| Title: | Spatial Modeling of Infectious Diseases with Co-Variate Error |
| Version: | 1.2.1 |
| Description: | Provides tools for simulating from spatial modeling of individual level of infectious disease transmission when co-variates measured with error, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based model within Susceptible-Infectious-Removed (SIR) compartmental frameworks. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.1 |
| Imports: | MASS, corpcor, mvtnorm, ngspatial, numDeriv, stats, psych |
| Depends: | R (≥ 2.10) |
| LazyData: | true |
| NeedsCompilation: | no |
| Packaged: | 2024-07-06 14:41:34 UTC; ruwan |
| Author: | Ruwani Herath [aut, cre], Leila Amiri [ctb], Mahmoud Torabi [ctb] |
| Maintainer: | Ruwani Herath <ruwanirasanjalih@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-07-09 15:20:06 UTC |
Areal level data
Description
The data which describes the areal level data (proportion of indigenous people and population) for 25 regions.
Usage
Areal_level_data
Format
A data frame with 25 rows and 2 columns:
- Region
Region number
- Pop
Population of each region
- Ind
percentage of indigenous people in each region
...
Estimating parameters along with corresponding variances based on the proposed model.
Description
Estimating parameters along with corresponding variances based on the proposed model.
Usage
Estimation(
ITER,
MHiteration,
eps,
d,
nSample,
mm,
time,
MuxStar0,
MuxInd0,
SigmaxStar0,
SigmaxInd0,
Sigmav0,
Sigmaw0,
lambda0,
sigma0,
delta0,
alpha0,
beta10,
beta20,
beta30,
beta40,
InfPeriod,
g
)
Arguments
ITER |
The number of simulation runs |
MHiteration |
The number of iterations in Metropolis–Hastings algorithm |
eps |
Stopping value for MCECM algorithm |
d |
distance between cells |
nSample |
number of sample in each cell |
mm |
Number of areas. |
time |
Maximum time. |
MuxStar0 |
Mean of unobserved areal level covariates. |
MuxInd0 |
Mean of unobserved individual level covariates. |
SigmaxStar0 |
Variance of unobserved areal level covariates. |
SigmaxInd0 |
Variance of unobserved individual level covariates. |
Sigmav0 |
Variance of areal level measurement error variable. |
Sigmaw0 |
Variance of individual level measurement error variable. |
lambda0 |
Spatial dependency parameter. |
sigma0 |
Over dispersion parameter. |
delta0 |
The spatial parameter. |
alpha0 |
Initial value for intercept. |
beta10 |
Initial value for coefficient of observed individual level covariates. |
beta20 |
Initial value for coefficient of observed areal level covariates. |
beta30 |
Initial value for coefficient of unobserved individual level covariates. |
beta40 |
Initial value for coefficient of unobserved areal level covariates. |
InfPeriod |
The infectious period length. |
g |
grid dimension |
Value
the result of the function
Examples
Estimation(1,5,0.05,2,4,4,20,0,0,1,1,0.3,0.3,0.5,0.5,2.5,0,1,1,1,
1,3,2)
Estimating parameters along with corresponding variances based on the proposed model with real data.
Description
Estimating parameters along with corresponding variances based on the proposed model with real data.
Usage
Estimation_RealData(
ITER,
MHiteration,
eps,
mm,
time,
MuxStar0,
MuxInd0,
SigmaxStar0,
SigmaxInd0,
Sigmav0,
Sigmaw0,
lambda0,
sigma0,
delta0,
alpha0,
beta10,
beta20,
beta30,
beta40,
InfPeriod,
Di,
D,
Nlabel,
n,
cov1,
cov2,
ww,
vv,
tau
)
Arguments
ITER |
The number of simulation runs |
MHiteration |
The number of iterations in Metropolis–Hastings algorithm |
eps |
Stopping value for MCECM algorithm |
mm |
Number of areas. |
time |
Maximum time. |
MuxStar0 |
Mean vector of unobserved areal level covariates. |
MuxInd0 |
Mean vector of unobserved individual level covariates. |
SigmaxStar0 |
Variance of unobserved areal level covariates. |
SigmaxInd0 |
Variance of unobserved individual level covariates. |
Sigmav0 |
Variance of areal level measurement error variable. |
Sigmaw0 |
Variance of individual level measurement error variable. |
lambda0 |
Spatial dependency parameter. |
sigma0 |
Over dispersion parameter. |
delta0 |
The spatial parameter. |
alpha0 |
Initial value for intercept. |
beta10 |
Initial value for coefficient of observed individual level covariates. |
beta20 |
Initial value for coefficient of observed areal level covariates. |
beta30 |
Initial value for coefficient of unobserved individual level covariates. |
beta40 |
Initial value for coefficient of unobserved areal level covariates. |
InfPeriod |
The infectious period length. |
Di |
Euclidean distance between individuals |
D |
Neibourhood structure |
Nlabel |
Label for each sample from the area |
n |
Total number of individuals |
cov1 |
observed individual level covariates |
cov2 |
observed areal level covariates |
ww |
Unobserved individual level covariates |
vv |
unobserved areal level covariates |
tau |
tau |
Value
the result of the function
Examples
Estimation_RealData(1,5,0.05,4,20,0.1,0.1,0.15,0.8,0.6,0.6,0.85,
1.1,2.7,0,1,0,1,1,3,
matrix(runif(900,min = 4,max = 20),nrow=30, byrow = TRUE),
matrix(c(2,-1,-1,0,-1,2,0,-1,-1,0,2,-1,0,-1,-1,2),nrow=4,byrow=TRUE),
rep(1:4,c(7,6,8,9)),30,runif(30, 0, 1),
runif(4,0,1),runif(30,-2,2),runif(4,0,1),sample(c(0,1),replace = TRUE, size = 30))
Individual level data
Description
The data which describes the Individual level data (average age below 5, average age above 65 and SEFI factor) for 758 individuals.
