Suffolk's CoronaWatch is the home of data and information produced under the Suffolk Joint Strategic Needs Assessment (JSNA). 

Please note: there are continual updates and improvement to the national COVID-19 data page. Occasionally, this will affect the timeliness of the data dashboard and other CoronaWatch products. We are updating when data is available.  The date that the data is refreshed is always available within the CoronaWatch dashboard. 

This page will be frequently updated as we are able to analyse and publish more information. 

Unfortunately, we are unable to respond to individual requests for COVID-19 data at the moment. This is due to exceptionally large volume of requests we are receiving.  However, we will log and monitor all queries, and aim to answer them within our FAQs section as soon as we possibly can. You can submit a query via the Knowledge and Intelligence Team: 

June 2021

National information

  • UK level data was released on the 17 July 2020 detailing deaths involving COVID-19, England and Wales: deaths occurring in June 2020. This data found:
    • COVID-19 was the third most frequent underlying cause of death in June 2020 (after Dementia and Alzheimer disease and Ischaemic heart diseases), with 7.1% of all deaths (2,525 deaths) due to COVID-19; this was a large decrease compared with the proportion seen in May, when COVID-19 was the most frequent underlying cause of death and accounted for 21.6% of all deaths.
    • Dementia and Alzheimer disease was the most common main pre-existing condition found among deaths involving COVID-19 and was involved in 12,869 deaths (25.6% of all deaths involving COVID-19) in March to June 2020.
    • The rate of deaths from all causes in June 2020 was 742.0 deaths per 100,000 persons in England and 837.5 deaths per 100,000 persons in Wales; both mortality rates were significantly lower than the five-year average (860.5 for England and 924.0 for Wales), though small increases in rates are expected over time as more deaths that occurred in June are registered.
    • Of all the deaths due to COVID-19 that occurred between March and June in England, 63.9% (28,390 deaths) happened in hospital. Most of the COVID-19 deaths in hospital were in people aged 65 years and over (86.1%). Care homes were the second most common place of COVID-19 deaths, with 30.2% of all deaths due to COVID-19 (13, 417 deaths) in England occurring in care homes. Almost all (98.9%) of the COVID-19 deaths in care homes were of people aged 65 years and over.

Cases in Suffolk care homes

All care home residents have been tested for COVID monthly, and all care home staff have been tested weekly, for some time. This testing has been effective in identifying cases where the person has no visible symptoms, known as being ‘asymptomatic’. When people are asymptomatic they can still spread the virus, so it has been very important to find these cases and support the workers and care home residents to self-isolate, limiting the further spread of disease.

Care home testing policy has developed, and now if any staff member or resident of any home tests positive for COVID-19, all the staff and all the residents in that home are immediately tested. It is really important that these tests are done, so that the home can be supported with their infection prevention and control practice, and with any other issues such as access to PPE, to try and prevent further spread of the virus.


Current data indicates that as of June 2021, there have been 401 reported outbreaks across complex settings since March 2020, 268 of these in care homes. As of 3 June 2021 there have been 4 outbreaks in Suffolk during the previous 30 days, of which 0 were in care homes.

As part of gaining access to local testing arrangements in Suffolk, a very robust process was set up requiring homes to report suspected outbreaks to both Suffolk County Council and PHE simultaneously.

Previous data produced by Public Health England (PHE) on outbreaks by setting provided cumulative reporting on care home outbreaks.  However, this reporting has now ceased.

It may also be useful to note that in Suffolk, the care home sector generally has fewer providers with larger numbers of beds per home. In neighbouring counties, there are higher numbers of smaller homes.  This means that data for Suffolk can appear comparatively high when only the percentage of homes with outbreaks is compared, even though actual cases, rates and outbreak numbers across different areas may be similar.  Suffolk County Council have been working on developing an integrated response and to deliver “wrap around” support to care settings as required, and have been working in tandem with the care home sector.

Care home deaths

Despite care homes in Suffolk continuing to care for their residents with the utmost kindness and professionalism, data indicates that during the first ‘wave’ of the pandemic in Suffolk, a higher rate of COVID-19 related deaths within care homes in Suffolk compared to some other areas. The reasons for this are complex, but factors which we think are contributing to this include:

  • More people choosing to, and then being supported to, die in their usual place of residence
  • The earlier and more extensive COVID-19 testing which took place in Suffolk compared to some areas, which enabled earlier, more accurate attribution of subsequent deaths to COVID-19.

