Carter came across James Reason's work in human failures and complex systems when he worked on patient safety at the Dept of Veterans Affairs.
Swiss cheese was a good way to explain the power of early coordinated NPIs in a pandemic, which was called "community mitigation." 2/
Community mitigation came out of @DrRHatchett's work to understand the impact of combined NPIs. In 2006 Richard commissioned NIH-funded MIDAS modelers (3 groups) to model NPIs at different points in time. 3/
Community mitigation was a major focus of the US Government's pandemic planning in 2006-7. The community mitigation strategy was published in 2007 along with the now-famous "flattening the curve" graphic. stacks.cdc.gov/view/cdc/11425 4/
Community mitigation was just one part of a comprehensive pandemic influenza strategy and implementation plan issued in 2006 with over 300 actions for departments & agencies across the US Government. cdc.gov/flu/pandemic-r… 5/
It's great to see the Swiss cheese model come to life through @MackayIM's illustration. It's opening people's eyes and helping them understand the power of combined imperfect interventions to slow the spread of a pandemic, just as it did 14 years ago. 6/
It is not a simple undertaking to establish a human challenge model, particularly with a novel virus for which the pathophysiology is not well-understood and where a targeted therapeutic is not available for what could be a lethal disease. 2/
Safety is obviously a major issue to be worked out, and this is tightly linked to ethical considerations. Beyond this, it takes time to determine the baseline infection/disease parameters that you hope to modify with the vaccine. 3/ thelancet.com/journals/lanin…
@bnallamo Fair question. Here are a few thoughts from a non-regulator. First, @US_FDA, led by Peter Marks and Operations Warp Speed, led by Moncef Slaoui, recognize that every day matters for HCWs and high-risk groups and are moving with extraordinary speed. 1/
@bnallamo@US_FDA An EUA (Emergency Use Authorization) for a vaccine is not the same as a therapeutic, given that the vaccine is being given to subgroups of people who are “healthy” and may or may not be exposed to the virus. The bar for safety & efficacy data is therefore higher than for Rx. 2/
@bnallamo@US_FDA The dataset is very large (44K participants), and thorough analyses of safety & efficacy take time. Moreover, the studies aren’t powered to conclude efficacy in the subgroups being considered for EUA, yet convincing benefit-risk assessments for those groups need to be shown. 3/
THREAD
In light of the Pfizer #vaccine news, a natural question is whether it's feasible to develop “better” #COVID19 vaccines after the first ones are approved?
The answer is yes. It can be complicated but there are ways to do it. 1/
First let’s break this down into three questions:
▪️ Why might we want better vaccines?
▪️ Why would it be hard to study new vaccines?
▪️ What are the options for doing this? 2/
WHY MIGHT WE WANT BETTER VACCINES?
After we’ve seen full Phase 3 datasets on the first vaccines, we may desire better efficacy in certain populations, longer protection, greater impact on transmission, improved dosing schedule, or an improved safety profile. 3/
First, it shows vaccines *can* prevent COVID illness in humans, and it validates the spike protein target. We didn't know these things before today, and it's good news for all #COVID19 vaccines in development. 1/
Second, the early efficacy is quite high, although it may wane over time. We can't say anything about duration of protection yet, but it helps to start from a high level of efficacy. Higher efficacy reduces the uptake needed to significantly dampen virus transmission. 2/
To be clear, it's not impossible, and OWS surely has assumptions to support this. And yes we must be ambitious.
But many will assume and/or communicate that these *targets* are what they can *expect* to happen, when there are many unknowns and execution risks. 1/
A few big ones: (1) we don't have *any* efficacy data, incl in elderly; (2) manufacturing scale-up is complex and delays very common; (3) first-time cold-chain, distribution and logistics; and (4) presumably more than one vaccine needs to succeed for this to happen; etc. 2/
Yes the first COVID vaccines will face challenges, but the overall situation is quite promising. Thread.
First, we can’t predict how good the first vaccines will be - we need Phase 3 data. We shouldn’t assume they will be very effective, poorly-effective, or “so-so.” 1/
It's true that some "second wave" vaccines will be better, because they're intended to address gaps, but that doesn't mean the first vaccines won't be good.
Second, don't underestimate complexity of aligning multiple Phase 3 vaccine programs around a single master protocol. 2/
This would have delayed the Phase 3 trials, with a human cost. It's not just about companies aligning with each other and regulators - it requires rigorous matching of the placebo arm with multiple vaccine arms to avoid reaching the wrong conclusions about efficacy. 3/