ramp.models

Models for the epidemiology, spatial transmission dynamics, and control of malaria and other mosquito-borne pathogens

Install ramp.xds

To install the latest version of ramp.xds from GitHub, run the following lines of code in an R session.

library(devtools)
devtools::install_github("dd-harp/ramp.xds")

Some models use modules found in ramp.library

devtools::install_github("dd-harp/ramp.library")

Finally, install this package:

devtools::install_github("dd-harp/ramp.models")

Also see the vignette Model Building

What is RAMP?

ramp.xds was developed to support RAMP.

RAMP – Robust Analytics for Malaria Policy – describes bespoke inferential systems for malaria decision support and adaptive malaria control that go to great lengths to characterize, quantify, and propagate uncertainty. RAMP includes conventional analysis and simulation-based analytics.

A Software Ecosystem for RAMP and Malaria Research

ramp.models is part of a suite of R packages developed to support RAMP:

  • ramp.xds is the core computational engine for simulation-based analytics. It includes a basic set of models – enough to design, verify, and demonstrate the basic features of modular software.

  • ramp.library is an extended library of stable code that has been tested and verified. It includes a large set of model families published in peer review that are not included in ramp.xds The ability to reuse code reduces the costs of replicating studies. Through this library, ramp.xds also supports nimble model building and analytics for other mosquito-borne pathogens.

  • ramp.work includes algorithms to apply the framework, include code to fit models to data and to do constrained optimization

  • ramp.models includes a large set of models illustrating capabilities of ramp.xds

  • ramp.falciparum takes a deep dive into human infections with Plasmodium falciparum, from exposure and infection through parasite densities and detection, immunity, disease, and infectiousness using a probabilistic approach ramp.falciparum

  • ramp.micro is a set of tools for analyzing malaria micro-epidemiology and mosquito micro-ecology

One of our goals in developing RAMP was to have a reusable code base, so for awhile, we became the mathematical equivalent of a chop shop (i.e. the kind that backstops car thieves). To get started, we wanted to develop a framework for nimble model building that was modular, flexible, and extensible.