Early data on COVID-19 vaccine effectiveness in England

Results from the SIREN study published yesterday bring us some much-needed good news: the Pfizer/BioNTech vaccine is very effective in preventing symptomatic and asymptomatic SARS-CoV-2 infection in healthcare workers!

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SARS-CoV-2 variant: an update

PHE have published a rapid epidemiological comparison of the SARS-CoV-2 variant (VOC 202012/01 aka B1.1.7) with ‘wild-type’ SARS-Cov-2 in this country. Most of the characteristics don’t look to be different – the variant is not associated with more hospitalizations or an increase in 28-day mortality. However, there does seem to be an increase in secondary attack rates of the variant compared with wild-type SARS-CoV-2.

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The new COVID-19 variant: a primer

Unless you have been living under a rock, you’ll have seen that there’s a new COVID-19 variant on the scene. This block summarises the key information that has emerged so far about this new variant. It seems to be more transmissible, no more virulent, and there’s no evidence that the vaccines that are approved or nearly approved will be less effective against the variant.

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Secondary attack rate of COVID-19 in different settings: review and meta-analysis

A rather beautiful review and meta-analysis by colleagues at Imperial College London examines the evidence around the secondary attack rate (SAR) for SARS-CoV-2 in various settings, highlighting the risk of prolonged contact in homes as the highest risk for transmission.

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The impact of a ward-based ‘PPE Helper’ programme on staff perceptions about COVID-19 PPE

During the first wave of COVID-19, we developed a ‘PPE Helper’ programme. This ward-based programme put PPE experts on the front line to spend time with staff to improve PPE knowledge, promote safe and effective use, and address staff anxiety. The programme was evaluated through a survey of staff views about PPE at the conclusion of the programme. This found that staff who had had contact with a PPE helper responded more positivity to questions about PPE and felt less PPE-related anxiety too.

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Antimicrobial copper surfaces and linen and healthcare-associated infection: a review and meta-analysis

A helpful new review and meta-analysis asks whether treating hard surfaces or linen reduces healthcare-associated infections. The review identified only a small number of studies that had both a copper-related intervention related to surfaces and/or linen and an outcome related to HCAI. But the meta-analysis of the seven studies found that, overall, the risk of HCAI was reduced by 27% (risk ratio 0.73, 95% confidence interval 0.57–0.94).

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SARS-CoV-2 incubation period: where does the 14 days come from?

If you’ve had to self-isolate for 14 days following a possible exposure to somebody with COVID-19, you’ll relate to just how long it feels. Towards the start of the pandemic, the Otter family entered a 14 day household self-isolation due to COVID-like symptoms in the pups. At that time, mass testing was not available and so we’re left hanging to this day as to where or not it was or wasn’t. But where does the 14 days come from? And how does the probability of developing COVID-19 following exposure change over time? I was asked this yesterday, and came across a very hand review and meta-analysis of studies related to the SARS-CoV-2 incubation period.

The review includes, published in BMJ Open, includes nine studies in the meta-analysis. Overall, the median incubation period was 5.1 days, and the 95% percentile was 11.7 days (see the Figure below). The team recognise that things will change as new studies come along, so helpfully have published an R Shiny app that will be updated as new data is published. Quite a clever trick, although the Shiny app isn’t the most intuitive.

Figure: How the probability of developing COVID-19 changes over time following exposure.

In answer to your specific question about the difference in risk on day 10 vs. day 14 following exposure, this is tricky and will depend on a number of factors. However, the risk of developing COVID from the point of exposure changes over the 14 days peaking around day 4/5. I’ve attached a systematic review and meta-analysis of the COVID incubation period. Figure 5 is probably most helpful, which shows from the meta-analysis of 8 studies that approx. 90% of individuals who would eventually test positive had tested positive by day 10, whereas >95% had tested positive by day 14.

International guidelines recommend an isolation period of 14 days following patient or staff exposure to COVID-19 (see PHE and CDC). So why 14 days? And not 13 or 16? As you can see, the odd person developed COVID-19 outside of the 14 day window since exposure, but this is uncommon. And I think there’s something pragmatic about 14 days being 2 weeks!

Preventing healthcare-associated COVID-19

The issue of preventing healthcare-associated COVID-19 is very topical right now, to say the least (see this JAMA commentary), so now is a really good time to review what happened in our hospitals during the ‘first wave’ to help us prevent hospital transmission during the second.

The study was performed during the first wave of COVID-19 in London, between March and mid-April. The focus of the study was on ‘hospital-onset definite healthcare-associated’ (HODHA) COVID-19 infections (with a sample date >14 days from the day of admission). Overall, 58 (7.1%) of 775 symptomatic COVID-19 infections in hospitalised patients were HODHA. Key findings included:

  • Compared with community-associated COVID-19, patients with HODHA were more likely to be older, Black Asian or Minority Ethnicity (BAME), have several clinical underlying conditions (e.g. malignancy), and had an increased length of stay after COVID-19 diagnosis. Surprisingly, there was no increased risk of mortality (either 7, 14, or 30-day) or ICU admission.
  • There was an interesting analysis of the impact of a delayed positive test (where there was no positive test within 48 hours of symptom development). This occurred in about a third of HODHA cases, and was associated with an increased risk of 30-day mortality.
  • A potential source patient (a positive case on the same ward within 14 days of the positive test) was identified for 44/58 HODHA cases.
  • There was a correlation between weekly self-reported sickness absence incidence and weekly HODHA incidence.

This is a similar piece of work to our analysis of healthcare-associated COVID-19. The period of time covered was almost identical (from March to mid-April) and the number of HODHAs was very similar (62 in our study compared with 58 in this study). This seems to illustrate how indiscriminate this outbreak has been regionally – a wave of healthcare-associated COVID-19 swept through our hospitals in March/April – and our job now is to reduce the size of this wave over the winter!