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Q: Why doesn’t the latest data date range include today’s date?

A: The data is pulled down from the devolved government websites and sometimes there is a few days lag – especially at weekends and over bank holiday weekends – in the current day’s data becoming available.

Q: Does that mean that the situation could be worse than portrayed in the graph?

A: Potentially, but only slightly, which is why the system always pulls data from the last 10 days and provides ascertainment biases of 2 and 5 to help account for any shortfall. It could also be slightly better if the trend is for falling cases, but better to err on the side of caution.

Q: Why 10 day’s data?

A: The recommended isolation period from the Government, PHE, NHS (11-Dec-20 – see UK Covid self-isolation period reduced from 14 to 10 days) and others is to isolate for 10 days if you have a positive test, journey to the UK from one of the restricted countries or have been in contact with somebody who has tested positive.

Q: How often is the database updated?

A: I try and do it every day in the afternoon, usually between 4pm and 6pm but that’s not always possible and some days the devolved Governments don’t update the data on their websites or release the data until very late in the day. The Northern Ireland Government, for example, didn’t always update their data over weekends or bank holidays. The extended timeline data on the Timeline page is updated once a week over the weekend because of the boundaries for the bars on the cases per 100,000 people histogram plot.
The database was last updated on: Wednesday 6th December, 2023 08:22.

Q: How current is the data?

A: The data from the UK Government’s database is updated nearly every day. However, the data is not fixed, it is constantly being revised; even data that is 6 months old can and does change. Number of cases data usually settles down to a fixed value after a week / 10 days and then stays more or less fixed but can fluctuate by 1 or 2 cases over time.

Q: How does this data relate to the numbers published every evening on British televsion?

A: I take my data from the UK government website GOV.UK Coronavirus (COVID-19) in the UK , I can only assume that the TV companies use the same data. The GOV.co.uk website allows you to extract data from their database in a number of different formats with a number of different metrics. I suspect that the TV companies  extract data using the cumCasesByPublishDate metric whereas I use the cumCasesBySpecimenDate metric, which correctly allocates the cases to the correct date so that I can safely use the accumulated data over the past 10 days as an indicator of the number of cases currently in the community. I can only assume that in some cases it appears to take several days for the data to pass up the reporting chain to be included in the database, so if I were to use the cumCasesByPublishDate metric I could be incorporating data that is more than 10 days old into value used for a particular date. Using the cumCasesByPublishDate metric means that on the timeline page , for example, the number of Covid-19 cases for a particular date are correct and so the timeline data as displayed is correct.   

Q: What is the science behind the analysis performed?

A: The method originally comes from Georgia Institute of Technology, a well respected US university. This website uses exactly the same analysis method and the validation page demonstrates how the method has been transferred from the Georgia Institute of Technology website to this website.

Q: Why ascertainment biases of 2 and 5?

A: Not everybody who has the virus has symptoms – they are asymptomatic – and the Government’s Track and Trace system does not successfully Track and Trace everybody who has been in contact with somebody who has tested positive. Therefore, there needs to be a margin between those tested and those in the community, who may have the virus and may not be aware of it or who do not isolate correctly even though they know they have the virus – see Less than 20% of people in England self-isolate fully, Sage says (Guardian article dated 11-Sep-2020). The Georgia Institute uses biases of 5 and 10 but somewhere in the range of 2 and 5 seems to be about the correct bias for the UK, but it could be worse. The about page has more information. The recently added Infection Ratio number to the mouseover data on the 2 graph views shows Infection Ratio numbers similar to those being talked about on the TV – see Coronavirus (COVID-19) Infection Survey, UK: 29 January 2021 and The Guardian headline on 19-Feb-21  (The Guardian 19-Feb-2021)  stated that 1 in 115 people had Covid-19 for the week ending 12th February, which equates to an ascertainment bias of approximately 4, close to the upper line on the plots in this tool.  Interestingly I’ve noticed that the Georgia Institute have changed their bias numbers to 3 and 5 (mid Feb-21) from the values 5 and 10 that they used when they initially launched their tool. Random checks on the data provided by the C-19 by ZOE app (throughout 2021) show that the ascertainment bias has regularly sat in the range 4 to 5.

Q: What’s the relationship between ascertainment bias and infection ratios and how do these graphs reflect the infection ratios being used in the media?

A: There is no fixed relationship except that as the ascertainment bias increases the infection ratio increases i.e the number falls from 75:1 to 50:1. Passing a mouse over the plotting area of the graphs will display an information box with the X and Y axis data points, the bias number and the infection ratio. Currently, early Feb 2021, as the cursor approaches the ascertainment bias of 5 line you should see infection ratios displayed of around 50:1; meaning that 1 in every 50 people in the community is infected. This report from the UK Government ONS website Coronavirus (COVID-19) Infection Survey, UK: 29 January 2021 from late January 2021 mentions similar infection ratios suggesting that the ascertainment bias line of 5 is the one to concentrate on when using this tool. 

Q: How accurate is the analysis?

