I don't put too much stock in ecological modelling studies, but I understand that some others do

A new study from the USA looks at which age groups appear to drive transmission trends

It has some interesting findings


They use age specific mortality data to eliminate bias from undertesting of cases, alongside mobility and contact data

They found adults age 20 - 49 are the origins of most infections

This did not change over time, nor with school reopenings

"This study provides evidence that the resurgent COVID-19 epidemics in the US in 2020 have been driven by adults aged 20-49, and in particular adults aged 35-49, before and after school reopening."

"Unlike pandemic flu, these adults accounted after school reopening in October, 2020 for an estimated 72.2% [68.6%-75.9%] of SARS-CoV-2 infections in the US locations considered, whereas less than 5% originated from children aged 0-9 and less than 10% from teens aged 10-19."

There is a whole list of caveats, as is common to ecological modelling studies (complex questions, complex methods and complex data)

Never-the-less, the idea that these types of studies universally suggest schools are the drivers of transmission is not accurate


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More from @apsmunro

5 Feb
You may have seen this headline today

It may even have been accompanied by scary emojis ⚠️ 🚨 💥 😱

The reality is much less scary (as is the article compared to the headline)


These numbers are roughly accurate, but do not reflect anything like a comparable scenario to spring

These children are MUCH less unwell, due to a combination of recognising less severe cases, early management, and perhaps a degree of over diagnosis to be on the safe side

Only a couple of patients per day are even unwell enough to be enrolled in the worlds only clinical trial for this condition, the RECOVERY trial

Very few cases of coronary artery aneurysms, which even after spring resolved for most children over follow up

Read 4 tweets
29 Jan
I've seen suggestions that the idea younger children might be less susceptible to infection with #COVID19 is a "myth", based on children just not being tested enough

That is untrue!

Whilst it's true children are under tested, this is not where this idea came from!

It comes from household contact tracing studies

When someone in a home is identified as being infected, the other members of the house are tested to see if they are infected

It's a useful experiment as everyone at home gets very similar exposure

Some early studies did only test contacts with symptoms, but actually most large studies since then have tested ALL close contacts REGARDLESS of symptoms

Here are just a handful




Read 8 tweets
9 Jan
I think people find it hard to understand the deal with kids reduced susceptibility to #COVID19 and what it means for schools etc

I thought I’d share a little analogy which helps me conceptualise it

Let’s imagine #COVID19 is rain... 🌧

Everyone wants to stop getting wet

Adults are just dressed normally 👦

Teens have a little hat on 🧢

Younger kids have got an umbrella ☂

When there is very little rain, you won’t notice much difference between how wet everyone is

When it starts raining a bit, you’ll notice the younger kids are less wet than adults

The teens may be just as wet as they spend more time out in the rain

Read 8 tweets
3 Jan
The current issue of #schoolclosures is so complex I am loathed to add my opinion to the twitter soup

Massive uncertainties✅
High stakes✅
Huge health trade offs✅
Opposing opinions ✅
Easy answers 🚫

I'll just add a few simple thoughts

Firstly, don't be fooled by twitter

It has the most shouty and polarised opinions only, the moderates have been largely hounded out

Both public and scientific opinion is almost certainly much more nuanced and balanced than this platform would fool you into believing

Next, advocating for widespread closure is a legitimate opinion in the current environment

Massive, uncontrolled community transmission and looming hospital capacity issues, with high prevalence of infections among children (esp teens) are a bad mix

Read 9 tweets
18 Dec 20
New findings from Swiss seroprevalence and an good opportunity to learn some more infectious disease epidemiology!

A similar prevalence in children aged 6 - 18 y (23%) than the adult population (~27%)

Lower in kids <6y (~15%) and over 65y (<15%)

What can we learn?

First, another lesson in age binning for kids (will we ever learn?)

6 - 18y is a weird age bin which I would not recommend

It hides big epidemiological differences

In fact, we have seen it in related data before...

The pre print of the first study from this team used age bin 5-19 y and reported no statistically different prevalence vs adults


They changed for publication and found significantly lower prevalence in children <10y


Read 8 tweets
15 Dec 20
Here is a good lesson in basic epidemiology

This data is difficult to interpret in a number of ways:
1. There is no denominator, either of institutions or populations
2. It counts the number of outbreaks, not cases
3. It doesn't tell you who had the infections

This matters

An extreme example of why this is important from earlier this year

After lots of excitement about outbreaks in schools it turned out the median number of children involved was...


For some denominator context there are:

- 24,000 schools (9 million pupils) not inc. university
- 11,000 care homes (410,000 residents)
- 117 prisons (79,000 prisoners)
- 26,000 restaurants (many not/partially open)

We are comparing apples and oranges

Epidemiology 101

Read 5 tweets

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