New Paper (Other): Potential roles of social distancing in mitigating the spread of coronavirus disease 2019 (COVID-19) in South Korea about covid19-review HOT 5 OPEN

When this gets added to the manuscript, we can use url:https://github.com/parksw3/Korea-analysis/blob/master/v1/korea.pdf as the Manubot citation. Tag me in the pull request so that I can follow up after it is merged. I'll edit manual-references.json so that the citation is correct. I tested Manubot with that PDF URL, and the metadata isn't extracted correctly.

I'll probably create a citation tag as well. That way, once this is posted somewhere formal and receives a DOI we can easily switch over.

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@hufengling, I was referring to the choice of priors used, not sure these are supported by evidence from the literature. Not the use of priors itself (I edited above to make this clear). I have no concerns about Bayesian modeling framework -- this is standard best practice.

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Hi @agitter how should this paper be cited? preprint on github; no doi afaik. Thanks!

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@alavendelm I created the manual reference in #120. Once that is merged, you can cite it as [@tag:Park2020_distancing].

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@alavendelm, regarding your last point: "Use of priors on the incubation period and generation time, is there support for these?"

This paper uses a Bayesian framework for their modeling, which allows for the mathematical integration of current data and "prior beliefs" (previous evidence) to generate a posterior distribution of the parameters they were looking to estimate (in this case, reconstructed incidence and R_t.)

In this paper, the authors use a hierarchical Bayesian framework - essentially, this provides mathematical language to say, "I have previous knowledge, but there's actually uncertainty about that previous knowledge too." This framework gives the model structure and flexibility, while allowing the data to speak. In my understanding, this is fairly common practice.

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