Inequalities and COVID-19
COVID19 (the disease caused by the SARS-CoV-2 virus) has become ubiquitous, affecting nearly all nations and regions and dominating global interest since the start of 2020.
In the very early stages, there was a large amount of press attention (In the UK at least) surrounding celebrities who had tested positive, including members of the Royal family and Boris Johnson, the Prime Minister of the United Kingdom, who became ill enough to be admitted to an Intensive Care Unit.
This apparently prompted some in Government and beyond to state that the disease was ‘a great leveller’ affecting rich and poor alike. There was, rightly, a large backlash against this idea and, whilst perhaps inconvenient for some political outlooks, early evidence suggests that the impacts of COVID19 are not equally distributed within populations.
This should not be surprising to us. Inequalities in health have been observed through time, in multiple contexts and pathologies. We know that socioeconomic factors influence health and behaviours and it follows that the underlying mechanisms behind this will be replicated today. Some of the key risk/prognostic factors in COVID19 identified from data thus far, such as High BMI, diabetes and other pre-existing conditions, are socially patterned, with higher prevalence in more deprived areas/groups. Occupations which are classed as higher risk, due to higher likelihood of exposure, are predominantly those which are considered to be in a lower social class. Indeed, many of the ‘key workers’ identified as important to the continued running of society under heavy restrictions are low-paid and low-status.
Racial/Ethnic considerations are also hugely important. Systematic and structural discrimination of these groups results in a higher representation in disadvantaged areas and socioeconomic classifications. Analysis in the US, UK and other parts of Europe has shown that areas with higher proportions of BAME or indigenous populations are those which have been worst affected by COVID19 mortality.
Death registration figures from the Office for National Statistics confirm that a Deprivation gradient exists. They found mortality rates in the most deprived areas are over twice those in the least deprived areas. Similarly, the Intensive Care National Audit & Research Centre found disease severity in COVID patients also conforms to this gradient.
However, it is not just the disease which highlights the importance of pre-existing inequalities. The restriction or lockdown measures, implemented around the world to slow the rate of transmission of the virus, have a disproportionate effect on the most deprived groups. Low paid workers in the service industry were under pressure to continue working with minimal protections (putting themselves at increased risk), or face losing their jobs before lockdown measures were officially enforced in the UK. Those in insecure employment, with zero-hours contracts, or in the ‘gig economy’ have little to no security net, whilst higher paid/valued occupations are more able to adapt to working from home. These factors will only play a greater role in the medium to long term recovery, as efforts inevitably pivot towards economic recovery.
To best mitigate the effects of COVID19 and policy responses, I echo calls that we urgently need to prioritise an equity approach and begin to adopt more widespread measurement of socioeconomic factors. In the early period of this pandemic, urgency may have led to the prioritisation of simple demographic information collection, thought to be more clinically relevant, but we can do better.
Acknowledgement of the importance of socioeconomic factors and collection of pertinent information will help us to understand the mechanisms which unfairly heap misery on the most vulnerable in our society. We can begin to better identify at-risk populations and formulate policy responses which mitigate the impacts more fairly.