Timeline

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Covid 19 Event Risk Assessment Planner
UNITED KINGDOM

Tuesday 5th July 2022

This part of the website shows the chronology of the change in %chance (vertical y-axis) during the pandemic since the start of mass testing in May 2020. Two views are available; one showing the timeline history of the change in %chance during the pandemic over time (horizontal x-axis); the other view, accesible via the Alt Timeline View button, shows the curved lines of chance versus event size, which using the date slider, shows how the risk vs event size has varied with time. The initial timeline view shows the change in cases per 100,000 people over time.

Data date range: 15th May 2020 to 26th June 2022
Last Update: Monday 27th June, 2022 17:10
Population: 66,796,807Alt view of data

U.K. England Scotland N.I. WalesAlt Timeline View

Regions (England):Authorities / Districts / Postcode (UK):
    Date: 12-Feb-21
    15-May-2012-Feb-21
    Attendees: 100
    105000
    Since May-20 2020 2021 Since Jul-21

    The following 10 authorities currently have the highest rate of infections (over a 10 day period) in the UK Cambridge, Isle of Wight, Orkney Islands, South Cambridgeshire, Shetland Islands, Cambridgeshire, Basingstoke and Deane, Vale of White Horse, Barrow-in-Furness, Na h-Eileanan Siar.

    The following 10 authorities currently have the lowest rate of infections in the UK Powys, Ceredigion, Monmouthshire, Newport, Torfaen, Caerphilly, Neath Port Talbot, Carmarthenshire, Flintshire, Swansea – lowest first.
    As mentioned above this section of the website lets you view the evolution of %chance of an infected person attending an event over time since May 2020 using the slider below the graph area. May 2020 has been chosen as the start point because prior to this date the UK government had chosen not to have a campaign of widescale testing so the number of cases in the community was probably widely clear of those indicated by the number of cases reported in the official government data. The slider steps through the data 1 week at a time because that level of granularity should be sufficient over the period of the pandemic. Friday has been chosen as the day of week of interest because the data provided by the devolved governments, apart from being constantly added to, is also updated and corrected as the information passes up the data chain to the team posting it on the various websites and can take a couple of weeks to stabilise. At weekends data is always a bit more erratic and unreliable as it seems to take longer to flow up the data chain and as a result is subject to more corrections over time before it stabilises. Obviously this delay and updating only really impacts the more recent data – that provided for dates in the last 2 weeks or so – but it is better to have as accurate a picture of the evolution of %chance as possible. As you will scroll through the timeline you can clearly see the impact of lockdown early 2021 on the %chance of an infected person attending an event during the summer followed by the sharp rise in cases in October/November as the English Government tried, unsuccessfully, to implement its zoning system for restricting people’s movements. It also shows the peak in %chance in the 2nd wave of infections early in 2021.

    As mentioned above this section of the website lets you view the evolution of %chance of an infected person attending an event over time since May 2020. May 2020 has been chosen because prior to this date the UK government had chosen not to have a campaign of widescale testing so the number of cases in the community was probably widely clear of the number indicated by the number of cases reported in the official government data. The data points are plotted for each Friday because that level of granularity should be sufficient over the period of the pandemic to see the peaks and troughs and the overall shape of the pandemic. Friday has been chosen as the day of week of interest because the data provided by the devolved governments, apart from being constantly added to, is also updated and corrected as the information passes up the data chain to the team posting it on the various websites and can take a couple of weeks to stabilise. At weekends data is always a bit more erratic and unreliable as it seems to take longer to flow up the data chain and as a result is subject to more corrections over time before it stabilises. Obviously this delay and updating only really impacts the more recent data – that provided for dates in the last 2 weeks or so – but it is better to have as accurate a picture of the evolution of %chance as possible. From the graph you can clearly see the impact of lockdown early 2021 on the %chance of an infected person attending an event during the summer followed by the sharp rise in cases in October/November as the English Government tried, unsuccessfully, to implement its zoning system for restricting people’s movements. It also shows the peak in %chance in the 2nd wave of infections early in 2021.

    This view of the timeline graph is overlain with a histogram of the number of cases per 100,000 people (plotted against the rh axis). This clearly shows the relationship between %chance and the number of cases and validates that the data is being interpolated correctly. The histogram blocks are 7 days wide and the block height is equivalent to the accumulated cases over the previous 10 days on the Friday of interest. The rh edge of the block is aligned with the Friday date on the X-axis.