[Linkpost] - Mitigation versus Supression for COVID-19

post by alexrjl · 2020-03-16T21:01:28.273Z · score: 9 (6 votes) · EA · GW · 4 comments

This is a linkpost for a paper put out today by the Imperial College "COVID-19 response team", which I thought might provoke interesting discussion. The paper is entitled:

Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand

A summary, copied from the paper, is below:

The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission.
Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option.
We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.

4 comments

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comment by UriKatz · 2020-03-17T15:30:30.525Z · score: 3 (2 votes) · EA(p) · GW(p)

I know there is a death toll associated with economic recessions. Basically, people get poorer and that results in worse mental and physical healthcare. Are there any studies weighing those numbers against these interventions? Seems like a classic QALY problem to me, but I am an amateur in any of the relevant fields.

Also, people keep suggesting to quarantine everyone above 50 or 60 and let everyone else catch the virus to create herd immunity. Is there any scientific validity behind such a course of action? Is it off the table simply because the ”agism” of the virus is only assumed at this point?

comment by Tsunayoshi · 2020-03-17T22:45:45.500Z · score: 3 (3 votes) · EA(p) · GW(p)

Not an expert myself, but the naive calculations that I have seen with regards to herd immunity are incorrect. The precise numbers are just to illustrate the thought process.

"We need 60-70% of people to be immune, people 65 and younger make up 65 % percent of the population, so if they catch it we have achieved herd immunity to protect the elderly".

The flaw with that reasoning is that the immune people need to be essentially randomly distributed in the population. However, the elderly make up a sub population with their own distinct networks, in which the virus can spread after the quarantines are lifted.

It also would probably not work in much (probably the larger part) of the world, where the elderly live together with their families, unless one would relocate them to special made quarantines.

comment by Aaron Gertler (aarongertler) · 2020-03-17T00:19:50.346Z · score: 3 (2 votes) · EA(p) · GW(p)

Thanks for posting!

I don't know the context of research that happened before this. Were there any major surprises from this modeling? Did some reputable scientists/agencies think that a single intervention was likely to be sufficient?

comment by Cornelius · 2020-03-18T18:52:18.487Z · score: 1 (1 votes) · EA(p) · GW(p)

Worth pointing out some academics think the parameters used in the Imperial model was too negative based on real world data we have. See Bill Gates's take on it:

Fortunately it appears the parameters used in that model were too negative. The experience in China is the most critical data we have. They did their "shut down" and were able to reduce the number of cases. They are testing widely so they see rebounds immediately and so far there have not been a lot. They avoided widespread infection. The Imperial model does not match this experience. Models are only as good as the assumptions put into them. People are working on models that match what we are seeing more closely and they will become a key tool. A group called Institute for Disease Modelling that I fund is one of the groups working with others on this. ~ Bill Gates from his Reddit AMA