##### https://github.com/morgankain/RRV_HostVectorCompetence

Tip revision:

**23436d0439ee523b05b8aa913d30b244bdfee9d5**authored by**Morgan Kain**on**25 May 2021, 16:20 UTC****LICENSE added for eLife submission** Tip revision:

**23436d0** ReadMe.txt

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Code for running the model presented in: "Physiology and ecology combine to determine host and vector importance for Ross River virus and other vector-borne diseases" submitted to eLife on January, 22, 2021.
All code needed to run the model is included now. Data needed to run the model will be made public upon paper acceptance to eLife or elsewhere.
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R scripts
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0_top_level_script.R -- The first/main script to load to run the model. All other needed scripts are sourced from within this script
** The scripts are described in the order in which they appear in the analyses
1_needed_packages.R -- All required packages
2_functions.R -- Functions used at various points in the other scripts
3_ggplot_theme.R -- theme for cleaner ggplots
4_parameters.R -- Define the values for the free parameters in the model
5_data.R -- Load and clean all required data files
6_real_data.R -- Wrapper to source all of the Statistical sub-model scripts
7_data.titer.R -- Statistical sub-model and predictions for mosquito survival (same = no variation among species)
8_data.hm.R -- Statistical sub-model and predictions for mosquito infection probability (hm = host to mosquito)
9_data.mh.R -- Statistical sub-model and predictions for mosquito transmission probability (mh = mosquito to host)
10_cond_cov.R -- Extract the conditional modes and covariances from the random effects model for mosquito transmission
11_data.mosq_surv_same.R -- Statistical sub-model and predictions for mosquito survival (same = no variation among species)
12_data.mosq_bite_pref.R -- Statistical sub-model and predictions for mosquito feeding preferences
13_data.community.R -- Organize the statistical model output into the appropriate orientation/groupings for the
14_data.R0_setup.R -- Organize sub-model predictions for the R0 calculation
15_model_complexity_setup.R -- Set up for which components of the model uncertainty will be propagated
16_R0_calc.R -- Set up MH, HM and Calculate R0 and some of the competence metrics from all of the statistical sub-models
17_matrix_algebra_exploration.R -- Script to walk through the R0 and competence calculations from the HM and MH matrices
18_host_mosq_comp_remaining.R -- Calculate the remaining components of host physiological and ecological competence that are not calculated "for free" in the main R0
19_host_competence_cleanup.R -- Clean up host competence from the pairwise transmission matrices
20_mosq_competence_cleanup.R -- Clean up mosquito competence from the pairwise transmission matrices
21_summarize_all_permuted.R -- Analysis that isn't actually presented in the manuscript, but allows for calculating the addition of all physiological and ecological components one at a time to do a form of sensitivity analysis
22_results_summary_for_plots.R -- Summarize and clean the output from the calculation scripts for remaining results and supplement figures
23_results_summary_for_plots_figure2_panels.R -- Summarize and clean the output from the calculation scripts for result figure 2 and 3 ggplots
24_manuscript_plots_fig2_panels.R -- All panels for main text figure 2 and figure 3
25_manuscript_plots.R -- Remaining manuscripts plots
26_multi_gen_predictions.R -- Run the multiple generation approximation
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Data
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mosquito_transmission.csv -- Mosquito transmission probability over time following experimental infection
host_abundance.csv -- Abundance of hosts in Brisbane
host_response.csv -- Non-human host titer response to RRV infection
host_seroprevalence.csv -- Proportion of hosts seroprevalent in Brisbane
human_titre.csv -- Human titer response to RRV infection
mosquito_abundance.csv -- Abundance of mosquitoes in Brisbane
mosquito_feeding.csv -- Blood meals of wild caught mosquitoes in Brisbane
mosquito_infection.csv -- Mosquito infection probability over dose following experimental infection
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Other files
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mosq_bite_random.stan -- Stan model for mosquito feeding preferences
```