Location: United Kingdom
Socio-Economic Considerations of Spread of Covid-19 Through Local Communities
With the implementation of national lockdown, the issue of how and why Covid-19 cases occur more in some areas than others has been brought into greater focus.
As the pandemic progresses and more data is gathered, we can better understand the factors affecting the spread and the impacts on our communities and economies.
Two areas that have been extensively assessed for their correlation to Covid-19 are population density and deprivation data. The Office for National Statistics (ONS) has already determined that the virus has had a higher impact in the more deprived areas of the UK.
Figure 1 and Figure 2 show the correlation between densely populated local authorities and high concentrations of cases in the North of England. Three of the four most densely populated centres in the North West for example – Liverpool, Manchester and Salford – reached the highest level 7-day case rate in mid-October. The fourth of the most densely populated districts in the region, Blackpool, reached the highest level by the end of October.
The concentration of cases in East Lancashire, including Blackburn, Pendle and Burnley is notable, as population density here is lower. Mapping of the 2019 Index of Multiple Deprivation below shows that each of these districts are among the top 10% most deprived local authority areas in England.
As a comparison, Figures 3 and 4 show almost all the most deprived areas reached the highest case rate by the end of October.
This data indicates that population density and deprivation levels are important markers for high case rates. There are some exceptions however which are useful to consider, such as Ribble Valley in Lancashire. Ribble Valley is amongst the least deprived districts in the region and is also one of the least densely populated. This would indicate a low instance of Covid-19 case rates, yet it reached the highest tier for cases by 28th October. It is notable however, that Ribble Valley has a boundary with three districts in the most deprived 10% in the country and a further two among the 20% most deprived. Of these five districts, four have reached the highest level 7-day case rate for Covid-19. Ribble Valley is a key residential location for regional employment areas such as Blackburn and Preston. The high level of interaction between the populations of these districts ensures that cases can easily be transmitted into Ribble Valley. This shows how the pandemic can be spread into low density, low deprivation areas where there is a high level of movement across borders, particularly through commuting. All of Ribble Valley’s top five commuting destinations reached the highest case rates by mid-October[ii].
The data also indicates that high population density areas where deprivation is lower, experience lower case rates than high density areas where deprivation is high. This is in evidence in London and the South East where population density is high and deprivation levels lower. Across the two regions, 7-day average case rates had yet to reach the highest levels and had only reached the second highest (above 200 per 100,000) in three district/metropolitan areas in London and the South East by October 28th (see Figure 5).
By comparison, in the two regions of the North West and North East, the highest levels (400+ per 100,000) had been reached in 37 authority areas by the same date. As the data has shown in the north however, a high rate of movement between local borders can see cases spread from high rate areas to lower rate areas, even in relatively low deprivation or low density areas.
What is clear is that high deprivation, high density areas have been affected first. The reasons for this may relate to issues of poor health for example, which early research has shown to be a key risk factor.[iii] Also the prevalence of elementary or factory-based occupations where people work at close quarters or in enclosed spaces has similarly been considered a risk factor[iv].
The tables below show the proportion of jobs in districts with the 5 highest and 5 lowest case rates in the North West and South East respectively. This shows how districts with high case rates have a high proportion of elementary occupations[v] in their labour market, while districts with low cases have a low proportion of these occupations.
Implications for Planning
This analysis highlights the importance of assessing the overall health of our communities, both in economic and in community terms, when planning for new development. Covid-19 has also exposed the serious consequences of health inequalities[vi]. Health Impact Assessments can ensure developments contribute to the health of the community and also avoid negative health impacts. This has long been understood by public health experts and by Public Health England and has been the purpose of Health Impact Assessments when introduced and adopted by certain Planning Authorities some years ago.
However, coverage and consistency in Health Impact Assessments in planning has been an issue and Public Health England has recently stated its intention to improve this, especially in light of the Covid-19 pandemic[vii]. As such we can expect more local authorities to require Health Impact Assessments as part of their local planning requirements.
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[ii] Ribble Valley Top 5 outward commuting destinations 2011 Census; Blackburn with Darwen, Preston, Hyndburn, Burnley, Pendle. All 5 districts reached highest case rate by 20th October
[iii] The Health Foundation; Inequalities and Deaths Involving Covid-19, 21st May 2020, https://www.health.org.uk/news-and-comment/blogs/inequalities-and-deaths-involving-covid-19
[iv] The Health Foundation; Inequalities and Deaths Involving Covid-19, 21st May 2020, https://www.health.org.uk/news-and-comment/blogs/inequalities-and-deaths-involving-covid-19
[v] ONS Standard Occupational Classifications
[vi] The Health Foundation; Will Covid-19 be a watershed moment for health inequalities?, 7th May 2020, https://www.health.org.uk/publications/long-reads/will-covid-19-be-a-watershed-moment-for-health-inequalities
[vii] IEMA, Impact Assessment Outlook Journal, Volume 8: October 2020