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Adam Kucharski

Feb 20 • 12 tweets • 4 min read

If COVID immunity can wane, what will happen after large epidemics peak? Some thoughts on post-epidemic 'honeymoon periods'... 1/

As immunity accumulates in a population (specifically immunity that protects against becoming infected/infectious), R will decrease. When R drops below 1, the epidemic peaks and starts to decline. But what might happen next? 2/

When R drops below 1, the epidemic doesn't magically end - it will continue to cause infections (and hence immunity) as it declines, meaning that the epidemic 'overshoots' the level of immunity required to get R below 1, potentially by quite a lot. 3/

So we can end up in a situation where R drops considerably below 1 as the epidemic continues to decline. End of story, right? Not quite... 4/

We know protection against infection can wane quickly for Omicron, e.g. below for immunity against symptomatic infection following vaccination (from: gov.uk/government/pub…) 5/

We also see evidence of some drop-off (although not as sharply) in protection against hospitalisation over time: 6/

But if R has dropped considerably below 1 during an epidemic, it will take some time for susceptibility to build up to sufficient levels to see a resurgence. Can therefore see a 'honeymoon period' where infection remains at lower levels for a while first. Here's a cartoon: 7/

We can also see the honey period happen after the introduction of vaccination. The term 'honeymoon period' was first coined in the context of measles (ncbi.nlm.nih.gov/labs/pmc/artic…). In this case, new susceptibility arrives from new births rather than waning of existing responses. 8/

Below shows hypothetical dynamics after vaccination introduced with 50%, 75%, 80% coverage among infants after 4 years... 9/

Examples of a post-vaccination honeymoon period were later observed in countries ranging from BNurundi, below left (from: pubmed.ncbi.nlm.nih.gov/8194915/) to Mongolia, below right (from: pubmed.ncbi.nlm.nih.gov/17642531/). 10/

Several European countries may well have had a COVID post-vaccination honeymoon period against Alpha in early summer 2021, with vaccination + post-infection immunity driving down R. But we never saw subsequent effect of any waning, because Delta came along first. 11/

So in summary, we shouldn't assume that post-Omicron level of infection/disease is where things will stay for good. What's more, above only focuses on waning immunity (& new births in the case of measles), and new variants also likely to shape future susceptibility to COVID. 12/

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Adam Kucharski

@AdamJKucharski

Feb 4

https://twitter.com/whippletom/status/1489197128916389894

There are many problems with below study, but what's striking is how many people sharing 'lockdowns do nothing' claims unquestioningly don't seem to realise that paper at the same time concludes mandated mask wearing has a substantial effect... 1/

https://twitter.com/whippletom/status/1489197128916389894

Despite the headline claim about 'lockdown' being essentially based on a single study (because it's weighted so heavily in the estimates – see thread above), the authors note the mask result (which apparently contradicts their main conclusion) is based 'on only two studies'... 2/

'Lockdown' is one of those terms that has meant many different things to many different people during pandemic, from Wuhan-style stay at home measures to any restriction at all. Above study uses any mandatory measure to mean 'lockdown' in main analysis... 3/

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Adam Kucharski

@AdamJKucharski

Jan 18

Suggestions to include spontaneous behavioural responses to a growing epidemic as default in scenario models might sound simple and obvious, but it's worth considering the assumptions involved... 1/

What magnitude of behaviour change in response to epidemic would you assume as a baseline scenario? And how would this relate to transmission reduction? 2/

Would you assume disruptive-but-ineffective change (e.g. avoiding low risk interactions and continuing to have high risk ones) or well-targeted change (e.g. using more rapid tests effectively)? 3/

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Adam Kucharski

@AdamJKucharski

Jan 18

Below analysis was two years ago (bbc.co.uk/news/health-51…). As well as providing an early warning about the COVID threat, it’s a good illustration of what is often an under-appreciated point: if we want to make sense of epidemic data and dynamics in real-time, we need models… 1/

At the time, only 41 cases of 2019-nCoV (aka COVID-19) had been reported in Wuhan. But two exported cases had just been detected in Thailand and one in Japan. How plausible was it that there were really just 41 cases in Wuhan? 2/

To answer this, we need to outline a model: if there are X cases in Wuhan, and travellers leave to different destinations at given rates, how likely is it we'd observe those three exported cases? With this model outlined, we can then use it to infer X given the observed data. 3/

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Adam Kucharski

@AdamJKucharski

Jan 12

https://twitter.com/FraserNelson/status/1479487688973688836

Given below observation, an obvious question to ask is 'did any models consider a scenario that could give insight into what a Tier 4-like change in behaviour could look like?' 1/

https://twitter.com/FraserNelson/status/1479487688973688836

If we look at scenarios that assume a prolonged return to behaviour levels seen in earlier steps of the reopening in England (e.g. Step 0, S1, S2 etc. below from 11 Dec: cmmid.github.io/topics/covid19…), models predict far lower levels of hospitalisations and deaths. 2/

Could summarise above scenarios as: 'If you want epidemic curve to look like that, this is the sort of virus characteristics and behaviour change that would be required - whether behaviour change comes from a policy, or pin hopes on spontaneous individual-level change' 3/

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Adam Kucharski

@AdamJKucharski

Jan 10

Some thoughts on the evolutionary trajectory of SARS-CoV-2 so far, how it compares to other viruses, and what might happen next... 1/

For seasonal coronaviruses & flu, we see a pattern of 'antigenic turnover' over time - circulating viruses give rise to new variants that escape prior immunity against infection, immunity builds against these new variants, then these in turn spawn new variants... 2/

When infections evolve to escape immunity like this, we typically end up with an evolutionary tree that looks like a lopsided ladder as new variants sequentially replace their 'parent' variant lineages (below from: journals.plos.org/ploscompbiol/a…) 3/

Read 12 tweets

Adam Kucharski

@AdamJKucharski

Jan 6

Flu is often quoted as an example of 'living alongside' an infection (even though countries work hard to reduce disease burden via vaccination). But I think sexually transmitted infections are also an important example to consider... 1/

For STIs, preaching abstinence to prevent infection has gradually fallen out of favour (e.g. thelancet.com/journals/langl…). Instead, societies deal with ongoing circulation of these infections using other tools... 2/

Testing & informing partners gives people information on their infection status (and treatment can reduce duration of infectiousness). Contacts can be made less risky with protection (e.g. condoms). And susceptibility can be reduced through vaccination (or, for HIV, PrEP)... 3/