Interesting paper- mitigation vs. suppression & social distancing

[bump]

Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf

This is an interesting paper, although kind of dire in its predictions.

The table at the bottom of page 5 is kind of interesting- it shows the hospitalization rates and critical care rates by age. It doesn’t really tell us anything we don’t already know, which is that over 60 years of age, the hospitalization rate really ramps up and so do the critical care and death rates.

[DSeid]

Thank you that article link. A mistake I believe they make is not considering the fact that children are, minimally, less contagious than adults. Still it is a good place to start.

I’m not sure people are aware of several of the basic points they discuss:

The aim of mitigation is to reduce the impact of an epidemic by flattening the curve, reducing peak incidence and overall deaths (Figure 2). Since the aim of mitigation is to minimise mortality, the interventions need to remain in place for as much of the epidemic period as possible. Introducing such interventions too early risks allowing transmission to return once they are lifted (if insufficient herd immunity has developed); it is therefore necessary to balance the timing of introduction with the scale of disruption imposed and the likely period over which the interventions can be maintained. In this scenario, interventions can limit transmission to the extent that little herd immunity is acquired – leading to the possibility that a second wave of infection is seen once interventions are lifted.

They presume 3 months as required for mitigation. They then modeled the efficacy of different non-pharmaceutical interventions (NPIs):

Table 3 shows the predicted relative impact on both deaths and ICU capacity of a range of single and combined NPIs interventions applied nationally in GB for a 3-month period based on triggers of between 100 and 3000 critical care cases. Conditional on that duration, the most effective combination of interventions is predicted to be a combination of case isolation, home quarantine and social distancing of those most at risk (the over 70s). Whilst the latter has relatively less impact on transmission than other age groups, reducing morbidity and mortality in the highest risk groups reduces both demand on critical care and overall mortality. In combination, this intervention strategy is predicted to reduce peak critical care demand by two thirds and halve the number of deaths.

However, this “optimal” mitigation scenario would still result in an 8-fold higher peak demand on
critical care beds over and above the available surge capacity in both GB and the US.

Stopping mass gatherings is predicted to have relatively little impact (results not shown) because the contact-time at such events is relatively small compared to the time spent at home, in schools or workplaces and in other community locations such as bars and restaurants.

So using their assumptions it is bad in any case. But there is by far the greatest gain with “a combination of case isolation, home quarantine and social distancing of those most at risk (the over 70s).”

Supression, getting R0 to below one, is possible but requires

, a combination of case isolation, social distancing of the entire population and either household quarantine or school and university closure are required (Figure 3, Table 4). Measures are assumed to be in place for a 5-month duration. Not accounting for the potential adverse effect on ICU capacity due to absenteeism, school and university closure is predicted to be more effective in achieving suppression than household quarantine. All four interventions combined are predicted to have the largest effect on transmission (Table 4). Such an intensive policy is predicted to result in a reduction in critical care requirements from a peak approximately 3 weeks after the interventions are introduced and a decline thereafter while the intervention policies remain in place. …

… Once interventions are relaxed (in the example in Figure 3, from September onwards), infections begin to rise, resulting in a predicted peak epidemic later in the year. The more successful a strategy is at temporary suppression, the larger the later epidemic is predicted to be in the absence of vaccination, due to lesser build-up of herd immunity. …

… To avoid a rebound in transmission, these policies will need to be maintained until large stocks of
vaccine are available to immunise the population – which could be 18 months or more. …

… We predict that school and university closure will have an impact on the epidemic, under the assumption that children do transmit as much as adults, even if they rarely experience severe disease …

Note Figures 2 and 4 very very carefully. The rebound after suppression is as high as the peak was with 3 months of combination of case isolation, home quarantine and social distancing of those most at risk (the over 70s) … but shifted into November and December … peak influenza season!!

They discuss an on and off again approach as well.

[MandaJo]

DSeid, do you think we should have done what the UK did (though they have backed off) and tried to maximize infections now to build herd immunity as quickly as possible.

[DSeid]

No.

But of the none great choices in their model (all theoretical mind you based on assumptions that may or may not be accurate) the combination of 3 months of combination of case isolation, home quarantine and social distancing of those most at risk (the over 70s and probably add in a few other higher risk individuals), was a BETTER long term result than the full out suppression mode, and is associated with many fewer harms (not just economic). I’d go with *that *as early as possible, aiming to stretch the curve across the summer, backfilling the time of year that hospitals have the most ability to have as much capacity as possible.

Doing the level of societal shut down we are doing, by their model anyway, only delays the same level of surge, whatever it is, into the worst time of year to have it. And at costs (health costs) that they do not address.

18 months of fairly complete societal shut down is of its own absurd level of harms. On and off again suppression efforts may be more than we can expect cooperation with.

Now my hope remains that the actual infection fatality rate (which we do not know yet) is significantly lower than what they use as an assumption … and IF kids actually are only a fraction as contagious as adults then we flatten more dramatically right there.

Still the model demonstrates how much of the benefit is gained with less harmful interventions, and the potential impact of a rebound having a still significant surge at the worse possible time to have one.

It’s a very important paper even with its limitations.
This is part of the information needed to make actually intelligent choices. There is also a desperate need for sampling of the Hubei population for serologic evidence of having had the disease to determine within some wide confidence window how many had undiagnosed infections, thus to get a better idea of infection mortality rate, and more study of infected children and their contacts to determine what their level of infectivity actually is.

To be making the decisions we are making, with their incomprehensible scale of impacts, without having collected that key information, and without this sort of modeling even using a greater variety of possible assumptions, as a high priority, is something that makes me want to bang my head against the wall.