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What will happen if we do nothing but vaccinate?

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Written by Dr Cam Bowie

Former Director of Public Health for Somerset, Cam Bowie, argues that the UK population is being used as a guinea-pig to test the impact of vaccinations alone in containing the Covid virus. Using a model he trusts he shows that introducing an effective track and trace system alongside vaccinations could greatly reduce the incidence of covid and hence also hospital admissions and cases of long-Covid.

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What will happen if we do nothing but vaccinate?  Will it be just a normal winter of colds, coughs and flu or something worse?  If much worse, is there a remedy which does not rely on restrictions?

“Following the science” is not heard much now from Downing Street when it comes to Covid-19.  The contrary would be more precise for the government has not just ignored the science but seems determined to set policies which abnegate what knowledge we have about the epidemic.  The gift this offers to other countries assessing their public health efforts is as valuable to them as it is unexpected.  We are providing an experiment offering a base-line for other countries to assess the effects of their own public health interventions.  The fact that we have twice the number of deaths and hospital admissions for our size compared to other European countries seems to demonstrate our stoicism in accepting preventable suffering.

We are providing a fertile opportunity for Covid-19 to spread throughout the population for months to come.  How many people will be infected in the next year?  How many will suffer long-Covid?  How many more people will die of Covid-19?  If we carry as now we will answer the question “If you do nothing except vaccinate – what will happen?”

How can we tell what will happen?

Professor Karl Friston FRS of The Wellcome Centre for Human Neuroimaging, University College London has refashioned his method of interpreting the huge number of neuronal signals derived from a brain scan to model the Covid-19 epidemic.  His model is called Dynamic Causal Modelling (DCM).  The Covid-19 DCM is designed to accommodate changes in population dynamics and virus behaviour.  It does so by continually assimilating 39 separate series of data such as deaths, vaccine coverage and mobility as the epidemic unfolds.  The model modifies the 54 parameters used in the model such as transmissibility of the virus and vaccine efficacy as new evidence emerges.

For each day since the epidemic started the model works out the probability of where each person is – at home, going out, in hospital or isolating.  At the same time, it works out for each of us the probability of being infected, infectious, immune, vaccinated or still susceptible.  As some people are infected but have no symptoms it works out if we are feeling well, have symptoms, have severe covid or are dead.  Finally, it works out how many people are tested and their results.  Our location and vaccine status affects how many people we meet who might infect us; being infectious or isolating affects whether we pass on the infection; our clinical state determines our chance of survival; our diagnostic status determines if we seek help or isolate.  The model works out how each state interacts with each other.  The model is complex but so is the way we respond to the epidemic.

Is the model any good?  It is different from the unidimensional standard SEIR (Susceptible Exposed Infectious Removed) models used by the research groups providing predictions for SAGE.  For them the most likely predictions of mitigated responses — i.e., what is likely to happen — are more optimistic than worst-case projections of unmitigated responses — i.e., what could happen.  The DCM results lie somewhere between the two types of responses.  DCM allows an interplay between the various effects of behaviour, epidemiology and seasonality that are key to the control of the epidemic.  For instance, the non-mandatory response to an increase in Covid-19 prevalence is one of the factors used in the model.  This provides insight into how individuals will respond to surges in prevalence—based upon responses to previous fluctuations.  The model is good at predicting what will happen if things carry on as before  (for details on predictive accuracy see here).

The model was used in a recent article to explore the effect of the increased ease of transmission of the Delta variant, the likely seasonal effect of the coming winter and the absence of meaningful public health measures.  Vaccine effectiveness with Delta and the curtailment of social distancing as well as the potential benefit of a successful Test & Trace scheme were also incorporated into the model.

This is what is likely to happen

The chosen parameters adjusted by the model reproduce the epidemic curve and infection sequelae experienced by the UK up to now – mobility, symptoms, test results, the R-ratio, Covid related deaths, vaccine coverage and hospital admissions.  Figure 1 shows the predicted slow reduction in the number of cases through winter and an effective reproduction number staying just below 1.  This is despite a rising transmissibility of the delta variant in winter which is moderated by the level of vaccine and post infection immunity in the community.

