File: age.epg

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epigrass 2.5.0+dfsg-1
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###############################################################
#
#  EPIGRASS -Model Definition
#  This script describes model and parameters specified
#  by the user.
#  It can be edited by the user directly, by means of a text editor.
#  WARNING: No variables may be removed, even if not used by the chosen model . 
#  Any comments added by the user must be preceeded  by the symbol #
#
################################################################
################################################################

#==============================================================#
[THE WORLD]
#==============================================================#
# Here you add information about the files that described the world the model is enclosed
# "Location" is the GRASS location with the maps describing the area.
# "vector layer" is the map layer that will be used as a background for the network display
# "sites" and "edges" are the files that describe the topology of the network (see Documentation)

shapefile =  ['riozonas_LatLong.shp','nome_zonas','zona_trafe']
sites = zonasRJcompleto.csv
edges = edgesRIO.csv
encoding =
#==============================================================#
[EPIDEMIOLOGICAL MODEL]
#==============================================================#
#model types available: SIS, SIS_s ,SIR, SIR_s, SEIS, SEIS_s, SEIR, SEIR_s, 
# SIpRpS, SIpRpS_s,SIpR,SIpR_s(see documentation for description)
modtype = Custom

#==============================================================#
[MODEL PARAMETERS]
#==============================================================#

#  They can be specified as constants or as functions of global or 
#    site-specific variables. these site-specific variables, are provided
#  in the sites file. All the numbers given after the geocode (4th column)
#  are collected into the values tuple.
#   Examples:
#   beta = 0.001
#   beta=values[0] #assigns the first element of values to beta 
#   beta=0.001*values[1]

# sem uso
beta = 0   #transmission coefficient (contact rate * transmissibility)
alpha = 0   # clumping parameter
e = 0           # inverse of incubation period
r = 0         # inverse of infectious period
delta = 0       # probability of acquiring full immunity [0,1]
B = 0           # Birth rate
w = 0           # probability of immunity waning [0,1]
p = 0           # Probability of a recovered become infected per time step [0,1]



# parametros do modelo:
pp = 1     # infecciosidade infeccao primaria
ps = 0.01   # infecciosidade infeccao secundaria
sp = 1     # suscetibilidade para infeccao primaria
ss = 0.7   # suscetibilidade para infeccao secundaria
pv = 0.90  # taxa de vacinacao
e = 0.7    # eficacia da vacina
gp = 0.1 # taxa de recuperacao infeccao primaria (0.333)
gs = 0.666 # taxa de recuperacao infeccao secundaria
a = 0.0019 # taxa de perda de imunidade adquirida pela infeccao
r = 0.0032 # taxa de perda de imunidade adquirida pela vacina
c0 = 0.1  # intensiade de contatos 
c1 = 0.3 # intensiade de contatos 
c2 = 0.7 # intensiade de contatos 
c3 = 1.0 # intensiade de contatos 
c4 = 1.4 # intensiade de contatos 
c5 = 1.8 # intensiade de contatos 
n0 = 4
n2 =  15
n10 = 15
n15 = 20
n20 = 20
n40 = 15
ep = 0. # 1/tempo de incubacao
es = 0.



#==============================================================#
[INITIAL CONDITIONS]
#==============================================================#
#   Here, the number of individuals in each epidemiological
#   state (SEI) is specified. They can be specified in absolute
#   or relative numbers.
#   N is the population size of each site.
#   The rule defined here will be applied equally to all sites.
#   For site-specific definitions, use EVENTS (below)
#   Examples:
#   S,E,I = 0.8*N, 10, 0.5*E
#   S,E,I = 0.5*N, 0.01*N, 0.05*N
#   S,E,I = N-1, 1, 0
### sem uso
S = N
E = 0
I = 0

