; *******************************************************************************
; * Template file for TB/MDR-TB case generation
; * e-TB Manager System
; * Rio de Janeiro, oct-2008
; * 
; * Change the values after = to generate your own testing database
; * 
; *******************************************************************************



; *******************************************************************************
; * Se true, apaga todos os casos pr-existentes nos anos selecionados
; * Se false, os casos novos sero includos e os pr-existentes no sero modificados
; *******************************************************************************
remExistingCases= true


; *******************************************************************************
; * Variao em dias do tempo de tratamento
; * Exemplo= 10 - Indica que o tratamento poder ser de + ou - 10 dias alm do tempo previsto no regime
; *******************************************************************************
cohortVarTime = 7


; *******************************************************************************
; * Indique o nmero de casos de TB e TBMR por ano
; *******************************************************************************
cases = [
	{ year= 2000, numTBCases= 1181,  numMDRTBCases= 96 }
	{ year= 2001, numTBCases= 1210,  numMDRTBCases= 97 }
	{ year= 2002, numTBCases= 1246,  numMDRTBCases= 101 }
	{ year= 2003, numTBCases= 1269,  numMDRTBCases= 102 }
	{ year= 2004, numTBCases= 1287,  numMDRTBCases= 104 }
	{ year= 2005, numTBCases= 1306,  numMDRTBCases= 105 }
	{ year= 2006, numTBCases= 1278,  numMDRTBCases= 103 }
	{ year= 2007, numTBCases= 1290,  numMDRTBCases= 105 }
	{ year= 2008, numTBCases= 1285,  numMDRTBCases= 104 }
	{ year= 2009, numTBCases= 650,  numMDRTBCases= 53 }
	]


; *******************************************************************************
; * Nmero mnimo e mximo de dias que pode variar entre 
; * a data de registro e a notificao
; *******************************************************************************
varDaysRegDiag=1..30



; *******************************************************************************
; * Peso para diagnsticos de casos de TBMR 
; * Exemplo: CONFIRMED=10, SUSPECT=1
; * Significa que as changes de gerar casos confirmados so 10x maior que para suspeitos 
; *******************************************************************************
mdrDiagnosis = [
	CONFIRMED = 10
	SUSPECT = 1
]



; *******************************************************************************
; * Peso para gerao de casos do sexo masculino e feminino
; * Exemplo=
; * MALE= 2, FEMALE= 1 
; * As changes de gerar casos do sexo masculino so o 
; * dobro de chances de gerar casos do sexo feminino
; *******************************************************************************
genders = [
	MALE= 2
	FEMALE= 1
]


; *******************************************************************************
; * Nacionalidade dos pacientes
; * Exemplo: NATIVE=100, FOREIGN=5
; * A quantidade de casos nativos sero 100/5 vezes maior que a quantidade de casos estrangeiros
; *******************************************************************************
nationalities = [
	NATIVE	= 100
	FOREIGN	= 3
]

; *******************************************************************************
; * Peso na gerao do tipo de pacientes
; *******************************************************************************
patientTypesTB = [
	NEW= 80
	RELAPSE= 4
	AFTER_DEFAULT= 10
	FAILURE_FT= 3
	FAILURE_RT= 2
	OTHER= 1
]

patientTypesMDR = [
	NEW= 80
	RELAPSE= 4
	AFTER_DEFAULT= 10
	FAILURE_FT= 3
	FAILURE_RT= 2
	OTHER= 1
]


; *******************************************************************************
; * Pesos para gerao do tipo pulmonar ou extrapulmonar 
; *******************************************************************************
infectionSites = [
	PULMONARY		= 85
	EXTRAPULMONARY	        = 13
	BOTH 			= 2
]


; *******************************************************************************
; * Pesos para gerao de casos pulmonares 
; *******************************************************************************
pulmonaryForms = [
    'Tipo 1' = 10
    'Tipo 2' = 20
]


; *******************************************************************************
; * Pesos para gerao de casos extrapulmonares 
; *******************************************************************************
extrapulmonaryForms = [
	'Extra 1' = 10
	'Extra 2' = 20
]


; *******************************************************************************
; * Pesos para gerao do tipo rural ou urbano 
; *******************************************************************************
localityTypes = [
	RURAL		= 5
	URBAN		= 100
]


; *******************************************************************************
; * Fator para gerao de regimes padronizados ou individualizados
; * Exemplo= 10/1 
; * Indica que a chance do caso gerado usar um regime padronizado  10 vezes
; * maior que de um regime individualizado (s para TBMR) 
; *******************************************************************************
facRegimenStdInd = 10/5