The latest data indicates the rate of deaths from COVID-19 in care homes is very low.  

In Suffolk there are very good practices for providing end of life care. Dying within a care home setting is often reflective of a person’s wish to remain in their usual place of residence, in comfortable surroundings with people around them who are familiar, as opposed to being within a hospital setting. To help inform our understanding of this issue, which is complex and multi-factorial, SCC are currently working with CCG and primary care colleagues to audit GP records. These records relate to care home residents who have died from COVID-19, to determine whether they had end of life care plans (known locally as “yellow folders”) recording their wishes at the end of life, and whether those wishes were met. A summary of findings from this audit is provided below.

Care homes audit 2020

Approximately 5,500 people live in care homes in Suffolk, across around 200 residential and nursing homes. Care home residents are potentially frail and often suffer from two or more long-term conditions at the same time, placing them at greater risk of diseases including COVID-19. They are also the recipients of advance care planning (ACP), which aims to reduce distress to patients with life-limiting and incurable conditions by putting in place “do not attempt cardiopulmonary resuscitation” orders (DNACPRs). Patients with ACPs in place often die in their usual place of residence (DiUPR) rather than being transferred to unfamiliar and frightening environments (e.g. hospitals) and being subjected to potentially distressing and invasive investigations at the end of life.

We identified individuals with ACPs using routinely-collected general practice (GP) data and death registration data. 47 of 51 Suffolk GP practices approached during this study responded; 61 residents across 29 care homes were included in the final analysis. 46 of 61 COVID-related care home deaths in this study (75%) had a DNACPR order in place at the time of death, and individuals with higher frailty scores tended to have a DNACPR order in place. This may suggest that residents were having their treatment approach adapted to suit their individual needs. 56 individuals were identified in both datasets based on provided information. Of these, 36 (64%) died in their usual residence, 19 (34%) in hospital, and 1 in hospice. This suggests that end-of-life planning may have played a part in the increased care home deaths observed in Suffolk county for some individuals. However, this study was relatively small, and repeating this with wider coverage (including Waveney CCG and GP systems using other software) might be helpful.

Overall, this study identified a high proportion of DNACPRs and DiUPR in the Suffolk care home population who died from COVID-19 between March and June 2020. More frail individuals comprised a higher proportion of DNACPRs, in keeping with end-of-life planning.

Discharging from hospital

  • Since March 2020, the whole health care system in Suffolk has worked together more closely than ever before in response to the challenges presented by coronavirus.
  • One of its actions was to secure additional bed capacity at local care homes. The aim is to enable the discharge of all hospital patients who are medically fit to leave, leaving staff to focus on treating those patients who really need to be there.
  •  An extra 182 beds in care homes were made available for use, which is an increase of just under 9% of the beds that the council commissions. This has greatly strengthened the ability to cope with the extra demand. Fortunately, although demand has increased it has not been overwhelming, meaning not all the extra beds have been needed.
  • As part of these beds, we have commissioned some specialist care provision for people who need admission to a care home but cannot be admitted. These step-down beds will be used where care homes cannot take in a person who is COVID-19 positive, but these individuals still need care and a period of isolation.  60 beds in three locations across Suffolk have been commissioned.


  • You can find data about deaths in care homes via the data dashboard.
  • You may also find the Local Government Association (LGA) report on care home deaths useful. A range of geographies and comparators can be chosen. 
  • When comparing data, it can also be helpful to compare to local authorities that are statistically similar to us: CIPFA nearest neighbours. Compared to CIPFA statistical neighbours, Suffolk is in the lower half of authorities in relation to the percentage of COVID-19 deaths in care homes for the year to date. 

On 12 August, a new UK-wide methodology to record COVID-19 deaths was announced and the deaths data reported on the Government's Coronavirus (COVID-19) in the UK website changed as a result. This may affect reported figures and ability to compare areas or change over time. Suffolk CoronaWatch uses deaths data reported from the ONS, so the figures our local website are not affected by this change.

Local data dashboard 

View the data dashboard for Suffolk.

This includes data on: 

  • Confirmed cases of coronavirus (COVID-19)
  • Deaths from coronavirus 
  • Care home outbreaks 
  • Google social mobility data 

The data is refreshed on a daily basis. 

We would like to extend our thanks to Norfolk County Council for kindly sharing their dashboard so we could recreate this locally. If you are interested in viewing the Norfolk dashboard, you can find this on the Norfolk Insight website.  

