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Early sensitive indicators of COVID-19 harm mitigation can detect vaccination impact in the New South Wales outbreak

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(The health metric data for this post will be updated as new health reports are published and the commentary will be revised if trends change.)

Revised 7/09/2021 

Key points

Comparing all infections before and after 16 June 2021, there has been a clear shift in the frequency profile of infection from older people to younger age groups, indicating rising vaccine induced immunity in the elderly is having impact in the community

Statistical indicator ratios for disease severity (eg weekly hospitalisations/weekly case numbers) appear to be improving, fitting with (marginally) better protection against severe harm of the most vulnerable groups over time being achieved by a targeted immunisation program. Further scrutiny may confirm these trends, although this may takes some weeks of monitoring.

Springtime in Australia. The first green shots of vaccination impact are here

The Pundit has been searching for indicators that the New South Wales Covid-19 outbreak causing so much anguish in Sydney is at least turning the corner by showing some moderation in health damage.

Gladys Berejiklian, the Premier of New South Wales,  has been repeatedly arguing that infection case numbers themselves are not the most important indicator of the status of the epidemic.

Premier Berejiklian definitely has a point. Many infections do not to cause obvious harm and it’s the minor fraction of patients with severe symptoms who are the main cause for worry. Metrics about the most severely threatened patients are clearly more important than total case numbers.

That’s what this post is about– measures of severe infection outcomes such as mortality rates  or numbers of patients needing to be admitted to an intensive care unit in an hospital.

These relevant numbers are available but only mortality figures are issued at press conferences each day, and the form in which information about intensive care unit numbers are presented in recent press releases is not all that useful for answering the questions being considered in this post. 

On the last weeks of August 2021 detailed comparisons of age profile of infection before and after the major 2021 Greater Sydney COVID-19 Delta variant outbreak became available as infection age-profile graphs in NSW government weekly surveillance reports.

The most recent of these is below (ending 21 August 2021, week 33 of the epidemiology year).

It shows the proportions of COVID-19 infections in different age groups. The black line is a reference value based on known age distribution of age from the census. If the observed infection proportions (red and blue bars) match this profile, then all matching age groups are equally susceptible to infection.

For the outbreak starting 16th June 2021, which is almost exclusively caused by a Delta variant strain of the virus it is clear that the age-groups older than 40 years are less frequently infected than expected. These include the most heavily vaccinated age groups who were given high priority in the vaccination program.

In contrast, in this same post 16 June outbreak period, people in the age range 10 to 39 were more likely to be infected than expected from their numbers in the population and assuming equal infection susceptibility represented by the black line.

The pattern of infection was markedly different before the July 16 outbreak (lower part of graph).

In the earlier period, overall, larger proportions of older people were infected than were infected during later period, and conversely there were decreased proportions of younger people getting infected. 

Its this contrast of patterns in the two time periods that’s strong evidence vaccination is having a preventative effect on infections. 

More people in younger age categories are getting infected, and fewer older people are getting infected in the latest wave, which is in some ways good because the young are less likely to suffer severe consequences of disease. This has already been widely noted .

This discover by NSW public health workers cheers the Pundit up in a time of universal gloom. 

It has provides the motivation to explore other indicators that favourable health outcomes are continuing  to improve over time, which is a work in progress at the moment. Any progress will be reported in updates below.

But first, a little explanation about the choice of statistical measure need to track this anticipated progress.

Capturing benefits of vaccination from health statistics.

There are two types of epidemic control health interventions taking place in Sydney:

  1. Limiting social interactions to prevent transmission and 
  2. A rapidly accelerating vaccination campaign to improve immunity to bad COVID-19 disease.

Immunisation is currently giving around 66% first dose protection for eligible participants in New South Wales. Protection is even higher in the most vulnerable older age-groups. This should be enough to ensure measurable health improvement trends over the coming days and weeks. The issue being tackled here is how to spot them.

The frequent emphasis on epidemic case numbers is understandable, but case numbers themselves are not the most sensitive and early measure of vaccination impact.

Vaccination protection gives most effect to the most severe medical conditions, namely death, admission to intensive care units or hospitalisation. Protection by vaccines against infection, especially with infection by the Delta SARS CoV2 variant causing the Sydney outbreak is less dramatic than protection against severe outcomes of disease such as hospitalisation.

A recent report by Antonelli and colleagues September 2021 Lancet Infectious Diseases  shows what to expect in terms of COVID-19 disease characteristics in either vaccinated or unvaccinated individuals,

Here is graphic from that report:

The odds ratio used here is a number indicating how different the group of infected previously vaccinated people in the study were from those getting infected who had not been vaccinated. An odds ratio =1.0 means no difference between vaccinated and unvaccinated people in patter of disease. The study found that there were distinct differences.

The low odds ratios for hospitalisation mean that vaccinated people were much less likely to go to hospital if they get infected as compared to unvaccinated people.

Conversely, coronavirus infections in vaccinated people were more likely to be symptom free than infections of unvaccinated people (odds ratio above 1).

Thus vaccination should improve the ratio of hospitalised numbers / non hospitalised numbers over time during a period in which vaccination coverage in improving.

A work in progress: Tracking the odds of good health in New South Wales.

For the purposes of this current blog posting, evidence like that in the UK just mentioned is taken as a starting point exploring statistics such as likelihood of hospitalisation as indicators of actual effective outcomes in the ongoing NSW Delta variant outbreak.

Useful metrics being considered are deaths per week, new ICU admissions each week, new hospitalisations, and new total cases (infections) and their relative values (eg ODDS of hospitalisation each week/ given you are diagnosed as infected that week).

The graph below shows the progression of a favourable health outcome odds ratio over time for the New South Wales outbreak , and is followed by a table of weekly event counts on which those odds were calculated, taken from weekly government reports.

The trend in odds ratio for staying away hospital and for staying away from the ICU if testing COVID-19 positive in Sydney appears to be improving.

The Pundit reckons its worth betting on vaccination at those odds.

So Punters, get vaccinated please.

Further information

Michela Antonelli, PhD Rose S Penfold, BMBCh Jordi Merino, PhD Carole H Sudre, PhD Erika Molteni, PhD Sarah Berry, PhD et al. 2021. Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study Lancet Infectious Diseases Open Access Published:September 01, 2021 DOI:


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