; *******************************************************************************
; * Idade dos pacientes por faixa etria. Indique o peso de cada faixa 
; * para a gerao dos casos
; *******************************************************************************
ageRanges = [
	{ range= '<= 4', weightRange =	3..30 }			= 1
	{ range= '5 - 14', weightRange = 35..60 } 		= 3
	{ range= '15 - 24', weightRange = 45..70 }		= 5
	{ range= '25 - 34', weightRange = 55..90 } 		= 8
	{ range= '35 - 44', weightRange = 55..90 } 		= 5
	{ range= '45 - 54', weightRange = 55..90 }	 	= 4
	{ range= '55 - 64', weightRange = 55..90 }	 	= 4
	{ range= '>= 65', weightRange = 55..80 } 			= 3
]


; *******************************************************************************
; * Peso para escolha do regime padronizado para o caso
; * Coloque o nome do regime como aparece no sistema
; * Ou caso queira usar o seu cdigo, use um $ antes do cdigo
; * Exemplo, se o cdigo do regime 'GLC' for 22750, voc poder definir o peso 
; * desde regime como  
; *		GLC = 10  
; * ou 
; *		$22750 = 10
; *******************************************************************************
regimensTB = [
	'Category I' = 85
	'Category II' = 15
]

regimensMDR = [
	'Category IV' = 100
]


; *******************************************************************************
; * Peso para a gerao de casos por paciente (s para TBMR)
; *******************************************************************************
numTreatments = [
	ONE_TREATMENT	= 50		; Pacientes com 1 tratamento
	TWO_TREATMENTS	= 35		; Pacientes com 2 tratamentos
	THREE_TREATMENTS= 15
]



; *******************************************************************************
; * Peso para a gerao dos casos por regio (indique todas ou apenas as regies
; * para que voc quer que sejam gerados casos)
; *******************************************************************************
regions = [
	'Region A'		= 50
	'Region B'		= 20
	'Region C'		= 10
	'Region D'		= 10
	'Region E'		= 10

]



; *******************************************************************************
; * Percentual de casos que so transferidos (0 = nenhum, 100 = todos)
; *******************************************************************************
percTransfCases =	2



; *******************************************************************************
; * Peso no resultado do desfecho de cada caso
; *******************************************************************************
outcomesTB = [
	CURED					= 55
	TREATMENT_COMPLETED			= 20
	FAILED					= 5
	DEFAULTED				= 10
	DIED					= 6
	TRASNFERRED_OUT				= 2
	DIAGNOSTIC_CHANGED			= 1
	OTHER					= 1
]

outcomesMDR = [
	CURED					= 50
	TREATMENT_COMPLETED			= 15
	FAILED					= 10 
	DEFAULTED				= 10
	DIED					= 11
	TRASNFERRED_OUT				= 2
	DIAGNOSTIC_CHANGED			= 1
	OTHER					= 1
]


; *******************************************************************************
; * Tempo mdio em dias para iniciar o tratamento de TB e TBMR a partir da data de diagnstico
; * 0..10 significa entre 0 e 10 dias a partir da data de diagnstico
; *******************************************************************************
startTreatmentTB	= 0..7
startTreatmentMDR	= 0..15



; *******************************************************************************
; * Medicines to be used in susceptibility tests
; *******************************************************************************
substances = [ R, S, Z, E, Eto, H, Ofx, Km, Am, PAS, Cm, Cs ]



; *******************************************************************************
; * Nmero de casos de TB com resistncia a algum medicamento (entre 0 e 100)
; * Exemplo: = 5 
; * Para cada 100 casos de TB, 5 tem resistncia a algum medicamento
; *******************************************************************************
resTB = 2


; *******************************************************************************
; * Resistance patterns and its weight-factor
; *******************************************************************************
resPatternsTB = [
	[ R ] 		= 15
	[ H ] 		= 15
	[ E ] 		= 10
	[ Z ] 		= 10
]

resPatternsMDR = [
	[ R, H ] 		= 100
	[ R, H, Z ] 		= 10
	[ R, H, E ] 		= 20
	[ R, H, Z, E ] 		= 15
	[ R, H, Z, E, S ] 	= 10
	[ R, H, Eto, E ]	= 10
	[ R, H, Ofx, S]		= 8
	[ R, H, Ofx, Am ] 	= 4
]


; *******************************************************************************
; * Pesos para resultados de exames de teste de resistncia
; *******************************************************************************
susceptResults = [
	NOTDONE = 10
	RESISTANT = 2
	SUSCEPTIBLE = 20
	CONTAMINATED = 1
] 


; *******************************************************************************
; * Perodo em que ser feito o primeiro exame em relao a 
; * data de diagnstico
; * exemplo:
; * 	sputumFirst = 20..5
; * Indica que o exame ser feito entre 20 e 5 dias antes da data de diagnstico
; *******************************************************************************
sputumFirst  = 14..7
cultureFirst = 60..30
susceptFirst = 90..30
hivFirst = 90..30