Figure 1 –Prevalence and reproductive ratio of the Covid-19 epidemic UK – February 2020 to October 2022

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Prevalence (blue line) is the number of infections per 100 people in the UK on each day.  Compared to previous waves the fall is prolonged due to the lack of mitigating measures.  R DCM (orange line) is the reproductive number calculated by the DCM model; it hovers just below 1 until the summer of 2022; R SPI-M (black dots) are the published estimates of the government SPI-M-O committee; R0 (purple line) is an estimate of the changing underlying transmissibility of the viruses in circulation. This estimate includes seasonality effects and rises above 5 as winter approaches.  The increase in transmissibility relates to the spread of the alpha variant towards the end of 2020 and the delta variant in the summer of 2021.  CI = 90% Bayesian credible intervals.

Will this level of infection overwhelm the NHS and how many people will get long-Covid?

The vaccines used will protect the NHS over winter despite high levels of infection.  This assumes the planned vaccine programme is fully implemented and no new variants emerge.  But already we are seeing a variant of the delta virus in about 10% of infections with a possible 10% increase in transmissibility.  Relying on vaccine alone is a high-risk strategy.  A quality Test & Trace system would provide the security needed by substantially reducing infections and their long-term consequences (Figure 2). An effective track and trace system would take three weeks to develop.

Figure 2 – projections of the UK epidemic curve – patients with acute respiratory distress requiring critical care and incidence of long-Covid.  February 2020 to October 2022

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The number of critical care beds in the UK has increased from 5900 to 6284.  The moderate stress expected before the new year (blue line) would rapidly reduce if a quality test & trace system was introduced (red line).

Booster vaccines have the perverse effect of increasing long-Covid until the spring (green line) due to the reduction in isolation of contacts in vaccinated individuals which will increase new infections.  A quality test & trace system would stop these new cases occurring (red line).

The cost of abandoning public health measures to control the epidemic on Freedom Day

If no further restrictions are imposed without an adequate Test & Trace system there are likely to be a further 21 million cases of Covid-19 in the next twelve months.  With a modest improvement in the Test & Trace system new cases would be limited to under two million.  Between Freedom Day and this time next year there are projected to be 2,000 Covid-19 related deaths, 23,000 hospital admissions and nearly three million people suffering long-covid.  This may seem a high price to pay for abandoning standard public health measures.  China has controlled the delta variant with such measures.

Table 1 – the cumulative effect of uncontrolled and controlled spread of Covid-19 in the UK – from 1st February 2020 to 19th July 2021 (Freedom Day) and 31st October 2022

Cumulative totals since 1st February 2020 19th July 2021 31st October 2022 31st October 2022
Scenario assuming T&T is 22% effective 22% effective 22% effective 50% effective
Estimated incidence 31,957,908 52,889,222 33,666,503
Deaths within 28 days of a positive PCR test 129,290 150,352 131,505
Hospital admissions 474,185 669,318 497,577
Post Covid-19 Syndrome 4,250,583 6,986,301 4,477,411
T&T= find test trace isolate and support system; PCR= polymerase chain reaction test. Post Covid-19 Syndrome definition – self reported symptoms more than 12 weeks after presumed Covid-19 infection used by Office of National Statistics.

What do these results tell us?

Despite very effective vaccines the UK can expect an extended wave of Covid-19 infections.  If other mitigating public health measures were employed to support the vaccine effects this further epidemic would be curtailed.  Simply making contact tracing effective would achieve this.

The size of the projected wave of infections provides fertile ground for new variants as witnessed by the new sub-lineage Delta variant which was designated a Variant Under Investigation (VUI) by the UK Health Security Agency on 20 October 2021 and the absence of border controls which will allow new variants from other countries to invade the UK.

The reality is that vaccination alone even with boosters will not control the epidemic.  The relaxation of mitigating public health measures carries several substantial risks. The health services may be overwhelmed, vaccine resistant variants may be created and the economic cost of huge numbers of acute and chronic cases will be high.  How long the UK population is prepared to be the guineapig remains to be seen.

Dr Cam Bowie FFPHM is a former Retired Director of Public Health for Somerset, and retired Professor of Community Health, College of Medicine, University of Malawi, Blantyre.

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About the author

Dr Cam Bowie