For models/exercise/, it wasn't immediately clear where the scripts lay. In the README you say:

Open two_strain.py and plot_two_strain_ts.py and examine the code.

However, it's not clear where this code actually is. I'd suggest moving the exercise instructions to models/exercise/README.md and link out to the GitHub source code locations https://github.com/trvrb/sismid/blob/master/models/exercise/two_strain.py, etc...

Or just link to https://github.com/trvrb/sismid/tree/master/models/exercise near the beginning of the exercise instructions.

ICAM1 upregulated by stress response (Palmenberg)
Clades A and B (C different)

Skyline exercise needs to be moved after the introduction of Ne * tau.

Revise lecture on Wright-Fisher dynamics and selection. Include tests of selection as mentioned in #7.

https://github.com/trvrb/sismid/tree/master/selection

I'm using this space to catch all ideas at the moment, though I'm sure I'm forgetting some from our conversation. After we receive the evaluations, we can refine the list.

1. Provide groups a structured list of questions to answer. Potential questions: (i) Which parts of the immune system does the pathogen interact with? (ii) How many "strains" are there? (iii) Does the host population structure the pathogen population? How? (iv) Is the pathogen experiencing purifying, neutral, and/or positive selection? Where/How?
2. Have fewer groups so that we can have a more in-depth discussion of each pathogen.
3. Have fewer but longer work sessions for the groups.
4. Many people seemed more interested in the phylogenetic aspects of the course. Perhaps expand them. (It's not clear to me which parts of the course are least valuable.)
5. Provide more resources online, include preparatory and introductory materials, for especially eager students to glance at before the course.
6. Consider supplying slides as pdf files.

I think we decided to merge 2015 lectures on fitting and ssr into a single timeseries lecture. Trying not to recapitulate POMP and instead focus on the concepts of how timeseries of interacting (interfering) pathogens will behave.

https://github.com/trvrb/sismid/tree/master/timeseries

Hi!

Is there a way to commit changes directly to the wiki from a local repo?
I successfully cloned the wiki, added and committed the changes, but I get a permission error when trying to push the changes (while I can edit the wiki from the website GUI).

Thanks,
Matteo

Potent protection against H5N1 and H7N9 influenza via childhood hemagglutinin imprinting

Possibly in OAS serology section, possibly somewhere else?

Revise lecture on multistrain models. I don't think a lot has to happen here.

https://github.com/trvrb/sismid/tree/master/models

I'd suggest including this figure (or something like it) to visually explain SMC:

smc.pdf

See Janeway 15-7

Need to pad out lecture on immunity (more detail on systemics of innate and adaptive-immunity):

https://github.com/trvrb/sismid/tree/master/immunity

I've set up reveal.js to do slides. For an example in action, see flu introduction:

• slides (use left and right arrows to navigate and esc to zoom out)
• code

You should be able to do the same if you'd like. Though doing PDFs instead would be just fine as well.

Need to pad out introductory lecture on pathogen diversity:

https://github.com/trvrb/sismid/tree/master/pathogens

Currently have slides specific to flu. Should generally incorporate background on:

• RNA viruses
• DNA viruses
• bacteria
• parasites / other

Right now we just have Pneumococcus as the sole bacterial pathogen. I remember there being more people interested in bacteria than this. Some options:

• Bordetella pertussis --- recent evidence of antigenic drift
• Neisseria meningitidis --- multiple serotypes

@sarahCobey, do you have a favorite (or another suggestion if preferred)? I can include background.

Refine lecture on the coalescent and phylogenetics. It was previously two 90 minute sessions with one session mostly taken up by the BEAST practical. Dropping practical in favor of more interactive efforts.

https://github.com/trvrb/sismid/tree/master/sequences

I'm making a separate directory for each top-level topic in the course outline. At the moment I plan for wright-fisher, coalescent and flu for day 2.

Dear @trvrb,

This si a great course, I like it very much!

Could you please tell me how to know the antigenic phenotypes for HA segment of flu data? I have a dataset, and want to explore this, thanks.

Put together lecture on forecasting. This extrapolates from previous lectures on serology, timeseries and phylogenetics. Include both epi and evolutionary components. We have this down for mostly Sarah, but with some input from me.

https://github.com/trvrb/sismid/tree/master/forecasting

This could get moved to Day 3 if we're running out of time on Day 2. I'd like to give time at the end of Day 2 for groups to prep presentations. The forecasting lecture can be a short (30 min?) lecture.

Possible pathogens to look at, roughly sorted in order of preference / data availability:

• HIV (Trevor)
• pneumo (Sarah)
• dengue (Trevor)
• malaria (Sarah)
• enterovirus 71, including Polio (Sarah)
• rotavirus (Sarah)
• norovirus (Trevor)
• coronavirus (Trevor)
• swine flu (Trevor)
• bird flu (Trevor)
• cholera (Sarah)
• Shigella
• Typhoid
• herpes virus, EBV, HSV, etc...

Planning paper-based cartography exercise.

Hello,

I've been using the matplotlib code from your WF repo for some special cases of the WF model I've been coding. I'd like to host this on GitHub with an MIT License, but I can't find a license on your repo. Do you plan on having one? If not I'll just write something different.

I wanted to write some notes on this now while the course is still fresh. I'd propose the following:

I would take over the first lecture that would incorporate the more biological material from "competition" and from "flu". This would aim to give an overview of different sorts of pathogens, and their strategies to escape immunity. Would touch on flu, HIV, malaria, HPV, rhinoviruses, etc...

You'd follow with a biological oriented immunity lecture that would be basically the B cell lecture from day 3, but would cover T cells and adaptive immunity as well.

I feel like my weakest link was actually the BEAST exercise. A large proportion of people had done exactly this exercise the week before. And I didn't like the step-by-step nature it entails. Better to tell people it exists and they can do it on their own time. This would free up some time.

I'd propose replacing "serology" with a more general "antigenic evolution" section. I could cover serology and you could cover things like the Hensley age distribution story you talked about here.

I'm propose to end with a "synthesis" discussion / exercise where students are given timeseries, trees, antigenic maps for say EV 71 and they're supposed to come to some conclusions about what's going on. Or maybe have people break up into groups and each group studies a particular pathogen and then reports to the class. We'd supply figures for each pathogen. So everything would be interpretation rather than data gathering.

Notice also that this makes it so you don't have a completely full day 1 and I don't have a completely full day 2.

Day 1

• Session A: Biological lecture on pathogens (Trevor)
• Session B: Biological lecture on immunity (Sarah)
• Session C: Epi Models (Sarah)
• Session D: Fitting (Sarah)

Day 2

• Session A: SSR (Sarah)
• Session B: Coalescent (Trevor)
• Session C: Phylogenetics (Trevor)
• Session D: Selection (Trevor)

Day 3

• Session A: Antigenic evolution (Both)
• Session B: Synthesis (Both)

Revise lecture on serology. I don't think a lot has to happen here.

https://github.com/trvrb/sismid/tree/master/serology

I've put down "Immunity" for Day 3. I was thinking of splitting this between us where I can cover "serology", including antigenic cartography and original antigenic sin, and you can talk about B cells, covering things like VDJ recombination, affinity maturation, clonal expansion, etc... Happy to discuss this further.

Should have an exercise of synthesizing tests of selection, time series and serological data to understand evolution of a particular pathogen. Possible candidate would be enterovirus.