The UK government yesterday announced a far-reaching package of social distancing measures to suppress the spread of COVID-19. These are based on some Imperial College London modelling work, published here. The model predicts that the UK approach to mitigate the impact of the UK epidemic would indeed reduce the overall number of people affected and those who die, but would still leave hundreds of thousands dead in an overwhelmed healthcare system. In contrast, a more intensive suppression approach would be effective in reversing the epidemic trend and keep the number of new cases to a low level – in the short term, at least.
I’m sure we’ve all been following the emerging story of the 2019-nCoV outbreak closely, with the third cases reported in the UK yesterday (pleased to see this is where you’d expect the UK to be based on Marc’s post earlier)! There’s been a small explosion of publications in the peer reviewed literature. I’ve chosen one slightly randomly to discuss today: a short modelling study providing some insight on the likely volume of unreported cases (very much the ice berg and not the tip!) and some sense of where this outbreak will end (it depends on how we respond, globally).
Continuing the theme of CPE (or CRE if you prefer) Toolkit evaluation, a US research group has performed a modelling study to evaluate the economic impact of the US CDC CRE Toolkit. Curiously, whilst all approaches generated cost savings eventually, hospitals acting independently rather than as a co-ordinated region resulted in faster but ultimately smaller cost savings.
“We are no more in the aerosol camp than the contact camp” conclude the authors. And this seems to be how it is in terms of influenza transmission routes – you’re either in one camp or the other. This 2010 PLoS Computational Biology paper is hardly hot off the press, but it is important and it does, to an extent, put the question of which camp you are in for influenza transmission to bed: you need to pitch your tent in different camps depending on the circumstances.
The paper describes a model to compare the various transmission routes for influenza, principally airborne, droplet and contact. The study evaluates four transmission routes: ‘respirable particles’ (<10 µm), ‘inspirable particles’ (>10 µm, <100 µm), ‘direct droplet spray’ (>100 µm) and ‘contact’. The model tests 10,000 scenarios, considering possible variation in virus properties, host susceptibility and environmental factors (such as the number of influenza shedders).
The key finding is that contact transmission had the highest average basic reproduction number (R0) (1.7) followed by droplet (0.27), respirable (0.05) and inspirable (0.006) particles (Figure). However, that is only part of the story. Of the 10,000 scenarios evaluated, contact only was associated with high transmission in 3,069, all four routes in 342 and none in 4,765. In high host density settings, all routes were more frequently important. Conversely, when self-inoculation was more common (i.e. when simulated individuals touched their simulated nose, eyes and mouths more frequently), contact transmission was more important.
Figure: Basic reproduction number (R0) of four influenza transmission routes, ‘respirable particles’ (<10 µm), ‘inspirable particles’ (>10 µm, <100 µm), ‘direct droplet spray’ (>100 µm) and ‘contact’.
The findings are interesting and probably very important. It’s a shame they were not able to evaluate the relative importance of contact transmission involving contaminated surfaces compared with contact transmission that occurs independent of surface transmission (this has been evaluated elsewhere). Also, I remain suspicious of modeling in general. If simplifying assumptions are too simplistic (which is often the case), the model spits out garbage, which is worse than useless. Put another way, Bertha can produce anything if she’s given the right inputs! Plus, it’s difficult to know how applicable these findings are to other respiratory viruses.
Still, the paper does shed light on the relative importance of influenza transmission routes. Which is most important? Well, that depends on the context. If you’re in a small room, airborne and droplet transmission is key. If you’re admitted to a room following the discharge of a patient with influenza, then contact transmission is key. Hence, we need to be flexible when considering influenza transmission routes and ‘contextualize’ our interventions accordingly.
Citation: Spicknall IH, Koopman JS, Nicas M, Pujol JM, Li S, Eisenberg JN. Informing optimal environmental influenza interventions: how the host, agent, and environment alter dominant routes of transmission. PLoS Comput Biol 2010; 6: e1000969.
Image: Sanofi Pasteur.