National data dashboard information 

These links are nationally published dashboards that contain local information, and may be of use: 


Can you tell me what households in my street have coronavirus?

  • We are continuing to monitor data on a daily basis.
  • Internally, we have access to household level data, that helps us to monitor cases, and enables early detection of potential increases in cases of coronavirus. This data is sensitive, and we cannot share it on the website.
  • We can share information at district and borough level through the CoronaWatch Dashboard, and there is also mapping on the website.
  • The links above are the most detailed publicly available data we can provide at this time.

Can you tell me if a specific care home has reported a coronavirus outbreak, or how many deaths there have been?

  • Internally, we have access to individual care home data, that helps us to monitor cases, and enables early detection of potential increases in cases of coronavirus. This data is sensitive, and we cannot share it on the website.

What is the lowest geography I can get coronavirus case information at?

  • The website has a publicly available COVID-19 map that looks at neighbourhood level data on positive cases diagnosed in the last week (7 day rolling average).    
  • These neighbourhoods are technically known as Middle Super Output Areas (MSOAs).  MSOAs are a type of Census geography, and tend to have a population of between 5,000-15,000 people.  You can find more information out about MSOAs on the Office for National Statistics website. 
  • For data confidentiality reasons, cases are not published when they number 0,1 or 2 in a neighbourhood. 
  • The data is updated on a daily basis, and you can look at data for the whole of England. 

What is the Suffolk mortality rate from COVID-19, can we divide the number of deaths directly into the number of cases?

  • This question is simple, but difficult to answer.
  • The case fatality rate is the number of confirmed deaths divided by the number of confirmed cases.
  • We cannot simply divide the number of deaths in Suffolk by the number of confirmed cases.
  • This not accurate because it relies on every case of COVID-19 being identified through testing. Evidence suggests that many cases of COVID-19 are not identified as at the start of the pandemic the availability of testing was limited, and quite a high proportion of people with COVID-19 are asymptomatic, and may therefore not know they need a test.
  • When there are people who have the disease but are not diagnosed, the case fatality rate will overestimate the true risk of death. With COVID-19, we think there are many undiagnosed people.

What is the infection mortality rate for Suffolk?

  • To more accurately estimate mortality from COVID-19 in Suffolk we need to calculate the infection fatality rate, which is the number of deaths from a disease divided by the total number of cases.
  • For example, if 10 people die from a disease, and 500 actually have it, then the infection fatality rate is 10 / 500 = 2%. The problem is that we don’t know how many people have had COVID-19 because not everyone has been tested.
  • Some estimates have been suggested for the proportion of people who have had COVID-19 and while these are not specific to Suffolk, we can use them to estimate the infection fatality rates.
  • One research group has estimated that 443,000 people in East of England have been infected with COVID-19.
  • Assuming that the rate of COVID-19 infection is the same across all counties within East of England, this would suggest around 53,780 people in Suffolk have had COVID-19. Using these figures we can estimate that the infection fatality rate is 558 / 53,780 = 1.04% i.e. 1 in 100 people with confirmed COVID-19 have died in Suffolk.
  • Note that even this is an estimate, and certain groups of people have higher risk of dying from COVID-19, so the risk of death varies depending on characteristics such as age, gender, ethnicity and underlying health conditions.

How does UK mortality compare with other countries?

  • This information is taken directly from the June 2020 Office for National Statistics publication: Comparisons of all-cause mortality between European countries and regions: January to June 2020. This article looks at all-cause mortality as a comparable international indicator of the impact of the coronavirus (COVID-19) pandemic and does not specifically analyse deaths involving COVID-19; deaths are shown for the UK countries by date of registration.
    • There has been considerable interest in international comparisons of mortality during the coronavirus (COVID-19) pandemic.
    • The best way of comparing the mortality impact internationally is by looking at all-cause mortality rates by local area, region and country compared with the five-year average.
    • All-cause mortality avoids the problem of different countries recording COVID-19 deaths in different ways, and also takes into account the indirect impact of the pandemic, such as deaths from other causes that might be related to delayed access to healthcare.
    • The ONS found that whilst England did not have the highest peak mortality, it did have the longest continuous period of excess mortality of any country compared, resulting in England having the highest levels of excess mortality in Europe for the period as a whole.
    • The ONS have produced an interactive animation that allows comparison of Suffolk to other European areas.