### CI do modelo:

#S0 = 0.029*N   #media etaria das ZTs do rio
#S2 = 0.132*N
#S10 = 0.076*N
#S15 = 0.07*N
#S20 = 0.324*N
#S40 = 0.369*N 
S0 = values[3]*N   #media etaria das ZTs do rio
S2 = values[4]*N
S10 = values[5]*N
S15 = values[6]*N
S20 = values[7]*N
S40 = values[8]*N 
Ep0 = 0
Ep2 = 0
Ep10= 0
Ep15= 0
Ep20=0
Ep40 = 0
Ip0 = 0
Ip2 = 0
Ip10= 0
Ip15= 0
Ip20=0
Ip40 = 0
Es0 = 0
Es2 = 0
Es10= 0
Es15= 0
Es20=0
Es40 = 0
Is0= 0
Is2= 0
Is10= 0
Is15= 0
Is20= 0
Is40 = 0
Rmax0= 0
Rmax2= 0
Rmax10= 0
Rmax15= 0
Rmax20= 0
Rmax40 = 0
Rmed0= 0
Rmed2= 0
Rmed10= 0
Rmed15= 0
Rmed20= 0
Rmed40 = 0 
Rmin0= 0
Rmin2= 0
Rmin10= 0
Rmin15= 0
Rmin20= 0
Rmin40 = 0
Vmax0= 0
Vmax2= 0
Vmax10= 0
Vmax15= 0
Vmax20= 0
Vmax40 = 0
Vmed0= 0
Vmed2= 0
Vmed10= 0
Vmed15= 0
Vmed20= 0
Vmed40 = 0
Vmin0= 0
Vmin2= 0
Vmin10= 0
Vmin15= 0
Vmin20= 0
Vmin40 = 0


#=============================================================#
[EPIDEMIC EVENTS]
#=============================================================#
#   Specify isolated events.
#   Localities where the events are to take place should be Identified by the geocode, which 
#  comes after population size on the sites data file.
#  All coverages must be a number between 0 and 1.
#  Seed : [('locality1's geocode', n),('locality2's geocode', n)]. 
#  N infected cases will be added to locality at time 0.
#  Vaccinate: [('locality1's geocode', time, coverage),('locality2's geocode', time, coverage)] 
#  Quarantine: [(locality1's geocode,time,coverage), (locality2's geocode,time,coverage)]
#seed = [(4550601,'ip20',10)] #santo cristo  #
seed = [(4552110,'ip20',10)] #pechincha  #  
#seed = []
Vaccinate = [] #
Quarantine = []

# The following events have not yet been implemented
#Screening = (locality, time, coverage) #screening for sick people on aiports bus stations
#Vector_control = (locality, time, coverage)
#Treatment = (locality, time, coverage)
#Prophylaxis = (locality, time, coverage)

#==============================================================#
[TRANSPORTATION MODEL]
#==============================================================#
# If doTransp = 1 the transportation dinamics will be included. Use 0 here only for debugging purposes.
doTransp = 0

# Mechanism can be stochatic (1) or deterministic(0). 
stochastic = 0
#Average speed of transportation system in km per time step. Enter 0 for instantaneous travel.
#Distance unit must be the same specified in edges files
speed =1440  # km/day -- equivalent to 60 km/h

#==============================================================#
[SIMULATION AND OUTPUT]
#==============================================================#

# Number of steps
steps = 50

# Output dir. Must be a full path. If empty the output will be generated on the 
# same path as the model script.
outdir = 

# Output file
outfile = simul.dat

# Database Output
# MySQLout can be 0 (no database output) or 1
MySQLout = 1 

# Graphical outputs
draw map = 0

# Report Generation
# The variable report can take the following values:
# 0 - No report is generated.
# 1 - A network analysis report is generated in PDF Format.
# 2 - An epidemiological report is generated in PDF Format.
# 3 - A full report is generated in PDF Format.
# siteRep is a list with site geocodes. For each site in this list, a detailed report is apended to the main report.
report = 0
siteRep = []

#Replicate runs
#If replicas is set to an integer(n) larger than zero, the model will be run n times and the results will be con-
#solidated before storing.
#Replicate mode automatically turn off report and batch options. 
Replicas = 0
RandSeed = 2 
#Batch Run
#  list other scripts to be run in after this one. don't forget the extension .epg
#  model scripts must be in the same directory as this file or provide full path.
#  Example: Batch = ['model2.epg','model3.epg','/home/jose/model4.epg']
Batch = []#['sarsDF.epg','sarsPA.epg','sarsRS.epg']

################################################################
################################################################