A: The analysis is only as good as the data provided. The data presented is not aimed at demonstrating the probability that you will catch the virus but the likelihood that somebody infected with the virus will be at an event. If you take the recommended additional precautions – space, mask, wash – then your chances of catching the virus reduce. The validation page explains the maths behind the analysis.

Q: What does 50% chance, for example, mean?

A: A 50% chance means that there is an odds-on even chance that somebody at the event will have the virus. This is not the same as 50% chance that you will catch the virus. It is up to you to assess that level of risk, decide if you want to go and if you do go, what precautions to take – that’s the purpose of this website, to provide you with the information necessary for you to make those decisions based on the available evidence and respond accordingly – evidence based decisions.

Q: Why does the My-Event page start with Dacorum?

A: The page has to start somewhere and I live in the district of Dacorum (Hemel Hempstead, Berhamsted and others) so I selfishly choose to start it there. I thought it better to display some data initially than to load a page with an empty graph.

Q: Who produced this website?

A: I did, my name is Paul. I live in a small village in rural Hertfordshire in the UK, I’m a retired Mechanical Engineer who spent 43+ years working in the space industry. Spent my time launching rockets from the South American rain forest and designing hardware for spacecraft both in Earth orbit and some which travelled to other planets and the far reaches of our solar system – wouldn’t have missed it for the world. I also design websites in my spare time.

Q: Why did you do it?

A: Because I can, since I’m retired from full-time work I have the time on my hands and the skills to produce such a website and I believe in people making decisions based upon facts and evidence, not on hearsay, conjecture and misinformation.

Q: What qualifies you to produce this analysis?

A: I hold a BSc (Hons) from the Open University and I enjoy doing this sort of activity. Most of my OU study courses were in computer programming / science. As part of my work / job I used to write – and thoroughly enjoy doing so – mathematical models predicting the operation of mechanisms on spacecraft in the zero-gravity environment and amongst many other things analyse satellite ejection from the Ariane 4 rocket during launch to ensure safe separation. The validation page shows that I understand the process of demonstrating that I’ve done it correctly and you are free to download the Excel version of the model and play around with it yourself. If you find an error or dispute my methodology, let me know by email.

Q: On the %chance vs event size graph – the curved line graph – as I tab through the top 10 infected regions the curved lines move progressively down the plotting area yet on the alternative view the horizontal and slopping lines move up and down the plotting area.

A: This is caused by the fact that the vertical axis on the Alt View graph is the number of circulating cases and this coupled with the region population defines where the horizontal and diagonally slopping lines lie. The position of the curved lines on the curved line %chance graph is defined by the ratio between circulating infections and the population of the region.

Q: Can you improve the display on mobile screens?

A: Very difficult, the detail of the graphs would be completely lost if the graph was sized to fit a small screen. You can scroll sideways, not ideal I know but…

Q: My town doesn’t appear on the drop down list of authorities

A: The data from the 4 devolved governments is grouped by local authorities. The recently added (Jun-21) postcode feature allows you to enter a postcode into the Authorities/Regions input box and the system will resolve it into a region in the UK.

