R packages

Modular Computation for Simulation-Based Analytics

RAMP (Robust Analytics for Malaria Policy) is an organized way of translating evidence into robust policy advice and support Adaptive Malaria Control. RAMP relies on simulation-based analytics implemented through SimBA software. Using SimBA, it is easy to develop site-specific dynamical systems models of malaria epidemiology, transmission dynamics, and control for scenario planning to support sub-national tailoring, monitoring and evaluation, and strategic planning.

SimBA

SimBA – defined narrowly – includes seven packages that support robust analytics for malaria policy.

  • ramp.xds handles core computational and analysis. It was developed to build and solve dynamical systems models for the epidemiology, transmission dynamics, and control of malaria and other mosquito-transmitted pathogens based on a well-defined mathematical framework [1].

    • all packages are ramp branded

    • xds stands for eXtensible Dynamical Systems

  • ramp.library is a supplementary model library for ramp.xds that has additional modules for the core dynamical components.

  • ramp.func is a supplementary code library for ramp.xds that holds algorithms to implement various models of malaria control, including vector control, mass vaccination, mass drug administration, etc.

  • ramp.forcing is is a supplementary code library for ramp.xds that holds algorithms to implement exogenous forcing by weather and other factors.

  • ramp.demog is is a supplementary code library for ramp.xds that handles human demography and stratification, including vital dynamics and age structure.

  • ramp.qa is a set of algorithms and functions to for qualitative analysis, including thresholds, connectivity, seasonality, and scaling relationships.

  • ramp.work is a set of algorithms and functions to fit models to data, and to apply malaria models in context.

Deep Dives

Microsimulation

Two packages have been developed by our team for behavioral state models for mosquitoes and microsimulation:

  • ramp.micro was developed to explore complexity in mosquito ecology through the development and analysis of simulation models describing mosquito behavioral & spatial dynamics on point sets representing resources, which we call micro-simulation [2,3]

  • MBITES is an individual-based simulation model developed to explore mosquito behavioral states [4].

Malaria Epidemiology

In ramp.falciparum, we explore malaria epidemiology, defined in the narrow sense to describe human exposure to malaria and infection, immunity, disease, drug taking, diagnostics and detection, and infectiousness [5].

Deprecated

ramp.xds was preceded by two packages that have since been deprecated (See Deprecated).

References

1.
Wu SL, Henry JM, Citron DT, Ssebuliba DM, Nsumba JN, C HMS, et al. Spatial dynamics of malaria transmission. PLoS Computational Biology. 2023;19: e1010684. doi:10.1371/journal.pcbi.1010684
2.
Perkins TA, Scott TW, Le Menach A, Smith DL. Heterogeneity, mixing, and the spatial scales of mosquito-borne pathogen transmission. PLoS Comput Biol. 2013;9: e1003327.
3.
Castellanos HMS, Wu SL, Henry JM, Guerra CA, Galick DS, García G, et al. Mosquito Dispersal in Context. bioRxiv; 2025. doi:10.1101/2025.03.22.642900
4.
Wu SL, Sánchez C HM, Henry JM, Citron DT, Zhang Q, Compton K, et al. Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology. PLoS Comput Biol. 2020;16: e1007446. doi:10.1371/journal.pcbi.1007446
5.
Henry JM, Carter AR, Wu SL, Smith DL. A Probabilistic Synthesis of Malaria Epidemiology: Exposure, Infection, Parasite Densities, and Detection. medRxiv; 2025. doi:10.1101/2025.03.24.25324561