ONS Covid Infection Survey

The Office for National Statistics (ONS) Covid-19 infection survey is based on random testing of a representative sample of the public in England. It is updated once a week. This gives by far the clearest estimate of the overall infection rate within the community ( The data actually use fortnightly results so the weekly figures represents a rolling average of infections). The results for July 8 show that the level of active infections have fallen to roughly 0.04% of the population and seems to be levelling off at that level. About 1 in 4000 people are currently infected with COVID-19 in England. ONS provide an embedded version of their results which I am hoping gets  updated weekly.

The population of England is 56 million people so an infection rate of 0.03% means there are currently ~ 14,000 people with Covid-19  Another way to see this is to look at the risk of anyone in the public catching COVID-19.

This says that on average there is roughly a 1 in 2500 chance of being infected with COVID-19 each  week. An alternative narrative is that with this level of infection it would take 50 years for everyone to catch COVID-19 at least once and  a further 5000 – 10000 years to actually die from it. This assumes there is no herd immunity or that any  vaccine available.

Here are the regional infections for England.

The graphs in this post should update automatically as the ONS updates their survey results each week. If so I will make a new “widget” !

We shall see next week!

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Comparisons of UK Covid Deaths with Italy

The number of cases and deaths in the UK has been slowly declining and the Government will allow Pubs and Restaurants to open from tomorrow. This post looks at how the UK’s “lighter” touch lockdown compares to that applied in  Italy and then looks wider at the rest of the world. Figure 1 shows a comparison between UK deaths and Italian deaths.

Fig 1. Comparison of UK deaths with those in Italy. The dashed curve are the Italian data advanced 2 weeks.

The UK was just 2 weeks behind Italy although at the time we didn’t know that. The shape of both curves are very similar but the UK eventually fared worse than Italy even after  allowing for the difference in population. It also looks like something went wrong between  the 23rd May and the 8th of June and we are still suffering the consequences.

We also now know that there were far more infections by the beginning of March than were assumed at the time,  so a lockdown 1 week earlier might  have saved up to half the total number of deaths. The reason why we were in the dark in March was simply due to the lack of widespread testing capacity. Italy actually did remarkably well at testing and curtailing the epidemic and now has a low level of infections. The cases curves for both countries are shown in Figure 2.

Fig 2. Confirmed Cases Italy and UK. The flattened curve for UK is due to low early testing capacity.

The reported number of cases in each country also reflects partly the widespread level of testing at the time. For Italy it appears that testing levels were high enough early on in the epidemic because  the shape is similar to reported deaths. The UK shape instead clearly shows a lack of testing data early on highlighting just how unprepared we were initially.

Note also the error in the PHE data for Cumulative Deaths on the 20th May (the negative dip). These are their figures for “Pillar 2” (cases in the community).

18/05 70488
19/05 71796
20/05 70615
21/05 72063

Finally figure 3 shows  how both countries compare to the overall global  picture.

Fig 3. Global Daily Deaths compared to UK/Italy. On this scale the initial outbreak in China looks tiny (are their figures correct?).  Note also the very pronounced “weekend” effect everywhere.

Unfortunately this makes it clear that the pandemic is still quite a long way from ending. There are still increasing numbers of cases across South America, Middle East and the Indian sub-continent. It is also worrying that talk of an Oxford/AstraZeneca  vaccine as early as this September has now been quietly been dropped by SAGE.

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Covid model implies IFR is ~0.5%

At the beginning of March Neil Fergusson modelled the impending Covid-19 epidemic for the UK  which was expected to begin in early April and consequently reach a peak in May, all based on the infection rate assumed at that time. His influential “Report9” circulated and published on March 16 reflected these underlying assumptions. The lockdown measures that he proposed  to suppress infections and thereby allow the NHS to cope with the predicted surge in demand for ICU beds were also timed for April. There seems to have been a widespread belief in SAGE at the time that the UK was 3 to 4 weeks behind Italy, so consequently we had ample time to plan measures accordingly. We can now see that this simply wasn’t true and infections were spreading fast in early March. This was mainly because of open borders to Europe and a lack of testing capability. Figure 1 compares the recorded deaths in Italy, France and England as of June 16.

Figure 1. Daily recorded deaths in Italy, France and in NHS hospitals in England. Note the overall similarity between  England to France. The criteria for recorded deaths vary between countries. Here  I am just using hospital deaths registered by  day of death for England (population: 56 million)

In Figure 1.  I am plotting just the hospital deaths in England as recorded by the NHS because this probably best represents the dynamics of community wide infections. (The tragic deaths that have also occurred in care homes are another story!). Note how the epidemic begins simultaneously in England and France, both of which lag about 2 weeks behind Italy.  However by the end of April  all 3 countries then tail off together at almost the same rate ending together.  The Italian epidemic just seems to have lasted longer.

Ferguson originally released his code for “CovidSim” on GitHUB in May, together with the parameters files that describe the UK, updated to describe the emerging epidemic data. The unmitigated run he used on GitHUB show that he increased Ro to 3 because it was discovered that early UK infections were doubling every 3-4 days. His suppression  simulation was really based on the consequent  March 16 Household Quarantine (HQ) and limited Social Distancing (SD) measures as announced by Boris Johnson, then followed 7 days later on March 23rd by stringent Place Closures(PC). On March 23rd Boris Johnson announced that all pubs, restaurants,  shops, schools, Universities would close forthwith and that everyone should stay at home as far as possible.  March 23rd is therefore considered to be the real lockdown date for the UK, forgetting that a week earlier social distancing had already been already been introduced. As a result of all this the parameter file that Fergusson uses to simulate what really would happen during the UK epidemic is called PC7_CI_HQ_SD, where “PC7” symbolises the 7 day delay between March 19 and March 23 in implementing full lockdown.

Firstly we look at the unmitigated predictions. Figure 2 shows the  comparison between the original Report9 Neil Fergusson model predictions as made in early March with those from his updated May version.

Figure 2. A direct comparison between Fergusson’s Report 9 simulation with R0=2.4 and the later UK simulation in May following the start of the outbreak.

The most striking feature here is the nearly one month anticipation of the real infection peak compared to the earlier Report9 simulations. Note also in passing that the original Report9  runs were made just for Great Britain and for some reason excluded Northern Ireland. This however can only explain a small proportion of the increase in  infections. The major reason for this increase was essentially due to using the observed increase in R0 to 3.0. SAGE were estimating that infections were doubling every 3 days.

Secondly we can compare the new May CovidSim “lockdown” simulations of deaths against the actual statistical data as recorded up to June 16th (Figure 3). I am using COVID-19 deaths as a measure of infection rates mainly  because these are the only consistent numbers across time.

Figure 3. A comparison between the Ferguson model simulation of the UK lockdown with the actual death data vas recorded across the UK including Care Homes. The total unmitigated deaths reach 620,000. The recorded cumulative UK deaths were 41736 on 16 June.

The new model is clearly predicting more deaths than were actually recorded even if we now also include care home deaths.  These care home deaths were more a consequence of NHS lockdown measures rather than community infections as simulated by Fergusson. So what does all this mean ?

Ferguson had assumed an IFR (Infection Fatality Rate) of 0.9% and as a consequence his model predicted that 70,000 deaths would occur by June 16. In reality 41736 total deaths have occurred across all settings by then. It is likely that he calculated the infection rate correctly but simply used a too high value for IFR.

Therefore I would  conclude that IFR is  ~0.5%, and probably less than that once you exclude hot spots of infections such as those occurring  inside care homes.

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