UK CoV-2 Update No logical reason for lockdown from 18Feb2021

UK CoV-2 Update No logical reason for lockdown from 18Feb2021

As shown in the image opposite, with low UV, high Relative Humidity and low temperatures airborne virus particles are more abundant (greater viral load), more people catch the virus and breathe out more virus particles, getting trapped in the lower atmosphere. Airborne viruses often attach themselves to small water molecules in the atmosphere and are breathed in. Less sunny, higher moisture and lower temperatures weather conditions prevent the virus particles reaching higher levels in the atmosphere and are not irradiated, they build up in the lower atmosphere, increasing viral load. The worst possible conditions for virus spread is sunless, foggy (high moisture content), windless (air cannot move viral load laterally), and low temperature (air cannot move viral load vertically).

Mountainous areas covered in low cloud and windless conditions, has the same effect. The Italian ski resort in the first outbreak was an ideal breeding ground, and hence extremely high infection rate. Another meteorological consideration of wind, downwind of large conurbations, with cloudy (little UV), high moisture, and low temperatures there is a risk of moving higher viral load. For example, with a westerly wind over London there would be a higher risk of infection over East London, Kent, and Essex.

The opposite occurs when UV levels are high, lowering the moisture levels (RH) and increasing temperature (raising the air and hence viral load, by convection), the airborne viruses are then irradiated and killed, hence less virus particles (virions). Virus particles in these conditions, due to drier air and increased thermal conditions can reach high into the atmosphere, up to a point where UVB and occasionally UVC can irradiate them. This is the crucial time for gaining herd immunity, less virions, less risk of infection, and because of the small number of virions the ensuing respiratory disease will be less potent.

On 13Jun2021 weekly COVID-19 deaths for England & Wales of 57 are 1,515 per week lower than the 11 year average of 1,572 (2010-2020) for respiratory deaths in England & Wales (the 3rd Benchmark)

In 2020 lockdown was ended when the COVID-19 deaths were 2,827. This figure was passed on the downward slope on 23Feb2021 and still in lockdown Another benchmark passed.

Statistically and scientifically there is no logical reason for lockdown or any other restrictions from 18Feb2021

Respiratory death peaks for the last 11 years, England & Wales:
Dates when COVID-19 deaths fell below
2014/15 (3,521) 18Feb2021 1st Benchmark
2017/18 (3,075) 21Feb2021
2020/21 (2,770) 23Feb2021 (Unlocked 10May2020)
2010/11 (2,706) 24Feb2021
2016/17 (2,690) 24Feb2021
2012/13 (2,508) 24Feb2021
2019/20 (2,477) 25Feb2021
2009/10 (2,345) 26Feb2021
2018/19 (2,214) 27Feb2021
2013/14 (2,100) 27Feb2021
2015/16 (1,971) 01Mar2021
2011/12 (1.934) 02Mar2021 2nd Benchmark
2020/21 CoV-2 06Mar2021 (1,572) 3rd Benchmark

The first benchmark is derived from the peak deaths of the 2014/15 seasonal respiratory virus outbreak of 3,521,when the NHS coped and there were no restrictions or lockdowns.

The second benchmark set when COVId-19 deaths fell below all 11 years seasonal peaks (2010-2020) of 1,934 the lowest of the peaks in 2011/12.

The third benchmark set when COVID-19 deaths fell below the average respiratory deaths the 2010-2020 average of.1,572

Death rates are following the Gompertz curve as all previous airborne viruses have done in the past.

The most robust measure for all seasonal airborne viruses is by understanding of death rates, not by testing transmission with unknown numbers of false positives.

Death rates provide both a better understanding of potency (as in viral load in the atmosphere) and transmission.

Lockdown & restrictions Actual vs Logical

Weekly death rates for COVID-19 on 13Jun2021 are 57, 1,514 lower than average weekly respiratory deaths for the last 11 years

SARS CoV-2 is an airborne seasonal respiratory virus. Just like Influenza, Spanish Flu, Hong Kong Flu, H1N1, H1N2, Bird Flu etc.All of these viruses act in virtually the same ways, the death rates begin to rise in September and start to fall in January. They follow the well documented Gompertz curve.

The reason is, in September UV radiation begins to fall, and then begins to rise again in January. UV radiation breaks down the virus's mRNA, reducing its potency and lessens its lethality. This happens with all airborne viruses.

If the governments aim was to "Save the NHS", their first objective, would be to look back at historical data and see, at the peak of the 2015 weekly respiratory death rates for England & Wales were 3,521, when the NHS coped without lockdown or any other restrictions.

This should have been their benchmark. Had this logical approach been adopted. we would have had 31 days in Mar/Apr2020 and 47 days in Jan/Feb2021. The difference between Logical (78 days) and Actual (189 days) is 111 days and counting.

Daily update comparing COVID-19 deaths with Sunshine (UV radiation). temperature (Tmax) and relative humidity (RH) - averages for the UK.