Usage
Individual_level_data
Format
A data frame with 758 rows and 4 columns:
- Index
Index for individual
- Ave_Age_5
Average of age smaller than 5
- Ave_Age_65
Average of age higher 65
- SEFI
SEFI factor
...
Estimating parameters along with corresponding variances based on Naive model.
Description
Estimating parameters along with corresponding variances based on Naive model.
Usage
NaiveEstimation(
ITER,
MHiteration,
eps,
d,
nSample,
mm,
time,
MuxStar0,
MuxInd0,
SigmaxStar0,
SigmaxInd0,
Sigmav0,
Sigmaw0,
lambda0,
sigma0,
delta0,
alpha0,
beta10,
beta20,
beta30,
beta40,
InfPeriod,
g
)
Arguments
ITER |
The number of simulation runs |
MHiteration |
The number of iterations in Metropolis–Hastings algorithm |
eps |
Stopping value for MCECM algorithm |
d |
distance between cells |
nSample |
number of sample in each cell |
mm |
Number of areas. |
time |
Maximum time. |
MuxStar0 |
Mean of unobserved areal level covariates. |
MuxInd0 |
Mean of unobserved individual level covariates. |
SigmaxStar0 |
Variance of unobserved areal level covariates. |
SigmaxInd0 |
Variance of unobserved individual level covariates. |
Sigmav0 |
Variance of areal level measurement error variable. |
Sigmaw0 |
Variance of individual level measurement error variable. |
lambda0 |
Spatial dependency parameter. |
sigma0 |
Over dispersion parameter. |
delta0 |
The spatial parameter. |
alpha0 |
Initial value for intercept. |
beta10 |
Initial value for coefficient of observed individual level covariates. |
beta20 |
Initial value for coefficient of observed areal level covariates. |
beta30 |
Initial value for coefficient of unobserved individual level covariates. |
beta40 |
Initial value for coefficient of unobserved areal level covariates. |
InfPeriod |
The infectious period length. |
g |
grid dimension |
Value
The results of the function
Examples
NaiveEstimation(1,5,0.05,2,4,4,20,0,0,1,1,0.3,0.3,0.5,0.5,2.5,0,1,
1,1,1,3,2)
Estimating parameters along with corresponding variances based on Naive model with real data.
Description
Estimating parameters along with corresponding variances based on Naive model with real data.
Usage
NaiveEstimation_RealData(
ITER,
MHiteration,
eps,
mm,
time,
MuxStar0,
MuxInd0,
SigmaxStar0,
SigmaxInd0,
Sigmav0,
Sigmaw0,
lambda0,
sigma0,
delta0,
alpha0,
beta10,
beta20,
beta30,
beta40,
InfPeriod,
Di,
D,
Nlabel,
n,
cov1,
cov2,
ww,
vv,
tau
)
Arguments
ITER |
The number of simulation runs |
MHiteration |
The number of iterations in Metropolis–Hastings algorithm |
eps |
Stopping value for MCECM algorithm |
mm |
Number of areas. |
time |
Maximum time. |
MuxStar0 |
Mean vector of unobserved areal level covariates. |
MuxInd0 |
Mean vector of unobserved individual level covariates. |
SigmaxStar0 |
Variance of unobserved areal level covariates. |
SigmaxInd0 |
Variance of unobserved individual level covariates. |
Sigmav0 |
Variance of areal level measurement error variable. |
Sigmaw0 |
Variance of individual level measurement error variable. |
lambda0 |
Spatial dependency parameter. |
sigma0 |
Over dispersion parameter. |
delta0 |
The spatial parameter. |
alpha0 |
Initial value for intercept. |
beta10 |
Initial value for coefficient of observed individual level covariates. |
beta20 |
Initial value for coefficient of observed areal level covariates. |
beta30 |
Initial value for coefficient of unobserved individual level covariates. |
beta40 |
Initial value for coefficient of unobserved areal level covariates. |
InfPeriod |
The infectious period length. |
Di |
Euclidean distance between individuals |
D |
Neibourhood structure |
Nlabel |
Label for each sample from the area |
n |
Total number of individuals |
cov1 |
observed individual level covariates |
cov2 |
observed areal level covariates |
ww |
Unobserved individual level covariates |
vv |
unobserved areal level covariates |
tau |
tau |
Value
The results of the function
Examples
NaiveEstimation_RealData(1,5,0.05,4,20,0.1,0.1,0.15,0.8,0.6,0.6,
0.85,1.1,2.7,0,1,0,1,1,3,
matrix(runif(900,min = 4,max = 20),nrow=30, byrow = TRUE),
matrix(c(2,-1,-1,0,-1,2,0,-1,-1,0,2,-1,0,-1,-1,2),nrow=4,byrow=TRUE),
rep(1:4,c(7,6,8,9)),30,runif(30, 0, 1),
runif(4,0,1),runif(30,-2,2),runif(4,0,1),
sample(c(0,1),replace = TRUE, size = 30))
Regional data
Description
The data which describes the individual level data and areal data for 758 individuals.
Usage
Regional_data
Format
A data frame with 758 rows and 7 columns:
- Index
Index for individual
- Lat
Latitude of the area
- Long
Longitude of the area
- Population
Population of each area
- SEFI
SEFI factor
- Age_5
Number of individuals age below 5
- Age_65
Number of individuals age above 65
...