What data do you have on ethnicity and COVID-19?

  • While some ethnicity data is shared with us, ethnicity data can sometimes be incomplete. 
  • We are exploring ways of obtaining better quality data in this regard, working with local health partners, which we hope will help to inform our work in the future, but are still working through both the analytical and information governance issues relating to this.

Below is a list produced by the Office for National Statistics that identifies common terms used as part of the COVID-19 response:


As part of Suffolk's continuing support to the ongoing emergency response and recovery phase of the COVID-19 pandemic, the following dashboard is designed to highlight key economic and social indicators. 

This dashboard is currently a work in progress, with additional data being added as and when it becomes available (publicly and internally).

View the data dashboard here

This includes data on:

  • Employment and Unemployment Rates
  • Alternative Claimant Counts
  • Universal Credit Statistics - People & Households
  • Business Counts (Births and Failures)
  • Poverty Statistics
  • Crime Statistics
  • Mobility Changes

An estimated 962,000 people living in private households in the UK (1.5% of the population) were experiencing self-reported "long COVID" (symptoms persisting for more than four weeks after the first suspected coronavirus (COVID-19) infection that were not explained by something else), as of 6 June 2021; this is down slightly from 1.021 million (1.6%) at 2 May 2021[1].

Of people with self-reported long COVID, 856,000 (89.0%) first had (or suspected they had) COVID-19 at least 12 weeks previously, and 385,000 (40.0%) first had (or suspected they had) COVID-19 at least one year previously.

Applying the above metrics to Suffolk, it is estimated that 11,419 people living in Suffolk (1.5% of the Suffolk population) are experiencing self-reported long COVID. Of these, an estimated 10,163 (89.0%) first had (or suspected they had) COVID-19 at least 12 weeks previously, and 4,567 (40,0%) first had (or suspected they had) COVID-19 at least one year previously.

The following links contain information from the Office for National Statistics (ONS), Department for Work and Pensions (DWP), HMRC and other official sources.  These have all been produced by the Suffolk Office of Data and Analytics: 

Key findings have been compiled into short briefings on the following topics: 

Research Action Digest And Review

Last RADAR  - This is the final edition of the RADAR report from April 2021. 

Public Health Suffolk's weekly RADAR:

  • summarises COVID-19 related research evidence, published in the previous week, that is relevant to the Suffolk system,
  • makes recommendations for action, and
  • aims to ensure research evidence is rapidly disseminated and turned into local action.

Our approach will be to include "need to know" research and not "nice to know". We will not be including research specific to NHS healthcare as this is covered elsewhere, including nationally.

Key sources of information include (but is not limited to) the following peer reviewed journals and websites:

Each article we include has also been given a grading level based on GRADE. This is an internationally recognised grading system used by the American Medical Association/ Cochrane for consistency in grading evidence.  Articles are graded for Quality of Evidence and Strength of Recommendation.

Public Health England have a publicly available COVID-19 map that looks at neighbourhood level data on positive cases diagnosed in the last week (7 day rolling average).    

  • These neighbourhoods are technically known as Middle Super Output Areas (MSOAs).  MSOAs are a type of Census geography, and tend to have a population of between 5,000-15,000 people.  You can find more information out about MSOAs on the Office for National Statistics website. 
  • Enter your postcode to find your area, double click on the map, use the + and - buttons to zoom, or "drag and drop" to move around the map.
  • Select an MSOA (click on the area) to see the number of cases for the period
  • For areas such as Suffolk, the numbers of cases are low.  For data confidentiality reasons, cases are not published when they number 0,1 or 2 in a neighbourhood. This means a lot of the data on the map is shaded in white.   

We are working on integrating this data with our data dashboard.

A COVID Symptom Study (CSS) app has been developed. Some estimates are published on maps on their website (to local authority level), and at a lower level to people who have signed up to share data on symptoms through the app. 

On 12 August, a new UK-wide methodology to record COVID-19 deaths was announced and the deaths data reported on the Government's Coronavirus (COVID-19) in the UK website changed as a result. This may affect reported figures and ability to compare areas or change over time. Suffolk CoronaWatch uses deaths data reported from the ONS, so the figures our local website are not affected by this change.

Office for National Statistics (ONS) data

Coronavirus (Covid-19) has spread across the vast majority of neighbourhoods in England and Wales. The ONS have produced an interactive map that allows you to see the number of deaths, where COVID-19 was mentioned as a cause on the death certificate. 