England & Wales C0VID-19 deaths 7-Day count-backs from;

23Jan2021 8,739 (7778) Peak

Under 1st Benchmark 3,521
18Feb2021 3,859 (3435)
19Feb2021 3,634 (3234)
20Feb2021 3,458 (3078)
21Feb2021 3,415 (3039)
22Feb2021 3,363 (2993)
Unlocked last year 2,827
23Feb2021 3,112 (2770)
24Feb2021 2,815 (2505)
25Feb2021 2,684 (2389)
26Feb2021 2,496 (2221)
27Feb2021 2,341 (2083)
28Feb2021 2,270 (2020)
01Mar2021 2,196 (1954)
Under 2nd Benchmark 1,934
02Mar2021 1,991 (1772)
03Mar2021 1,864 (1659)
04Mar2021 1,783 (1587)
Under 3rd Benchmark 1,572
All data after this is below the 3rd benchmark

13Jun2021 64 (57)

After date column, is total UK and for England & Wales (in brackets)

Bearing in mind Worldometers daily COVID-19 data use the whole of the UK and weekly data form ONS is for England & Wales only. The above data would be 11% lower (minus Scotland & Northern Ireland) to be representative of England & Wales ONS weekly figures.

ONS data update for 08Jan2021 has changed it's format and also changed a lot of historical data!!!

The weather conditions during January 2021 were perfect for increased airborne viral spread and increased potency, cold, high humidity and most importantly lack of sunshine.

COVID-19 daily deaths data from CoronaVirus

Daily UK average weather data from Weather Research.


The first benchmark was set at 3,572, the peak of the 2014/15 respiratory outbreak, when the NHS coped without lockdown or any other restrictions.

The second benchmark was derived when CoV-2 death rates fell below 2,827, when the government unlocked on 10thMay2020 in the 2020 Mar-May outbreak.

The third benchmark was derived, when weekly England & Wales CoV-2 deaths fell below all the peaks of respiratory deaths for the last 11 years.
The lowest peak was 1,934 during the 2011/12 season, which occurred on 02Mar2021 (1,772)

The fourth benchmark occurred when weekly E&W death rates fell below the average respiratory deaths for 2010/11-2019/20 seasons at 1,572.

People have asked why not include other respiratory deaths like Influenza and pneumonia. The reason is, we have never been locked down or had any restrictions until Cov-2 for at least the last 11 years. Don't forget CoV-2 is a respiratory disease.

There is also a lot of confusion about reporting of other respiratory deaths, in just one week between 01Jan2021 and 08Jan2021 the number jumped from 678 to 7,025, I can't find a rational answer, better ask ONS..

UK CoV-2 Update No logical reason for lockdown from 18Feb2021

Peaks & Troughs of Seasonal Airborne Virus Outbreaks

The table to the right shows the troughs and peaks dates for weekly respiratory deaths in England & Wales

2020 and 2021 include CoV-2/COVID-19

Noticeable is, trough dates are around the end of August/beginning of September, about 3-4 weeks before the Autumnal equinox. Most peak dates are within the first 2 weeks of January, about 3-4 weeks after the winter solstice. This indicates UV radiation as a key factor.

A definitive seasonal pattern apart from 2020 semi-seasonal CoV-2/COVID-19 and 2016 when the peak was just 99 more than 07 January.

The semi-seasonal CoV-2/COVID-19 outbreak is questionable as with a novel virus it wasn't recognised as such during Dec2019, Jan/Feb 2020 and only became known about during March,

As someone who was infected with COVID-19 in mid Dec2019, probably in Lisbon and confirmed by classic symptoms, x-rays, and CT scan. It was probably diagnosed as a bad chest infection, as was mine, therefore it probably was an extension of the 2019/20 seasonal epidemic.

3rd Waves in Europe
I have read a lot of reports in the news about third waves of SARS CoV-2 in the last few days. What they are referring to is seasonal Gompertz curves.

As such I thought I would investigate. Using Worldometers I picked popular holiday destinations of UK citizens.

N.B. Look carefully at the scales for each country, as the vary considerably.

Firstly, I suggest there is no such thing as second, third or fourth waves (outbreaks) of airborne viruses, they have a distinct seasonality. Starting about the 1stSeptemeber and peaking about the middle of January. The outbreak in Mar/Apr/May 2020 looked unusual by recorded deaths of CoV-2 only starting in March2020. The virus was in the atmosphere well before this date, at least December 2019 and probably earlier, making it the 2019/20 seasonal outbreak.

Understanding how airborne viruses spread is interesting. They are minute, you could get billions on the tip of a needle. They are very light in weight and travel in the atmosphere at different heights from the surface to above the tropopause driven upwards by winds an heat (convection). UV radiation kills viruses by breaking down their mRNA. The higher the virus gets in the atmosphere the more it is destroyed by UVB and even occasionally UVC at the highest levels. Thank goodness UVA, which we get at ground level, also does it work, but slight less efficiently. However UVA can be blocked from reaching the surface by clouds (water/ice) and water vapour.

