AMRSpreadModel is an R package designed to simulate the spread of malaria with a focus on antimalarial resistance. This package allows users to model the impact of different treatment rates, infection rates, and other parameters on malaria prevalence and resistance.
You can install the development version of AMRSpreadModel from GitHub:
install.packages("devtools")
devtools::install_github("ChaokunHong/MalariaResistSim")
To create a malaria model, use the create_model function. You need to specify various initial conditions and parameters for the model.
library(AMRSpreadModel)
params <- list(
S0 = 0.9, Ds0 = 0.05, As0 = 0.025, Ts0 = 0.0125,
DR0 = 0.005, AR0 = 0.0025, TR0 = 0.001,
a = 0.3, b_h = 0.1, m = 0.7, Phi = 0.7,
fT = 0.2, rD = 0.05, rA = 0.03, rTs = 0.02,
rTR = 0.01, Sv0 = 0.9, Ev_s0 = 0, Iv_s0 = 0,
Ev_r0 = 0, Iv_r0 = 0,
e = 0.1, mu = 0.1, n = 10,
Lambda_v_s = 0.005, Lambda_v_r = 0.003,
EIR_s = NULL, EIR_R = NULL
)
results <- create_model(params)
# Run the model for 500 time steps
model_output <- results$model$run(0:500)
print(model_output)
print(results$FOI)
print(results$EIR_s)
print(results$EIR_R)
print(results$Prevalence)
print(results$Prevalence_R)
You can also run the model over a range of treatment rates (fT) and entomological inoculation rates (EIR_s and EIR_R).
fT_range <- seq(0.1, 0.9, by = 0.1)
EIR_s_range <- seq(10, 200, by = 10)
EIR_R_range <- rep(0, length(EIR_s_range))
params <- list(
S0 = 0.9, Ds0 = 0.05, As0 = 0.025, Ts0 = 0.0125,
DR0 = 0.005, AR0 = 0.0025, TR0 = 0.001,
b_h = 0.1, Phi = 0.7,
rD = 0.05, rA = 0.03, rTs = 0.02, rTR = 0.01,
Sv0 = 0.9, Ev_s0 = 0, Iv_s0 = 0, Ev_r0 = 0, Iv_r0 = 0,
e = 0.1, mu = 0.1, n = 10, Lambda_v_s = 0.005, Lambda_v_r = 0
)
results <- run_model_for_ranges(fT_range, EIR_s_range, EIR_R_range, params)
print(results)
Contributions are welcome! Please open an issue or submit a pull request on GitHub.
This package is licensed under the MIT License.