Vaccines, social measures and Covid19 - A European evidence-based analysis Vaccines, social measures and Covid19

  1. John R Porter

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Abstract

Background

A fully quantitative picture of national effectiveness in controlling the spread of the Covid19 virus should consider the percentage of a population vaccinated in relation to the percentage of a population as active cases.

Methods

Publicly available data from 27 European countries on nine dates in 2021. Data were (i) initial Covid19 vaccinations and (ii) Covid19 active cases, both as percentages of a country’s population. Dividing (i) by (ii) yielded a new metric, the V ratio, which can increase as (i) increase or as (ii) decreases or both. I correlated the change in V ratio with the change in R statistic in the 27 counties and nine dates.

Results

Mean European V ratio increased from January 11 2021 onwards; inverse correlation was found between V ratio and R statistic (p<0.001, r2=0.15, df=234). Initial threshold V ratio of 10-15 resulted in an R statistic of 1.0 or lower; this threshold increased to 30-40 with further vaccinations. Variation between countries in the V ratio increased with time.

Conclusion

This quantitative assessment and use of a summary data-derived threshold index showed the integrated effectiveness of vaccinations and social measures for European countries for Covid19. It established a threshold range for an R value of 1 and calculation of the number of vaccinations needed in Europe to reduce the infectivity of the virus to unity. Results can be used to quantify the relation between transmission following vaccination and social measures to control the spread of Covid19.

Summary box

‘What is already known’ in the epidemiology of the Covid19 pandemic in Europe countries is time- and country-based estimates of the R statistic as a measure of infectivity, the percentages of vaccinated persons to reduce infectivity and the number of active cases amenable to social measures. What is not known is how these three parameters interact.

What does this study add’? This study adds by invention an index (V) of percentage vaccinated population divided by percentage active cases. It then examines the corresponding V index in relation to the R statistic. It derives a range threshold V ratio for an R statistic of unity and extends this to suggest the total number of vaccines needed in Europe.

Policy implications

These results will allow policy judgements to be made on the basis of measured evidence, and not just models, of the means to reduce the Covid19 pandemic in Europe. The R statistic captures the development of the pandemic; the V ratio measures the integrated and quantified measures to reduce it. Further development of the analysis could assist in calculating the relative effectiveness of vaccination and social measures linked to a range of values of the V ratio. It can also be used as an alarm call to identify states which, even given 100% vaccination, may not reduce their R statistic below unity.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.15.21255558: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are caveats of course – the R statistic could be calculated in a more nuanced way; the number of sample countries and frequency of sampling could be increased; the study could be extended outside Europe – but I do wish to make the point that all my calculations are based on empirical and publicly available data from official sources. The only modelling involved is my calculation of R – but my calculated numbers are conservative and close to observed, for example to the UK figures - www.gov.uk/guidance/the-r-number-in-the-uk. A second caveat is that there could be an overlap between people who are active cases and people who are vaccinated – i.e. one could double count them. But is it both unlikely and also would not have much effect on the V ratio as the difference between the vaccination and active case percentages are large. So, if the active cases are 0.5% and the vaccination percentage is 5 then the V ratio is 10. If all the active cases are also in the vaccination percentage then the V ratio becomes 4.5%/0.5%, a value of nine, with little change in the V ratio. However, more nuanced calculation of the V ratio needs to take account of the demographics of different countries, whether active cases are a percentage of the total whole population or just of the population of potential active cases. However, such distinctions should not make major change to my essential message that there exists a range of V ratio values that inversely correlate with the R statistic and c...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2021.04.15.21255558v1 on medRxiv