New APPS

UPDATE: Here's a nice piece that talks about the complexities of reducing restrictions, framing the overall need in terms of keeping R0 (the number of new infections a given case leads to) from rising much above 1.

A new article in Science models our future under the new Coronavirus regime.  It is not pretty.  A few takeaways, followed by a thought on social distancing (the whole study is worth a read, because I’m cherry-picking here, and I’m not indicating anything about the modeling process, only some of the implications):

• Social distancing works, BUT when you stop it, COVID will come back. The relation between the two is complex, because effective social-distancing reduces population immunity: “We evaluated the impact of one-time social distancing efforts of varying effectiveness and duration on the peak and timing of the epidemic with and without seasonal forcing. When transmission was not subject to seasonal forcing, one-time social distancing measures reduced the epidemic peak size. Under all scenarios, there was a resurgence of infection when the simulated social distancing measures were lifted. However, longer and more stringent temporary social distancing did not always correlate with greater reductions in epidemic peak size. In the case of a 20-week period of social distancing with 60% reduction in R0, for example, the resurgence peak size was nearly the same as the peak size of the uncontrolled epidemic: the social distancing was so effective that virtually no population immunity was built. The greatest reductions in peak size come from social distancing intensity and duration that divide cases approximately equally between peaks
• You’d better hope COVID is not seasonal: “For simulations with seasonal forcing, the post-intervention resurgent peak could exceed the size of the unconstrained epidemic, both in terms of peak prevalence and in terms of total number infected. Strong social distancing maintained a high proportion of susceptible individuals in the population, leading to an intense epidemic when R0 rises in the late autumn and winter. None of the one-time interventions was effective in maintaining the prevalence of critical cases below the critical care capacity.” And: “One-time social distancing efforts may push the SARS-CoV-2 epidemic peak into the autumn, potentially exacerbating the load on critical care resources if there is increased wintertime transmissibility”

• Not surprisingly, the emergence of decent treatments can be game-changers: “Introducing a hypothetical treatment that halved the proportion of infections that required hospitalization had a similar effect as doubling critical care capacity”
• Intermittent social distancing only works with a lot of testing: “Intermittent social distancing might maintain critical care demand within current thresholds, but widespread surveillance will be required to time the distancing measures correctly and avoid overshooting critical care capacity”
• Again, better disease surveillance is not optional: “Sustained, widespread surveillance will be needed both in the short term to effectively implement intermittent social distancing measures and in the long term to assess the possibility of resurgences of SARS-CoV-2 infection, which could occur as late as 2025 even after a prolonged period of apparent elimination”
• We need that tech fix, or we’re stuck in our houses for a while: “New therapeutics, vaccines, or other interventions such as aggressive contact tracing and quarantine – impractical now in many places but more practical once case numbers have been reduced and testing scaled up – could alleviate the need for stringent social distancing to maintain control of the epidemic. In the absence of such interventions, surveillance and intermittent distancing (or sustained distancing if it is highly effective) may need to be maintained into 2022, which would present a substantial social and economic burden”
• A lot hinges on how much immunity having COVID confers on those who recover, and for how long. Learning about this is an urgent priority: “Our findings indicate key data required to know how the current SARS-CoV-2 outbreak will unfold. Most crucially, serological studies could indicate the extent of population immunity, whether immunity wanes, and at what rate. In our model, this rate is the key modulator of the total SARS-CoV-2 incidence in the coming years …. In our assessment of control measures in the initial pandemic period, we assumed that SARS-CoV-2 infection induces immunity that lasts for at least two years, but social distancing measures may need to be extended if SARS-CoV-2 immunity wanes more rapidly. In addition, if serological data reveals the existence of many undocumented asymptomatic infections that lead to immunity, less social distancing may be required.”

One point that stuck out to me is the assumptions used to model social distancing – equaling a 60% reduction in close contacts (=df those capable of causing a transmission).  If memory serves, the IHME model assumes a 75% reduction.  We need to know more about “social distancing” because there’s at least two massive gaps in our knowledge baked into those assumptions.  One is that we still don’t know exactly what it takes to transmit the virus.  It can be detected on some surfaces for days, but isn’t obviously (or not) capable of causing an infection for much of that period.  Data on how aerosolized it can be is all over the place.  Is a “close contact” simply being within six feet (12 feet?  Three feet?) of an infected person?  For how long?  It’s apparently more transmissible than the flu but less than measles, but that’s still a huge range.  In short, we don’t know a lot about what sort of viral load is sufficient to cause an infection and how you can encounter that, and knowing these will help to understand social distancing.

The second is that we really need to know, at a more granular level, what different social distancing policies do in terms of contacts.  If we know that, it may (hopefully!) be possible to establish a baseline less stringent than stay-at-home.  The question of whether to open schools falls into this category, with the added question of whether children transmit the virus.  But it might be possible to open restaurants with reduced seating but not sporting events for example.

Finally, of course, all of this needs to be understood in the context of what models can do, as Zeynep Tufekci reminds us.