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age15.epg
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age15.epg
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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,'ip15',1)] #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 = 340
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']
################################################################
################################################################