Scenario comparison for deterministic models

[pratikunterwegs]

This PR is WIP #221 and adds basic intervention scenario comparison functionality. The function outcomes_averted() offers options for calculating the differences in outcomes averted (cases, and deaths where applicable) between a baseline scenario (with parameter uncertainty), and multiple comparator scenarios (with identical parameter uncertainty).

• See the vignette on scenario modelling, modelling_scenarios.Rmd for how to use this.
• There's a limitation that this only works for models with parameter uncertainty. This is because the output format of a model with a single parameter set does not preserve model arguments/infection parameters which are used for matching. This in turn is because it was felt that users should be able to run a non-vectorised model and get simplified output that can be passed directly to plotting (see #176).
• There's no support for comparing scenarios where the axis of variation is an infection parameter, e.g. $R_0$ is one of 1.3, 2.0, 2.5 etc.
• Support for the Ebola model is forthcoming in a separate PR based on feedback from this one.

Happy to take feedback on the implementation here, and more general discussion on scenario comparison in #221.

[github-actions[bot]]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if a6e001e1866556521434ae4ca32ba757ee7da484 is merged into main:

• :rocket:default_ode: 10.6ms -> 10.5ms [-1.79%, -0.01%]
• :heavy_check_mark:default_ode_interventions: 97.2ms -> 95.9ms [-2.98%, +0.47%]
• :heavy_check_mark:default_ode_param_vec: 845ms -> 842ms [-1.4%, +0.76%]
• :heavy_check_mark:default_ode_paramvec_intervs: 6.19s -> 6.17s [-1.27%, +0.7%]
• :heavy_check_mark:ebola: 577ms -> 575ms [-1.44%, +0.83%] Further explanation regarding interpretation and methodology can be found in the documentation.

[github-actions[bot]]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if a6e001e1866556521434ae4ca32ba757ee7da484 is merged into main:

• :heavy_check_mark:default_ode: 10.7ms -> 10.6ms [-2.01%, +0.96%]
• :exclamation::snail:default_ode_interventions: 93.4ms -> 94.6ms [+0.02%, +2.4%]
• :heavy_check_mark:default_ode_param_vec: 819ms -> 819ms [-0.94%, +0.92%]
• :heavy_check_mark:default_ode_paramvec_intervs: 6.2s -> 6.2s [-0.65%, +0.42%]
• :heavy_check_mark:ebola: 550ms -> 549ms [-1.44%, +1.23%] Further explanation regarding interpretation and methodology can be found in the documentation.

[github-actions[bot]]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if a6e001e1866556521434ae4ca32ba757ee7da484 is merged into main:

• :heavy_check_mark:default_ode: 10.8ms -> 10.8ms [-0.48%, +1.07%]
• :heavy_check_mark:default_ode_interventions: 97.7ms -> 97.7ms [-1.02%, +1.04%]
• :exclamation::snail:default_ode_param_vec: 832ms -> 841ms [+0.14%, +1.9%]
• :heavy_check_mark:default_ode_paramvec_intervs: 6.24s -> 6.24s [-0.62%, +0.54%]
• :heavy_check_mark:ebola: 563ms -> 562ms [-1.07%, +0.56%] Further explanation regarding interpretation and methodology can be found in the documentation.

[github-actions[bot]]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if a6e001e1866556521434ae4ca32ba757ee7da484 is merged into main:

• :heavy_check_mark:default_ode: 10.8ms -> 10.8ms [-0.83%, +1.14%]
• :heavy_check_mark:default_ode_interventions: 100ms -> 100ms [-1%, +1.42%]
• :heavy_check_mark:default_ode_param_vec: 837ms -> 835ms [-0.68%, +0.39%]
• :heavy_check_mark:default_ode_paramvec_intervs: 6.24s -> 6.26s [-0.1%, +0.79%]
• :heavy_check_mark:ebola: 570ms -> 566ms [-1.57%, +0.14%] Further explanation regarding interpretation and methodology can be found in the documentation.

[pratikunterwegs]

Thanks @joshwlambert. I haven't found a good fix for the second issue, but I'm merging this now so I can move ahead with more scenario functionality.