Covid 19 Event Risk Assessment Planner
UNITED KINGDOM
Thursday 12th December 2024Estimated chance that one or more individuals are COVID-19 positive at an event (diagonal lines) given the event size / number of attendees (horizontal x-axis) and the current case prevalence within the population(vertical y-axis)
Estimated chance that one or more individuals are COVID-19 positive at an event (vertical y-axis) given the event size / number of attendees (horizontal x-axis) and the current case prevalence (curved lines)
Data date range: 28th November 2024 to 12th December 2024
Last Update: Wednesday 6th December, 2023 08:22
Population: 66,796,807Alt view of dataU.K. England Scotland N.I. WalesCurrent Data 1 week ago 2 weeks ago 1 month ago 2 months ago
| Regions (England): | Authorities / Districts / Postcode (UK): |
The following 10 authorities currently have the highest 10-day rate of infections in the UK: Lisburn and Castlereagh, Ards and North Down, Antrim and Newtownabbey, Mid and East Antrim, Belfast, UNITED KINGDOM, Newry, Mourne and Down, Armagh City, Banbridge and Craigavon, Causeway Coast and Glens, Derry City and Strabane.
The above graph of event attendees (horizontal x-axis) against risk of an infected attendee (vertical y-axis) is overlain with curved lines of level of infection within the community. This COVID-19 Risk Assessment Planning tool can therefore be used to explore the possibility that at least one person at an event of a certain size is currently infected with COVID-19, given a certain number of circulating infections in the selected region.
The above graph of event attendees (horizontal x-axis) against number of circulating infections (vertical y-axis) is overlain with diagonal lines of level of chance that somebody infected with Covid-19 is attending a particular event. This COVID-19 Risk Assessment Planning tool can therefore be used to explore the possibility that at least one person at an event of a certain size is currently infected with COVID-19, given a certain number of circulating infections in the selected region.
These calculations only tell you how likely it is that at least one person at any event of a given size is infectious. This is not the same as the risk of any person being exposed or infected with COVID-19 at the event.
To identify the chance of an infected person attending an event, first determine the likely size of the event on the horizontal x-axis and then follow the line upwards until you hit the horizontal incidence lines. The first line with blue circular dots (●) is based upon the number of recorded cases in the selected region over the last 10 days. The coloured diagonal lines and the coloured dots (mouse over to get the exact value) show the chance of an infected person attending the same event. So, if the event has say 500 people attending and you are between the green and purple lines there is between a 20% to 50% chance of an infected person at the event. However, not all cases are caught by the testing system and the number of cases in circulation will therefore exceed the number of tested cases. A reasonable estimate of the ascertainment bias is somewhere between 2 and 5 – see the About page. In which case you need to proceed up the graph to the next pair of horizontal lines. The line with yellow diamonds (◆) has an ascertainment bias of 2 and the line with red triangles (▲) has an ascertainment bias of 5. Following the attendees line into this region of the graph will show you that the risk level will probably move above the 50% level and lie between 50% and 90%, if not above. It is then up to you as an individual to decide whether to attend the event or not and if you do what precautions to take. If the event is outside and the opportunity to socially distance yourself from other attendees is high and, in addition, you and other attendees wear correctly fitted face masks and wash your hands regularly then the chance of catching Covid-19 reduces. If however the event is inside with poor ventilation and social distancing is restricted then the chance of catching Covid-19 increases significantly.
To identify the chance of an infected person attending an event, first determine the likely size of the event on the horizontal x-axis and then follow the line upwards until you hit the curved bias lines. The first line with blue circular dots (●) is based upon the number of recorded cases in the selected region over the last 10 days. If the event has, say, 100 people attending based upon the number of recorded cases read across to the vertical axis to determine the chance that an infected person is attending the event – probably greater than 40%. However, not all cases are caught by the testing system and the number of cases in circulation will therefore exceed the number of tested cases. A reasonable estimate of the ascertainment bias is somewhere between 2 and 5 – see the About page. In which case you need to proceed up the graph to the next curved line. The line with yellow diamonds (◆) has an ascertainment bias of 2 and the line with red triangles (▲) has an ascertainment bias of 5. Following the attendees line into this region of the graph will show you that the risk level will probably move above the 50% level and lie somewhere between 50% and 90%, if not above. It is then up to you as an individual to decide whether to attend the event or not and if you do what precautions to take. If the event is outside and the opportunity to socially distance yourself from other attendees is high and, in addition, you and other attendees wear correctly fitted face masks and wash your hands regularly then the chance of catching Covid-19 reduces. If however the event is inside with poor ventilation, poor mask discipline and social distancing is restricted then the chance of catching Covid-19 increases significantly.
The “Current data”, “2 weeks ago”, “1 month ago” and “2 months ago” buttons can be used to show how the situation for the selected region has evolved over time.
All of these calculations are necessarily estimates, based on imperfect data. It is not possible to tell you the probability that someone in the event will get infected. It is important to remember that a certain amount of chance is involved in these outcomes but you have the means to reduce that probability by using this data to make evidence based decisions, following the official recommendations, taking the recommended precautions and being cautious. Large event planners need to exercise caution in the coming months, especially given the potential for one infected person to transmit the virus to many others in one super-spreading event.
The above graph and data can be used to support an Event Risk Assessment (RA) and help you decide what precautions need to be taken and what measures should be put in place to protect event attendees. There are several very good websites that can take you through the Risk Assessment process and assist you in developing a RA for your event. These include: