ramp.control - Disease Control for ramp.xds
ramp.control is a code library that extends ramp.xds. It aims to hold a comprehensive set of published disease control models and algorithms with code that has been verified and tested.
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")To install the latest version of ramp.control from Github, run the following line in an R session:
devtools::install_github("dd-harp/ramp.control")RAMP – Robust Analytics for Malaria Policy – is a bespoke inferential system for malaria decision support and adaptive malaria control. A core goal for RAMP is to characterize, quantify, and propagate uncertainty in conventional analysis and through simulation-based analytics.
ramp.xds?
ramp.xds is an R software package that supports nimble model building for simulation-based analytics and malaria research. It was designed to help research scientists and policy analysts set up, analyze, solve, and apply dynamical systems models describing the epidemiology, spatial transmission dynamics, and control of malaria and other mosquito-transmitted pathogens. The software also supports nimble model building and analysis for mosquito ecology, with the capability to handle forcing by weather and other exogenous variables.
The software was designed around a rigorous mathematical framework for modular model building, described in Spatial Dynamics of Malaria Transmission (Wu SL, et al. 2023. PLoS Computational Biology)1. The mathematical framework has now been extended to cover exogenous forcing by weather and vector control.
ramp.control?
ramp.control is a code library with models of vector control that can be used by ramp.xds. These packages are 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.control is a collection of disease control models for ramp.xds
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.library is under active development.
ramp.library This package – ramp.library – contains reusable code that has been rigorously tested and that implements a large number of dynamical model families and other algorithms taken from the literature describing malaria and other mosquito-transmitted pathogens (see Reiner, et al. 2013)2. The supporting code was designed to be modular, and plug-and-play. The modular design makes it possible to break down published models to serve as the dynamical components in new models for malaria.
Wu SL, Henry JM, Citron DT, Mbabazi Ssebuliba D, Nakakawa Nsumba J, Sánchez C. HM, et al. (2023) Spatial dynamics of malaria transmission. PLoS Comput Biol 19(6): e1010684. https://doi.org/10.1371/journal.pcbi.1010684↩︎
Reiner RC Jr, Perkins TA, Barker CM, Niu T, Chaves LF, Ellis AM, et al. A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970-2010. J R Soc Interface. 2013;10: 20120921.↩︎