This is why we see higher correlations with death rates when there are lower temperatures, lower sunshine levels and moister air. When these parameters change to higher levels of sunshine, this produced higher temperatures and a drier atmosphere, depending on airmass.

So why are there peaks and troughs? Day length is a major factor, as the longer the day length, the greater possibility for more sunshine and hence more UV radiation.

Any airborne virus can be trapped in the lower layers of the atmosphere by clouds and water vapour. Because UV isn't available to kill the virus, the numbers increase and its potency increases (because there are more in the lower atmosphere), hence greater deaths..

On the charts to the right, what you are seeing in most, is the death rates from CoV-2, last years peak and this seasons peak, as well as weather (cloud/sunshine) effects.

There are no waves, they are different seasons and different weather conditions

Summer vs Winter Deaths

During summer when temperatures rise we often hear about heatwave deaths in the media.

These two plots show all causes of deaths in Summer vs Temperature (Max) and in Winter vs Temperature (Max)

Average weekly deaths for England & Wales 2010-2019 10,032

Average weekly Summer deaths
2010-2019 9,502

Average weekly Winter deaths
2010-2019 10,627

Which equates to 58,500 more deaths per year in winter than summer.

The Weather Effect on Seasonal Airborne Virus Outbreaks

Does weather affect airborne virus epidemics? I have read some papers which argue against a weather "effect" and say no. The peak and trough information on the last 11 years in the UK does indicate a seasonal trend.

Because the Mar/Apr2020 CoV-2 epidemic was not considered as fully seasonal, I looked at weekly all causes of death and respiratory deaths from 2010 to a benchmark.

It is quite possible that the Mar/Apr epidemic was seasonal, there may have been many thousands of people who had respiratory symptoms (COVID-19) during Dec2019, Jan, and Feb 2020 and were treated as a bad flu without needing hospital treatment, just two courses of antibiotics from the GP. (I was one of them Dec/Jan with X-ray and CT scan as evidence, I did need hospital visits for the scans) and this was before SARS CoV-2/COVID-19 had been recognised..

When you see the correlations on the plots on the left they confirm seasonal airborne viruses are controlled by the weather, particularly UV radiation which kills airborne viruses. Because airborne viruses a very light in weight they can reach high altitudes and hence stimulated by UVA (which boosts vitamin-D synthesis and enhancing the innate immune system, UVB during summer months, and probably UVC at the very highest levels...

Deaths data from ONS is weekly for England & Wales and therefore the temperature, sunshine (UV) data comparisons have to be averaged weekly. This significantly weakens the correlation for Sunshine (UV) which is the key marker. UV radiation destroys airborne viruses hence reduces the viral load in the atmosphere

Length of Day (LOD) vs Sunshine Hours

Because daily sunshine hours are erratic, ranging from zero to 15 hours per day in the summer. Having given this some thought I looked at the relationship between Length of Day, which has a stable rise and fall during a season,.and sunshine hours for Birmingham.

The overall correlation between the two parameters was a moderate 0.54, this was lower than anticipated due to the erratic nature of sunshine. When you observe the polynomial curve of each trend line the relationship is more understandable. The LOD trend R squared=0.9591 almost matching the Sunshine polynomial curve. Thus showing LOD could be used as a good marker for potential sunshine/UV radiation.

Conclusion: LOD would be a better parameter to measure airborne virus activity and hence transmission and deaths for long term forecasting and sunshine hours up to 15 days ahead for short term forecasting..

Day Length vs Airborne Viruses Respiratory Deaths & COVID-19

In the previous section we looked at how weather affects airborne viruses respiratory deaths. Two major problems were obvious, firstly death rates are compiled weekly by ONS, and secondly because of that the weather data has to be UK weekly means. This is shown up by moderate correlations.

Because weather is very variable, it could be wet, cloudy and cool in the north, but dry, with bright sunshine and warm in the south. Averaging weather never gives a good result. Having thought about this problem we decided to look at day length, as this does nor vary by much across the country. As the death rate data is for England & Wales, we chose Birmingham as a central point to collect day length hours and minutes per day.

The charts opposite show, on the left hand column weekly death rates versus average 7-day count back (weekly) day lengths.

Correlations ranged between weak to moderate, but with an obvious three week lag between deaths and day lengths. In the charts on the right we lagged the death rates by 3 weeks and the correlations increased dramatically to moderate and strong.

This shows day length is an important factor to improve forecasting ability for future airborne virus outbreaks. the longer the day length the more likely there is more sunshine. And it is sunshine (UV radiation) which kills airborne viruses, always has done and always will do.

The number of deaths depends on two factors, the potency of the virus and what happened in the previous season. this is shown by many deaths in the 2014/15 season (strong correlation) and far less deaths in the next season 2015/16 (moderate correlation).