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Previous by Date: Subject: Re: [DCHAS-L] Is Swiss cheese helpful for understanding accident causation? Date: Sunday, May 2, 2021 at 4:51:19 PM Author: NEAL LANGERMAN <neal**At_Symbol_Here**CHEMICAL-SAFETY.COM> |
Next by Date: Subject: [DCHAS-L] Chemical Safety headlines (9 articles) Date: Mon, 3 May 2021 06:51:29 -0400 Author: Ralph Stuart |
> >The value of the Swiss Cheese graphic is its ability to clearly present layer of protection. Ralph does this with respect to Covid.
For what it‰??s worth, I am working on further developing this idea by scaling the size of the holes in the Covid protection model with relevant data for each level. For example,
1) Vaccinations appear to be more than 90% effective, but uptake in the population is as expected to be as low as 60%
2) Testing on our campus reaches 95% of the population and isolation of positives and their contacts is rapid and probably more than 90% effective in preventing spread from the positive case.
2) Physical distancing of at least 6 feet is well-observed in classrooms, as many of our students prefer to zoom into class.
3) Based on campus observations, mask wearing is about 90%, but, recently, as the weather warmed more people are observed wearing no masks or masks that don‰??t cover their nose (7% last week).
4) We have HEPA air cleaners deployed to poorly ventilated classroom spaces (as determined by CO2 monitoring); I am conducting field work to assess how effective these cleaners are in terms of managing potentially infectious particles.
My hope is that adding this level of detail will help upper management understand the impact of changing one of these parameters on the overall system. As we all know, there is ongoing pressure to reduce these measures; for example, the NH governor removed the state mandate for mask wearing this week. I would also note, that the swiss cheese model can be adapted into a bowtie graphic (see https://pubs.acs.org/doi/10.1016/j.jchas.2016.10.003 for one example), if you want to include factors that are part of the response to the event, such as the isolation of close contacts after a positive Covid result.
As I mentioned before, adding numerical components to these models require a lot more data that is typically available for lab scenarios. Unfortunately, we have a fair amount of both global and local data about Covid management. However, that data is not well tested, given the short duration of the pandemic and the changing nature of the virus. But I hope it can help communicate the opportunities and challenges we‰??re facing in managing recognized workplace hazards.
- Ralph
Ralph Stuart, CIH, CCHO
Environmental Safety Manager
Keene State College
603 358-2859
ralph.stuart**At_Symbol_Here**keene.edu
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