In England this is Adur, Allerdale, Amber Valley, Arun, Ashfield, Ashford, Aylesbury Vale, Babergh, Barking and Dagenham, Barnet, Barnsley, Barrow-in-Furness, Basildon, Basingstoke and Deane, Bassetlaw, Bath and North East Somerset, Bedford, Bexley, Birmingham, Blaby, Blackburn with Darwen, Blackpool, Bolsover, Bolton, Boston, Bournemouth, Christchurch and Poole, Bracknell Forest, Bradford, Braintree, Breckland, Brent, Brentwood, Brighton and Hove, Bristol, City of, Broadland, Bromley, Bromsgrove, Broxbourne, Broxtowe, Burnley, Bury, Calderdale, Cambridge, Camden, Cannock Chase, Canterbury, Carlisle, Castle Point, Central Bedfordshire, Charnwood, Chelmsford, Cheltenham, Cherwell, Cheshire East, Cheshire West and Chester, Chesterfield, Chichester, Chiltern, Chorley, Colchester, Copeland, Corby, Cornwall and Isles of Scilly, Cotswold, County Durham, Coventry, Craven, Crawley, Croydon, Dacorum, Darlington, Dartford, Daventry, Derby, Derbyshire Dales, Doncaster, Dorset, Dover, Dudley, Ealing, East Cambridgeshire, East Devon, East Hampshire, East Hertfordshire, East Lindsey, East Northamptonshire, East Riding of Yorkshire, East Staffordshire, East Suffolk, Eastbourne, Eastleigh, Eden, Elmbridge, Enfield, Epping Forest, Epsom and Ewell, Erewash, Exeter, Fareham, Fenland, Folkestone and Hythe, Forest of Dean, Fylde, Gateshead, Gedling, Gloucester, Gosport, Gravesham, Great Yarmouth, Greenwich, Guildford, Hackney and City of London, Halton, Hambleton, Hammersmith and Fulham, Harborough, Haringey, Harlow, Harrogate, Harrow, Hart, Hartlepool, Hastings, Havant, Havering, Herefordshire, County of, Hertsmere, High Peak, Hillingdon, Hinckley and Bosworth, Horsham, Hounslow, Huntingdonshire, Hyndburn, Ipswich, Isle of Wight, Islington, Kensington and Chelsea, Kettering, King’s Lynn and West Norfolk, Kingston upon Hull, City of, Kingston upon Thames, Kirklees, Knowsley, Lambeth, Lancaster, Leeds, Leicester, Lewes, Lewisham, Lichfield, Lincoln, Liverpool, Luton, Maidstone, Maldon, Malvern Hills, Manchester, Mansfield, Medway, Melton, Mendip, Merton, Mid Devon, Mid Suffolk, Mid Sussex, Middlesbrough, Milton Keynes, Mole Valley, New Forest, Newark and Sherwood, Newcastle upon Tyne, Newcastle-under-Lyme, Newham, North Devon, North East Derbyshire, North East Lincolnshire, North Hertfordshire, North Kesteven, North Lincolnshire, North Norfolk, North Somerset, North Tyneside, North Warwickshire, North West Leicestershire, Northampton, Northumberland, Norwich, Nottingham, Nuneaton and Bedworth, Oadby and Wigston, Oldham, Oxford, Pendle, Peterborough, Plymouth, Portsmouth, Preston, Reading, Redbridge, Redcar and Cleveland, Redditch, Reigate and Banstead, Ribble Valley, Richmond upon Thames, Richmondshire, Rochdale, Rochford, Rossendale, Rother, Rotherham, Rugby, Runnymede, Rushcliffe, Rushmoor, Rutland, Ryedale, Salford, Sandwell, Scarborough, Sedgemoor, Sefton, Selby, Sevenoaks, Sheffield, Shropshire, Slough, Solihull, Somerset West and Taunton, South Bucks, South Cambridgeshire, South Derbyshire, South Gloucestershire, South Hams, South Holland, South Kesteven, South Lakeland, South Norfolk, South Northamptonshire, South Oxfordshire, South Ribble, South Somerset, South Staffordshire, South Tyneside, Southampton, Southend-on-Sea, Southwark, Spelthorne, St Albans, St. Helens, Stafford, Staffordshire Moorlands, Stevenage, Stockport, Stockton-on-Tees, Stoke-on-Trent, Stratford-on-Avon, Stroud, Sunderland, Surrey Heath, Sutton, Swale, Swindon, Tameside, Tamworth, Tandridge, Teignbridge, Telford and Wrekin, Tendring, Test Valley, Tewkesbury, Thanet, Three Rivers, Thurrock, Tonbridge and Malling, Torbay, Torridge, Tower Hamlets, Trafford, Tunbridge Wells, Uttlesford, Vale of White Horse, Wakefield, Walsall, Waltham Forest, Wandsworth, Warrington, Warwick, Watford, Waverley, Wealden, Wellingborough, Welwyn Hatfield, West Berkshire, West Devon, West Lancashire, West Lindsey, West Oxfordshire, West Suffolk, Westminster, Wigan, Wiltshire, Winchester, Windsor and Maidenhead, Wirral, Woking, Wokingham, Wolverhampton, Worcester, Worthing, Wychavon, Wycombe, Wyre, Wyre Forest and York.

…and East Midlands, East of England, London, North East, North West, South East, South West, West Midlands, Yorkshire and The Humber, Buckinghamshire, Cambridgeshire, Cumbria, Derbyshire, Devon, East Sussex, Essex, Gloucestershire, Hampshire, Hertfordshire, Kent, Lancashire, Leicestershire, Lincolnshire, Norfolk, North Yorkshire, Northamptonshire, Nottinghamshire, Oxfordshire, Somerset, Staffordshire, Suffolk, Surrey, Warwickshire, West Sussex and Worcestershire.

In Wales: Blaenau Gwent, Bridgend, Caerphilly, Cardiff, Carmarthenshire, Ceredigion, Conwy, Denbighshire, Flintshire, Gwynedd, Isle of Anglesey, Merthyr Tydfil, Monmouthshire, Neath Port Talbot, Newport, Pembrokeshire, Powys, Rhondda Cynon Taf, Swansea, Torfaen, Vale of Glamorgan andWrexham.

In Northern Ireland: Antrim and Newtownabbey, Ards and North Down, Armagh City, Banbridge and Craigavon, Belfast, Causeway Coast and Glens, Derry City and Strabane, Fermanagh and Omagh, Lisburn and Castlereagh, Mid and East Antrim, Mid Ulster, Newry and Mourne & Down.

In Scotland: Aberdeen City, Aberdeenshire, Angus, Argyll & Bute, City of Edinburgh, Clackmannanshire, Dumfries & Galloway, Dundee City, East Ayrshire, East Dunbartonshire, East Lothian, East Renfrewshire, Falkirk, Fife, Glasgow City, Highland, Inverclyde, Midlothian, Moray, Na h-Eileanan Siar, North Ayrshire, North Lanarkshire, Orkney Islands, Perth & Kinross, Renfrewshire, Scottish Borders, Shetland Islands, South Ayrshire, South Lanarkshire, Stirling, West Dunbartonshire and West Lothian.