model_param_list_create
creates list of model parameters to be used
within equilibrium_init_create
imperial_model_param_list_create(
eta = 1/(21 * 365),
rho = 0.85,
a0 = 2920,
sigma2 = 1.67,
max_age = 100 * 365,
rA = 1/195,
rT = 0.2,
rD = 0.2,
rU = 1/110.299,
rP = 1/15,
dE = 12,
delayGam = 12.5,
cD = 0.0676909,
cT = 0.322 * cD,
cU = 0.006203,
gamma1 = 1.82425,
d1 = 0.160527,
dID = 3650,
ID0 = 1.577533,
kD = 0.476614,
uD = 9.44512,
aD = 8001.99,
fD0 = 0.007055,
gammaD = 4.8183,
alphaA = 0.75735,
alphaU = 0.185624,
b0 = 0.590076,
b1 = 0.5,
dB = 3650,
IB0 = 43.8787,
kB = 2.15506,
uB = 7.19919,
theta0 = 0.0749886,
theta1 = 0.0001191,
iv0 = 1.09629,
kv = 2.00048,
av = 2493.41,
gammaV = 2.91282,
fvS = 0.141195,
pctMort = 0.215,
phi0 = 0.791666,
phi1 = 0.000737,
dCA = 10950,
IC0 = 18.02366,
kC = 2.36949,
uCA = 6.06349,
PM = 0.774368,
dCM = 67.6952,
dVM = 76.8365,
dVA = 30 * 365,
PVM = 0.195768,
uVA = 11.4321,
tau1 = 0.69,
tau2 = 2.31,
muF = 0.132,
nEIP = 3,
qEIP = 1/10,
Q0 = 0.92,
DY = 365,
thetaB = 0.89,
thetaI = 0.97,
r_llin = 0.56,
s_llin = 0.03,
r_irs = 0.6,
s_irs = 0,
qE = 1/3,
nE = 2,
qL = 1/7,
nL = 3,
qP = 1/1,
nP = 2,
muE = 0.05,
muL = 0.15,
muP = 0.05,
muM = 0.132,
eps = 58.9,
nu = 1/(4/24),
NH = 1000,
...
)
A named vector of all baseline parameters required by the Imperial malaria model.
This function creates all of the necessary parameters for the Imperial model. Parameters furnished by MGDrivE will be removed from this function. Adapted from: https://github.com/mrc-ide/deterministic-malaria-model/blob/master/R/model_parameters.R
A newer version of the model also includes parameters for severe disease. See: https://github.com/mrc-ide/malariasimulation for details.
Death rate for expoential population distribtuion, i.e. 1/Mean Population Age. Default = 0.0001305
Age-dependent biting parameter. Default = 0.85
Age-dependent biting parameter. Default = 2920
Variance of the log heterogeneity in biting rates. Default = 1.67
Maximum age in days. Default = 100*365
Rate of leaving asymptomatic infection. Default = 0.00512821
Rate of leaving treatment. Default = 0.2
Rate of leaving clinical disease. Default = 0.2
Rate of recovering from subpatent infection. Default = 0.00906627
Rate of leaving prophylaxis. Default = 0.06666667
Latent period of human infection. Default = 12
Lag from parasites to infectious gametocytes. Default = 12.5
Untreated disease contribution to infectiousness. Default = 0.0676909
Treated disease contribution to infectiousness. Default = 0.322 * cD
Subpatent disease contribution to infectiousness. Default = 0.006203
Parameter for infectiousness of state A. Default = 1.82425
Minimum probability due to maximum immunity. Default = 0.160527
Inverse of decay rate. Default = 3650
Scale parameter. Default = 1.577533
Shape parameter. Default = 0.476614
Duration in which immunity is not boosted. Default = 9.44512
Scale parameter relating age to immunity. Default = 8001.99
Time-scale at which immunity changes with age. Default = 0.007055
Shape parameter relating age to immunity. Default = 4.8183
PCR detection probability parameters state A. Default = 0.757
PCR detection probability parameters state U. Default = 0.186
Maximum probability due to no immunity. Default = 0.590076
Maximum relative reduction due to immunity. Default = 0.5
Inverse of decay rate. Default = 3650
Scale parameter. Default = 43.8787
Shape parameter. Default = 2.15506
Duration in which immunity is not boosted. Default = 7.19919
Maximum probability of severe infection due to no immunity. Default = 0.0749886
Maximum reduction due to to immunity. Default = 0.0001191
Scale parameter. Default = 1.09629
Shape parameter. Default = 2.00048
Age-dependent modifier. Default = 2493.41
Age-dependent modifier. Default = 2.91282
Age-dependent modifier. Default = 0.141195
Percentage of severe cases that die. Default = 0.215
Maximum probability due to no immunity. Default = 0.791666
Maximum relative reduction due to immunity. Default = 0.000737
Inverse of decay rate. Default = 10950
Scale parameter. Default = 18.02366
Shape parameter. Default = 2.36949
Duration in which immunity is not boosted. Default = 6.06349
New-born immunity relative to mother’s. Default = 0.774368
Inverse of decay rate of maternal immunity. Default = 67.6952
Inverse of decay rate. Default = 76.8365
Inverse of decay rate. Default = 30 * 365
New-born immunity to severe disease relative to mothers. Default = 0.195768
Duration in which immunity to severe disease is not boosted. Default = 11.4321
Duration of host seeking, assumed to be constant between species. Default = 0.69
Duration of mosquito resting after feed. Default = 2.31
Daily mortality of adult mosquitos. Default = 0.132
Number of Erlang-distributed EIP compartments. Default = 6
Inverse of the mean duration of the EIP. Default = 1/10 (days)
Anthrophagy probability. Default = 0.92
number of days in a year. Default = 365
proportion of bites on a person in bed. Default = 0.89
proportion of bites on a person outdoors. Default = 0.97
probability of repeating a feeding attempt due to LLINs. Default = 0.56
probability of feeding and surviving in presence of LLINs. Default = 0.03
probability of repeating a feeding attempt due to IRS. Default = 0.60
probability of feeding and surviving in presence of IRS. Default = 0
mosquito egg lifecycle parameter. Default = 1/3
mosquito egg lifecycle parameter. Default = 2
mosquito larval lifecycle parameter. Default = 1/7
mosquito larval lifecycle parameter. Default = 3
mosquito pupae lifecycle parameter. Default = 1/1
mosquito pupae lifecycle parameter. Default = 2
death rate of egg stage. Default = 0.05
death rate of larval stage. Default = 0.15
death rate of pupae stage. Default = 0.05
death rate of male adult stage. Default = 0.132
eggs laid per day. Default = 58.9
mosquito lifecycle parameter. Default = 1/(4/24
number of humans. Default = 1000
Any other parameters needed for non-standard model. If they share the same name
as any of the defined parameters model_param_list_create
will stop. You can either write
any extra parameters you like individually, e.g. model_param_list_create(extra1 = 1, extra2 = 2)
and these parameteres will appear appended to the returned list, or you can pass explicitly
the ellipsis argument as a list created before, e.g. model_param_list_create(...=list(extra1 = 1, extra2 = 2))