Public Health Suffolk are undertaking local analysis of this data.


All viruses including the virus that causes COVID-19 evolve over time. When a virus makes copies of itself, it can change slightly, these changes are called “mutations”. A virus with one or more new mutations is referred to as a “variant” of the original virus.

When a virus is widely circulating in a population and causing lots of infections, the likelihood of the virus mutating increases. The more opportunities a virus has to spread, the more it replicates – and the more opportunities it has to undergo changes.

Most viral mutations have little to no impact on the virus’s ability to cause infections and disease. Depending on where the changes are located in the virus’s genetic material, they may affect a virus’s properties, such as how easily the virus can spread, or virus severity.  

This information was taken from the World Health Organization website. 

Names of variants

Previously, variants were named after the places they were first identified (for example the 'Kent' variant).  However, the World Health Organization has published new names for variants using Greek letters.  So the variant previously commonly known as the Kent variant is now commonly known as the Alpha variant.  For a full list of names have a look on the World Health Organization website.

Data on variants

Public Health Suffolk are collecting data on variants of concern (VOC) and variants under investigation (VUI) internally, we receive this information from Public Health England.  Public Health England also publish weekly data on the Delta VOC (B.1.617.2). In June 2021 Public Health England experts stated that the Delta variant has overtaken the Kent variant to become the dominant COVID-19 variant in the UK.  You can find more information on the Public Health England website, alongside local authority Delta variant data

Work in Suffolk to identify vulnerable populations

Following the outbreak of Covid-19, the Suffolk Office of Data and Analytics (SODA) set out to identify which individuals and households in Suffolk may be particularly vulnerable to the impact of the Coronavirus.

A list of the clinically extremely vulnerable or ‘shielded’ residents was shared by central government. Emergency food parcels were sent out to those who indicated that they were struggling to get food supplies and support was offered through the Home But Not Alone service to those with care needs. 

In addition to residents on the shielding list, a team of analytical, data, information governance, and IT specialists was pulled together to identify other potentially vulnerable groups. A data-led exercise was conducted to identify people and households who may be particularly clinically, financially or socially vulnerable. Data from Suffolk County Council, the District and Borough Councils, and other organisations such as DWP was brought together to produce a list of individuals falling into these groups across Suffolk.

A list of the most vulnerable was produced and shared with the relevant local authorities. Each person on this list was contacted by the Home But Not Alone service in order to check their welfare and signpost to any relevant support services they may need.

The outputs of this work are sensitive and cannot be shared on the Healthy Suffolk website, however the tools below may also be of interest, and are in the public domain.

Tools that can help identify potentially vulnerable populations

In response to the COVID-19 (coronavirus) pandemic, many tools were produced nationally to help identify potentially vulnerable or high risk populations.

This information is taken directly from the GOV.UK website. 
You can find a more detailed briefing on R as well as the latest data via the GOV.UK briefing on the R number and growth rate in the UK.

What is R? 

The reproduction number (R) is the average number of secondary infections produced by 1 infected person.

  • An R number of 1 means that on average every person who is infected will infect 1 other person, meaning the total number of new infections is stable.
  • If R is 2, on average, each infected person infects 2 more people.
  • If R is 0.5 then on average for each 2 infected people, there will be only 1 new infection.
  • If R is greater than 1 the epidemic is growing, if R is less than 1 the epidemic is shrinking.

R can change over time. For example, it falls when there is a reduction in the number of contacts between people, which reduces transmission.

What is a growth rate?

The growth rate reflects how quickly the number of infections are changing day by day It is an approximation of the change of number infections each day. If the growth rate is greater than zero (+ positive), then the disease will grow. If the growth rate is less than zero (- negative) then the disease will shrink.

The size of the growth rate indicates the speed of change. A growth rate of +5% will grow faster than one with a growth rate of +1%. Likewise, a disease with a growth rate of -4% will be shrinking faster than a disease with growth rate of -1%. Further technical information on growth rate can be found on Plus magazine.

How are growth rates different to R estimates?

R does not tell us how quickly an epidemic is changing. Different diseases with the same R can give epidemics that grow at very different speeds. For instance, a disease with R=2 with infection lasting years will grow much more slowly than a disease with R=2 with infection lasting days.

The growth rate provides us with information on the size and speed of change, whereas the R value only gives us information on the direction of change.