COVID-19: Regional Analysis and Impact on Care Services

The novel coronavirus disease 2019 (COVID-19) originated in Wuhan, China in December 2019 and has since rapidly spread worldwide. The World Health Organisation (WHO) declared the outbreak as a pandemic on 11 March 2020. Governments and health authorities worldwide are responding to the evolving pandemic in an effort to contain the outbreak and prevent overwhelming health services.

27 Mar 2020 | 8 min read

Individuals infected with COVID-19 may be asymptomatic or have flu-like symptoms including a fever, cough, shortness of breath, fatigue and muscle pain. The usual incubation period between infection and the display of symptoms is 1-14 days. Development of the disease may lead to more severe respiratory diseases such as pneumonia and acute respiratory distress syndrome, which can also result in sepsis and death.

Out of those infected, the elderly and immunocompromised are most vulnerable to more severe conditions brought about by the disease. The disease is more severe among elderly patients and among comorbid patients, particularly those with a history of respiratory illnesses.

Dr Foster have analysed available data relating to COVID-19.

The objectives are:

1.       To show the spread of the disease across England and the UK,

2.       To identify regions most at risk of developing severe cases of COVID-19,

3.       To identify trends and monitor the spread of the disease across the UK,

A detailed description of the analyses is provided in this commentary.

1. Spread of disease

The animation that corresponds to the image below shows how COVID-19 has spread across England (left) and London (right) over time.

It highlights that the disease is spreading rapidly, particularly in London, with the highest rates observed centrally and spreading outwards. Between 7 and 24 March 2020, Kensington and Chelsea are consistently found to have the highest rate of confirmed cases per 100,000 people residing in the area.

2. Vulnerable regions

This analysis identifies regions in the UK at Upper Tier Local Authority (UTLA) level most vulnerable in terms of developing more severe cases of COVID-19, which might place pressure on the local health services in the region. The vulnerability score of an area is based on:

The ‘risk’ of an area is based on:

  • The rate of elderly people populating the area[1]. A high density of an elderly population (60 years and over) would make the region more vulnerable.
  • The proportion of the population who have a history of admissions for respiratory conditions[2]. High proportions would make the region more vulnerable.
  • The proportion of the population who are frail. High proportions would make the region more vulnerable.

A heat map showing the vulnerability of regions is overlaid with the rate of confirmed COVID-19 cases[3]  per 100,000 people residing in an area. Monitoring the rate of COVID-19 cases in the more vulnerable regions could be vital to avoid overwhelming the hospitals in these regions and to avoid deaths.

People who are elderly, frail or have a history of respiratory diseases are more vulnerable, and if infected, would have a higher probability of an admission to hospital and likely have more severe symptoms.

Based on these vulnerability scores alongside the rate of cases, Torbay, Cumbria, Stockport and Tameside should be closely monitored – these areas have been identified as being in the top 30 most vulnerable regions and have higher than average rates of COVID-19 cases compared to the national average (as of 23 March 2020) (Figure 1).

Other vulnerable regions which should be closely monitored are Blackpool, Sefton, Wirral and Knowsley who have been identified in the top 5 most vulnerable regions.

Figure 1. Trends of COVID-19 case rates for vulnerable regions

The following maps visualise the above data.

Figure 2. Heat map showing an overlay of the rate of confirmed COVID-19 cases per 100K and the vulnerability of regions. The colour map shows the vulnerability score based on three factors: 1) the proportion of the population who are elderly (60+ years). 2) The proportion of the population who have been admitted for respiratory conditions in the past 10 years. 3) The proportion of the population who are frail. The score has been normalised to range from zero to 100. The circles indicate the rate of confirmed cases per 100K.

Figure 3. Heat map showing an overlay of the rate of confirmed COVID-19 cases per 100K and the proportion of the population previously admitted for respiratory conditions within the past 10 years broken down by UTLA. The colour map shows the proportion of patients with a history of respiratory conditions within the past ten years. The circles indicate the rate of confirmed cases per 100K. The view on the left is for England, the view on the right is for London only.

Figure 4. Heat maps showing an overlay of the rate of confirmed COVID-19 cases per 100K and the proportion of the population who are elderly (60+ years) by UTLA. The colour map shows the proportion of patients who are elderly (60+ years). The sizes of the circles indicate the rate of confirmed cases per 100K. The view on the left is for England, the view on the right is for London only.

Figure 5. Heat maps showing an overlay of the rate of confirmed COVID-19 cases per 100K and the proportion of the population who are frail by UTLA. The colour map shows the proportion of patients who are frail. The sizes of the circles indicate the rate of confirmed cases per 100K. The view on the left is for England, the view on the right is for London only.

Blackpool is identified as most vulnerable, having 26.45% of the population of the age of 60 years or above. The region has a comparatively high proportion of patients who have been admitted for respiratory conditions (14.86%) and a relatively high proportion of frail (4.79%). 

3. Trends and monitoring

The following dashboard presents trend curves of the rate of confirmed cases by UTLA alongside the national rate. To the left, the table shows the top 20 UTLAs having the highest rate of cases per 100K population based on the most recent data.

Specific up to 23 March:

The national rate shows an exponentially increasing trend. Out of all UTLAs in England, Kensington and Chelsea has the highest rate of confirmed cases, substantially more than the national average. The rate of confirmed COVID-19 cases per 100K population in Kensington and Chelsea is 54.42, which is 5.5 times the national average.

[1] Population statistics at UTLA level are sourced from the Facts and Dimensions dataset, with an effective snapshot of the population as at 2018-07-01. This is the latest release date as per the Office for National Statistics available here
[2] Data from HES, January 2010 – December 2019
[3] The number of confirmed cases within the UK by Upper Tier Local Authority (UTLA) is published daily by Public Health England available here data source includes patients who have recovered. Real numbers are actually higher because cases with unknown geographical information are excluded, as well as cases awaiting confirmation.