add reference paper for the reproduction number calculation #151
Conversation
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@joshwlambert few points
would you be able to do this? Willing to see how you are storing references.
I am open to discussing this further. I am able to add a line that suits the best if appropriate. |
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@avallecam I'm happy to add the reference to the bibliography. Please feel free to add information to the "Warning..." paragraph if you think it will be informative for users. It's worth adding it as we can always revert to the current commit if we decide not to include it. I'll let you add the text to the README first and then I'll add the reference. |
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hi @joshwlambert, welcome back, and thank you for your patience! I just finished the paragraph content. This is ready for your review and to add the reference paper for |
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Thanks for the contribution @avallecam. It's always good to reference epi literature/theory in the packages.
However, in looking through this again I'm not uncertain about whether the descriptions of Bjornstad et al. directly correspond to the individual-based simulation used in {simulist} (see in-text comments).
@jamesmbaazam given your experience with epidemic modelling and branching processes, would you mind taking a look at this PR and letting us know whether the descriptions added to the README and the code are correct?
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| To simulate a line list for COVID-19 with an Poisson contact distribution with a mean number of contacts of 2 and a probability of infection per contact of 0.5, we use the `sim_linelist()` function. The mean number of contacts and probability of infection determine the outbreak reproduction number, if the resulting reproduction number is around one it means we will likely get a reasonably sized outbreak (10 - 1,000 cases, varying due to the stochastic simulation). | |||
| To simulate a line list for COVID-19 with a Poisson contact distribution with a mean number of contacts of 2 per day and a probability of infection per contact of 0.5, we use the `sim_linelist()` function. As outlined in @bjornstad2020a, the contact rate ($k$) and probability of infection on contact ($\pi$) are combined into a transmission rate that, multiplied by the infectious period ($1/\gamma$), determines the outbreak reproduction number ($R_o$). If the resulting reproduction number is around one it means we will likely get a reasonably sized outbreak (10 - 1,000 cases, varying due to the stochastic simulation). | |||
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I think the addition of "per day" is incorrect, the contact distribution is independent of time, and only defines the number of contacts per case. It is the infectious period that defines the temporal aspect of transmission.
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As outlined in @bjornstad2020a, the contact rate (
$k$ )
I'm now wondering if in fact the sim_linelist() model is not parameterised slightly differently from the description given here and in Bjornstad et al. Related to the above comment, the contact_distribution is not a rate and therefore I'm don't think it is equivalent to
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Perhaps the fact that infectious_period is uniformly sampled in {simulist} mean that both processes give the same result (making an assumption about large sample sizes).
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Thanks for tagging. I'll take a closer look tomorrow. |
NEWS.mdFix #139
README paragraph Quick start section relates contact distribution and probability of infection for the Ro calculation. We can add a reference to this relationship.
This proposes to add complementary text to the README to refer to the equation relating
contact_distribution,prob_infectionandinfectious_periodelements to calculate Ro, using as reference a paper cited in {epidemics} https://www.nature.com/articles/s41592-020-0822-zNo
This still requires adding the reference to the paper: https://www.nature.com/articles/s41592-020-0822-z to make
@bjornstad2020awork. This can reuse content in https://github.com/epiverse-trace/epidemics/I wanted to include the
infectious_periodobject to theWarning: ...paragraph, but not sure how to phrase it or if it would be appropriate given the emphasis oncontact_distributionandprob_infection. So open for your assessment.