regions is much greater than the inequalities in all cause mortality rates in previous years” (p5)
It is unsurprising that a virus that spreads quicker (R factor) when people are close to each other, is more prevalent in urban areas than in rural districts. The significance of this is that the inequality is more emphasised with Covid-19 than with historical mortality rates.
“People who live in deprived areas have higher diagnosis rates and death rates than those living in less deprived areas. The mortality rates from COVID-19 in the most deprived areas were more than double the least deprived areas, for both males and females” (p6)
“High diagnosis rates may be due to geographic proximity to infections or a high proportion of workers in occupations that are more likely to be exposed. Poor outcomes from COVID-19 infection in deprived areas remain after adjusting for age, sex, region and ethnicity, but the role of comorbidities requires further investigation“ (p6)
“Office of National Statistics reported that men working as security guards, taxi drivers and chauffeurs, bus and coach drivers, chefs, sales and retail assistants, lower skilled workers in construction and processing plants, and men and women working in social care had significantly high rates of death from COVID-19.” (p7)
Jobs which either brought people into close contact with the public, or where social distancing has not been practiced, results in more infection. These are jobs which, typically, are performed by men.
“Among deaths with COVID-19 mentioned on the death certificate, a higher percentage mentioned diabetes, hypertensive diseases, chronic kidney disease, chronic obstructive pulmonary disease and dementia than all cause death certificates.” (p7)
“Diabetes was mentioned on 21% of death certificates where COVID-19 was also mentioned… This proportion was higher in all BAME groups when compared to White ethnic groups and was 43% in the Asian group and 45% in the Black group. The same disparities were seen for hypertensive disease”. (p7)
“Several studies, although measuring the different outcomes from COVID-19, report an increased risk of adverse outcomes in obese or morbidly obese people.” (p8)
“Death rates from COVID-19 were highest among people of Black and Asian ethnic groups. This is the opposite of what is seen in previous years, when the mortality rates were lower in Asian and Black ethnic groups than White ethnic groups. Therefore, the disparity in COVID-19 mortality between ethnic groups is the opposite of that seen in previous years” (p6)
“An analysis of survival among confirmed COVID-19 cases and using more detailed ethnic groups, shows that after accounting for the effect of sex, age, deprivation and region, people of Bangladeshi ethnicity had around twice the risk of death than people of White British ethnicity. People of Chinese, Indian, Pakistani, Other Asian, Caribbean and Other Black ethnicity had between 10 and 50% higher risk of death when compared to White British.” (p6)
“These analyses did not account for the effect of occupation, comorbidities or obesity. These are important factors because they are associated with the risk of acquiring COVID-19, the risk of dying, or both. Other evidence has shown that when comorbidities are included, the difference in risk of death among hospitalised patients is greatly reduced.” (p6)
Later in the report it states;
“These analyses were not able to include the effect of occupation. This is an important shortcoming because occupation is associated with risk of being exposed to COVID-19 and we know some key occupations have a high proportion of workers from BAME groups”. (p39)
“These analyses were also not able to include the effect of comorbidities or obesity. These are also important factors because they are associated with the risk of death and are more commonly seen in some BAME groups. Other evidence has shown that when these are included, the difference in risk of death among hospitalised patients is greatly reduced” (p39)
The report is quite candid in its shortcomings and therefore the validity of the headline statistics. In a more focussed analysis but just for intensive care
“However, an analysis of over 10,000 patients with COVID-19 admitted to intensive care in UK hospitals suggests that, once age, sex, obesity and comorbidities are taken into account, there is no difference in the likelihood of being admitted to intensive care or of dying between ethnic groups” (p40).
The overall numbers used in the report were:
The total number of deaths up to 13th May was 28,246 (p83) ( note that this is significantly lower than reported elsewhere)
81% ( 22,880) were White – British [ 2011 Census – 87%]
14% (3,287) were Asian / Black [2011 Census – 10%]
5% (2,079) were White Other, mixed, or Other [ 2011 Census 3%]
The report looked at migrants ( people born in other countries)
“Being born outside of the UK does not necessarily mean a person is a vulnerable migrant, but migration is a factor that impacts on people’s health. In the UK resident population, there is some association between ethnicity and being born abroad.” (p54/55)
“The biggest relative increase was for people born in Central and Western Africa (4.5 times higher in 2020 than in 2014 to 2018). This group of countries includes Nigeria, Ghana and Somalia. For people born in four other groups of countries, deaths in 2020 were more than 3 times higher than the equivalent period in 2014 to 2018: the Caribbean (3.5), South East Asia, which includes Malaysia, the Philippines and Vietnam (3.4), the Middle East (3.2) and South and Eastern Africa, which includes South Africa, Zimbabwe and Kenya (3.1).” (p55)
“For people born in the European Union 2001, the relative increase was 1.8 times higher, and this was the only group of countries not significantly higher than the average for England” (p56)
The expectation that the report would uncover a fundamentally different insight was perhaps naive. It does further strengthen the basic understanding that there are 2 over-riding factors affecting risk.
- Proximity to the other people – the extent to which social distancing can be maintained
- Exacerbated by living in urban, deprived areas, and occupations that necessitate close contact
- Susceptibility to the consequences of Covid-19 – underlying health conditions
- Exacerbated by Age, specific conditions, obesity, being born abroad in certain regions.
There is no evidence that being a BAME person is a risk, in itself. The conclusion is that, socially, BAME people are more likely to live in urban areas, more likely to be in jobs that bring them into contact with other people, and exhibit health conditions that are more susceptible to the consequences of the virus.
Professor John Newton ( Epidemiologist and Public Health expert) at the Government Press meeting on 2nd June 2020 summarised
“Clearly outcomes are worse for people in Black and Minority ethnic groups and that is not necessarily because of their ethnicity – it may be related to their occupation or other reasons why there may be a high level of exposure. So one has to be a little bit careful in doing a risk assessment – one has to look at the causes of increased risk which may be as much to do with other factors and not necessarily someone’s background per se. Although there is probably an element of that as well.
The report emphasises the complexity of what we’re seeing so we are urging people not to jump to conclusions and institute measures which aren’t justified by the data. There is an element of caution in our results”
Categories: Corona virus