Thread by @sfiscience

Follow this thread for coverage of our SFI Flash Workshop re: #COVID19, "After the First Wave," organized by @mikha_ehl, Cris Moore, & @svscarpino — with presentations by @meyerslab, @Caroline_OF_B, @rajivatbarnard, @glenweyl, & @sdelvall.

More info:
santafe.edu/events/after-f…

Some background from Lauren Ancel Meyers @meyerslab about the #epidemiology modeling community's efforts to produce #pandemic projections for the @CDC — first about #influenza and then, suddenly and with the models incomplete, pivoting to #COVID19:

Aggregate data from travel in and out of #Wuhan in early 2020. To infer the pace of the #epidemic, @meyerslab and colleagues used info on timing & location from first cases in other areas, travel volume to/from Wuhan, and gave an early doubling rate for #COVID19:

In 10% of Chinese cases studied by @meyerslab and colleagues, the infected started showing symptoms before those who transmitted it to them. The asymptomatic transmission of SARS-CoV2 makes #COVID19 especially difficult to contain:

How do different containment measures (#SocialDistancing, etc.) affect models about #COVID19's overwhelm of #healthcare capacity?

Epidemic models by @meyerslab (@UTAustin) help answer the question on everyone's mind: "When can we get back to life?"

Different levers & outcomes:

Using an agent-based simulation (#ABM) @sdelvall (@LosAlamosNatLab) & colleagues modeled several #influenza #pandemic scenarios.

Pictured: emergence of secondary waves based on school closures & #StayAtHome scenarios, and how temporary compliance creates susceptible populations:

Models by @sdelvall (@LosAlamosNatLab) & colleagues show that multi-component #pandemic interventions (#SchoolClosures + #StayAtHome + #Antiviral), while less than 1% of the population is infected, just may be enough to prevent a second wave of infections:

"We really need to think through different household structures and how they relate to control."
- @Caroline_OF_B (@Harvard)

Pics: The convergence of different at-risk populations, [elderly x poor], [heart disease x uninsured], [close proximity living x low hospital bed counts]:

By some metrics the economic impact of #COVID19 is already bigger than The Great Depression—including unprecedented #unemployment levels.

Impact unevenly distributed: collapsing demand for some goods/services, spiking demand for others.

@rajivatbarnard on #pandemic #economics:

A brief tour of economic strategies for weathering #COVID19: freeze-in-place, mobilize-to-transition, find-the-safe, find-the-virus.

@rajivatbarnard (@Columbia) on each approach, incl. variations in testing rollout and labor market adaptations:

Major issue raised by @CT_Bergstrom: decay of #trust in governments/scientists. Without responsible #data collection, #transparency, & #SciComm, "It's going to be extremely hard to do some sort of nuanced #SocialDistancing down the road."
- @Caroline_OF_B

santafe.edu/events/after-f…

Video is up for yesterday's flash seminar "After The First Wave," featuring talks by @meyerslab, @sdelvall, @Caroline_OF_B, @rajivatbarnard, @glenweyl on #pandemic modeling/surveillance/intervention and the secondary/tertiary economic impacts of #COVID19:

Risks for transportation of 2019 novel #coronavirus disease (#COVID19) from #Wuhan, China, before #quarantine was imposed — figure from the recent @CDC_EIDjournal paper coauthored by SFI External Prof Lauren Ancel Meyers (@meyerslab at @UTAustin):

wwwnc.cdc.gov/eid/article/26…