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# R package landsepi
Landscape Epidemiology and Evolution
......@@ -51,7 +56,8 @@ R packages dependencies :
To install :
```r
install.packages(c("Rcpp","sp","rgdal","Matrix","MASS","rgeos","maptools","fields","splancs","sf","RCALI"))
install.packages(c("Rcpp","sp","rgdal","Matrix","MASS","rgeos","maptools"
,"fields","splancs","sf","RCALI"))
```
### Install landsepi
......@@ -97,7 +103,8 @@ Open R:
```r
library(landsepi)
??landsepi ## select <landsepi::landsepi-package> for a complete description of the package
??landsepi
## select <landsepi::landsepi-package> for a complete description of the package
```
Run a demonstration (a 30-year simulation of a mosaic deployment strategy of two resistant cultivars in balanced proportions and high level of spatial aggregation):
......@@ -110,54 +117,66 @@ The package includes 5 landscape structures and a parameterisation to represent
```r
## complete description of the parameters
?simul_landsepi
## Default parameterisation
simul_landsepi() ## 5-year simulation of a mosaic deployment strategy of two resistant cultivars in balanced proportions and high level of spatial aggregation
## Default parameterisation (5-year simulation of a mosaic deployment strategy
## of two resistant cultivars in balanced proportions and high level of
## spatial aggregation
simul_landsepi()
```
#### Strategies combining qualitative and quantitative resistance
Examples of combinations in a 50-year period using landscape #1:
```r
## Combination of two major resistance genes
simul_landsepi(seed=1, idLan=1, propSR=0.8, isolSR=1, strat="PY", nHost=2, nYears=50
, resistance1=c(1,1,0,0,0,0,0,0)
, costInfect=0.5, costAggr=0.5, taumut=1e-7, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination of a major gene with a quantitative resistance against the infection rate
simul_landsepi(seed=1, idLan=1, propSR=0.8, isolSR=1, strat="PY", nHost=2, nYears=50
, resistance1=c(1,0,0,0,1,0,0,0)
, costInfect=0.5, costAggr=0.5, taumut=1e-7, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination of a major gene with a quantitative resistance against the latent period
simul_landsepi(seed=1, idLan=1, propSR=0.8, isolSR=1, strat="PY", nHost=2, nYears=50
, resistance1=c(1,0,0,0,0,1,0,0)
, costInfect=0.5, costAggr=0.5, taumut=1e-7, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination of a major gene with a quantitative resistance against the sporulation rate
simul_landsepi(seed=1, idLan=1, propSR=0.8, isolSR=1, strat="PY", nHost=2, nYears=50
, resistance1=c(1,0,0,0,0,0,1,0)
, costInfect=0.5, costAggr=0.5, taumut=1e-7, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination of a major gene with a quantitative resistance against the sporulation duration
simul_landsepi(seed=1, idLan=1, propSR=0.8, isolSR=1, strat="PY", nHost=2, nYears=50
, resistance1=c(1,0,0,0,0,0,0,1)
, costInfect=0.5, costAggr=0.5, taumut=1e-7, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
simul_landsepi(seed=1, idLan=1, nYears=50, strat="PY", nHost=2
, propSR=0.8, isolSR=1, resistance1=c(1,1,0,0,0,0,0,0)
, costInfect=0.5, MGeff=1.0, taumut=1e-7)
## Combination major gene and quantitative resistance against infection rate
simul_landsepi(seed=1, idLan=1, nYears=50, strat="PY", nHost=2
, propSR=0.8, isolSR=1, resistance1=c(1,0,0,0,1,0,0,0), taumut=1e-7
, costInfect=0.5, costAggr=0.5, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination major gene and quantitative resistance against latent period
simul_landsepi(seed=1, idLan=1, nYears=50, strat="PY", nHost=2
, propSR=0.8, isolSR=1, resistance1=c(1,0,0,0,0,1,0,0), taumut=1e-7
, costInfect=0.5, costAggr=0.5, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination major gene and quantitative resistance against sporulation rate
simul_landsepi(seed=1, idLan=1, nYears=50, strat="PY", nHost=2
, propSR=0.8, isolSR=1, resistance1=c(1,0,0,0,0,0,1,0), taumut=1e-7
, costInfect=0.5, costAggr=0.5, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
## Combination major gene and quantitative resistance against sporulation duration
simul_landsepi(seed=1, idLan=1, nYears=50, strat="PY", nHost=2
, propSR=0.8, isolSR=1, resistance1=c(1,0,0,0,0,0,0,1), taumut=1e-7
, costInfect=0.5, costAggr=0.5, MGeff=1.0, QReff=0.5, beta=1.0, nAggr=6)
```
#### Spatiotemporal strategies to deploy 2 major resistance genes
Examples of spatiotemporal strategies in a 50-year period using landscape #1:
```r
## Mosaic
simul_landsepi(seed=1, idLan=1, propSR=2/3, isolSR=3, propRR=1/2, isolRR=3, strat="MO", nHost=3, nYears=50
, resistance1=c(1,0,0,0,0,0,0,0), resistance2=c(0,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
simul_landsepi(seed=1, idLan=1, nYears=50, propSR=2/3, strat="MO", nHost=3
, isolSR=3, propRR=1/2, isolRR=3
, resistance1=c(1,0,0,0,0,0,0,0), resistance2=c(0,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
## Mixture
simul_landsepi(seed=1, idLan=1, propSR=2/3, isolSR=3, propRR=1/2, strat="MI", nHost=3, nYears=50
, resistance1=c(1,0,0,0,0,0,0,0), resistance2=c(0,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
simul_landsepi(seed=1, idLan=1, nYears=50, strat="MI", nHost=3
, propSR=2/3, isolSR=3, propRR=1/2
, resistance1=c(1,0,0,0,0,0,0,0), resistance2=c(0,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
## Rotations
simul_landsepi(seed=1, idLan=1, propSR=2/3, isolSR=3, isolRR=1, strat="RO", nHost=3, nYears=50
, resistance1=c(1,0,0,0,0,0,0,0), resistance2=c(0,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
simul_landsepi(seed=1, idLan=1, nYears=50, strat="RO", nHost=3
, propSR=2/3, isolSR=3, isolRR=1
, resistance1=c(1,0,0,0,0,0,0,0), resistance2=c(0,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
## Pyramiding
simul_landsepi(seed=1, idLan=1, propSR=2/3, isolSR=3, strat="PY", nHost=2, nYears=50
, resistance1=c(1,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
simul_landsepi(seed=1, idLan=1, nYears=50, strat="PY", nHost=2
, propSR=2/3, isolSR=3, resistance1=c(1,1,0,0,0,0,0,0)
, costInfect=0.5, taumut=1e-7)
```
### Simulation with other data
......
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