Figures from the LCP Covid-19 Tracker show a strong but variable association between deprivation levels and Covid-19 infections, providing crucial information for those planning the next stages of our response to the pandemic.

The Covid-19 pandemic has affected us all, but its impacts have been far from equal. One of the key determinants of how severely places have been affected by Covid-19 is the level of deprivation.

More deprived areas – places with worse housing, fewer employment opportunities and higher crime rates – have significantly higher mortality rates than less deprived areas, and Covid-19 has added to the burden. Death rates from Covid-19 in the first wave were approximately twice as high in the most deprived areas compared with the least deprived. This same group were seven times more likely to work in a sector that was shut down during the first wave, while those whose sectors were not shut down were much less likely to be able to work from home as their least deprived counterparts.

After the national lockdown ends, a regional or local approach to restrictions will most likely be adopted. It will be important to manage restrictions carefully and identify which areas and populations face the greatest threat from the virus, to help direct funds, rebuild communities and avoid putting further strain on the NHS.

A data-driven approach

The LCP Covid-19 Tracker creates a comprehensive picture of the scale of Covid-19 infections across England at the Lower Tier Local Authority (LTLA) level by combining data from Public Health England (PHE) and the Office for National Statistics (ONS) and applying actuarial techniques. Lower Tier Local Authorities (District, Borough or City Councils, LTLAs) are the smallest geographical areas that we have these datasets for, with 315 in England. A full description of our methods can be found here.

For this analysis, we also incorporated data from the Index of Multiple Deprivation (IMD) which is a composite measure of the relative deprivation of local areas within the UK, taking into account factors such as income, education, health, crime and housing. The Government publishes IMD scores by Lower Layer Super Output Area (LSOA) which is at postcode level with around 35,000 LSOAs across the country. A higher score corresponds to a higher level of deprivation. We generated IMD estimates for each LTLA by taking a population-weighted average of the IMD scores of the LSOAs within each LTLA.

We integrated IMD scores with the LCP Covid-19 Tracker to estimate the cumulative Covid-19 infection rates across LTLAs in England from July to December 2020 according to deprivation status.

Associations between cumulative Covid-19 cases and deprivation

Regional variations

We found large variations in cumulative Covid-19 infection rates across regions in England for the second half of 2020. The North-West had the highest estimated cumulative infection levels at 8.4% of the population, equating to 8,417 per 100,000 over this period, followed by London at 7.6% (7,608 per 100,000). This was more than twice the rate in the South-West, where just 3.1% were estimated to have been infected, equating to 3,113 per 100,000 (Table 1, Figure 1). We found deprivation to be associated with higher rates of cumulative Covid-19 infection rates across all nine English regions, but there were large variations, with the association being strongest in Yorkshire and the Humber and weakest in the East of England.

More deprived LTLAs associated with higher cumulative Covid-19 infections

We found a strong correlation between deprivation at LTLA level and cumulative Covid-19 infections during the second wave (July-December 2020).

Our estimates for July-December 2020 suggest that cumulative infection rates were almost double (96% higher) in the most deprived 10% of local authorities compared with the least deprived 10%. In the most deprived 10% of LTLAs, an average of 8.7% of the population were infected with Covid-19 during this period, compared with just 4.4% in the least deprived areas (Table 2).

The inequalities in cumulative Covid-19 infections were even starker at individual LTLA level, with a more than nine-fold difference between those areas with the highest and lowest cumulative infection rates. We estimate that 13.7% and 12.9% of the populations of Blackburn with Darwen and Burnley were infected, compared with just 1.5% in Torridge and South Hams.

When taken together, the ten most deprived LTLAs had a population weighted average of approximately 8,900 cumulative Covid-19 infections over the last six months of 2020 (Table 6) compared with around half that rate (4,500 cumulative Covid-19 infections) across the ten least deprived LTLAs (Table 7).

Density matters

We found that 7.4% of people in areas with a population density greater than 1,000 people per square kilometre were infected with Covid-19 in the last six months of 2020, compared with only 4.6% in more sparsely populated areas. Cumulative infection rates in the 10% most densely populations LTLAs were more than those in the least densely populated (Table 5).

Living in an urban area was associated with much higher cumulative Covid-19 infection rates. Our findings suggest that, in the more sparsely populated northern parts of the country, the worst infection rates were concentrated in hotspots such as Merseyside and Greater Manchester, while infection levels were spread more evenly in the more densely populated, more interconnected South (Table 8-9).

Informing efforts to level up health

Deprived and urban areas had higher cumulative Covid-19 infection rates from July to December 2020, findings that add to the body of evidence confirming that the pandemic has been felt unequally across England. These inequalities should inform future measures with regards to vaccination roll out, additional resource for local contact tracing efforts, and support to the health and care system.

As the Government looks to build back better following the worst of the pandemic, addressing the structural health inequalities laid bare by Covid-19 must be a priority.

You can view full tables and figures by clicking here.