The site package supports malariaverse users to:
- Access and download the latest country site-files 🌐 ➡️ 💻
- Translate site file information into malariasimulation parameters 🌍 ➡️ 📉
⚠️ The site package streamlines model runs for specific geographies, but it also encapsulates many underlying assumptions, limitations, and uncertainties. Mis-specifying inputs or misinterpreting outputs from the complex malariasimulation model remains very possible. We strongly recommend consulting a member of the Imperial College modelling team before using these results for science, policy or decision-making purposes.
While every effort has been made to ensure the reliability of the package and its outputs, the authors, contributors, and affiliated institutions accept no responsibility or liability for any errors, omissions, or consequences arising from their use. All results should be interpreted with caution and professional judgement.
Email: malariaverse@imperial.ac.uk
The site-file
The site-file is the file storing all of the sub nationally disaggregated information for a country. Components of the site-file include:
- The Metadata, with high level information about the country and site-file version.
- Historical Epidemiological Data with estimates of cases, deaths and parasite prevalence.
- Population and Demography information.
- Estimates of the Historical Intervention Use in the country.
- Rainfalll and Seasonality data.
- Information on the Mosquito Vectors
Accessing and downloading site-files
Please see this detailed guide for information on how to gain access and download site files.
Translating site-file information to malariasimulation parameters
If we have access a site file, then all we need to do to run the model is
- Isolate a single site, this is a single sub-national unit within the country
- Create the parameter list
- Pass that to malariasimulation to run the simulation
# Pull information for a single sub-national unit from the site-file
site <- subset_site(
site = example_site,
site_filter = data.frame(
country = "Burkina Faso",
iso3c = "BFA",
name_1 = "Sahel",
urban_rural = "rural")
)
# Convert site information to malariasimulation parameters
site_par <- site_parameters(
interventions = site$interventions,
demography = site$demography,
vectors = site$vectors$vector_species,
seasonality = site$seasonality$seasonality_parameters,
eir = site$eir$eir,
overrides = list(
human_population = 1000
)
)
# Run the model!
site_sim <- malariasimulation::run_simulation(
timesteps = site_par$timesteps,
parameters = site_par
)