; *******************************************************************************
; * Frequncia em dias para realizar novos exames
; * Exemplo:
; * 	sputumFreq = 90
; * Indica que a cada 90 dias ser feito um novo exame de baciloscopia
; *******************************************************************************
sputumFreqTB	= 30
cultureFreqTB 	= 0
susceptFreqTB 	= 0
hivFreqTB 	= 100

sputumFreqMDR	= 30
cultureFreqMDR = 60
susceptFreqMDR = 0
hivFreqTB 	= 100


; *******************************************************************************
; * Variao mxima percentual na data de realizao de um prximo exame
; * Exemplo:
; * 	varDateExam = 10
; * Significa que o prximo exame do caso pode acontecer com uma margem de erro
; * de 10% (para mais ou menos) da data prevista de realizao em relao ao 
; * exame anterior
; * Se a frequncia de realizao de cultura for de 30 dias, ento no exemplo acima
; * ela poder variar entre 27 e 33 dias (+ ou - 3 dias)
; *******************************************************************************
varDateExam = 7


; *******************************************************************************
; * Pesos para resultados de exames de baciloscopia
; *******************************************************************************
sputumResults = [
	NEGATIVE = 5
	POSITIVE = 10
	PLUS	 = 20
	PLUS2 	 = 25
	PLUS3 	 = 20
] 



; *******************************************************************************
; * Pesos para resultados de exames de cultura
; *******************************************************************************
cultureResults = [
	NEGATIVE	= 5
	POSITIVE	= 10
	PLUS		= 20
	PLUS2		= 25
	PLUS3		= 20
]


; *******************************************************************************
; * Pesos para resultados de exames de HIV
; *******************************************************************************
hivResults = [
	NEGATIVE	= 30
	POSITIVE	= 10
]



; *******************************************************************************
; * Nomes de homens usados para compor o nome do paciente 
; *******************************************************************************
firstNamesMale = [
	Marcos
	Samuel
	Ricardo
	Ronaldo
	Martin
	Mark
	Raymond
	Augusto
	Antony
	Arnaldo
	Alan
	Alexandre
	Alex
	Arin
	Arnald
	Agnaldo
	Albert
	Alberto
	Albert
	Alan
	Arnold
	Abaet
	Abdo
	Abdias
	Abel
	Ademar
	Beto
	Benedito
	Bernardo
	Bejamin
	Bruno
	Biafra
	Baltazar
	Bartolomeu
	Batista
	Belisario
	Benjamin
	Bonifcio
	Bruce
	Cludio
	Clenildo
	Carlos
	Caetano
	Clayton
	Conrado
	Constantino
	Caio
	Dado
	Daniel
	Dilson
	David
	Dean
	Flvio
	Fbio
	Fernando
	Francisco
	Fernandes
	Gustavo
	Glauco
	Geonor
	Gabriel
	Germano
	Giulio
	Ivo
	Ivan
	talo
	Iuri
	Yuri
	Joel
	Jorge
	Jos
	Jair
	John
	Jos
	Joo
	Jefferson
	Jlio
	Jonatas
	Jonathan
	Jeremias
	Jaco
	George
	Gilberto
	Gabriel
	Gregory
	Garcia
	Luiz Gustavo
	Lucas
	Lean
	Legolas
	Marcos
	Moises
	Manoel
	Nuno
	Norberto
	Nilo
	Noel
	Osmar
	Oswald
	Paulo
	Pedro
	Peter
	Paul
	Phill
	Patrick
	Rubens
	Ronald
	Rivaldo
	Renan
	Robson
	Roosevelt
	Rennan
	Renato
	Raul
	Ramon
	Rachid
	Sandro
	Steffano
	Xavier
]

; *******************************************************************************
; * Nomes de mulheres usados para compor o nome do paciente 
; *******************************************************************************
firstNamesFemale = [
	Albertina
	Andreia
	Arinan
	Ana Maria
	Ana Lcia
	Ana
	Ameely
	Alice
	Aline
	Arminda
	Benedita
	Bruna
	Beatriz
	Barbara
	Bianca
	Berenice
	Clara
	Clia
	Carolina
	Carol
	Carla
	Clarice
	Cleide
	Cludia
	Carmen
	Denise
	Daniella
	Daniele
	Diana
	Dbora
	Emlia
	Esmeralda
	Flvia
	Ftima
	Fabiana
	Fernanda
	Geovanna
	Glucia
	Gilda
	Helena
	Iraci
	In
	Irene
	Janete
	Juliana
	Jurema
	Josefina
	Joelma
	Jocilaine
	Maria
	Maria Antnia
	Maria Teresa
	Martha
	Mirian
	Marcela
	Manoela
	Michele
	Nair
	Karla
	Keli
	Kimberly
	Keila
	Lara
	Lair
	Lourdes
	Lvia
	Lauren
	Leonora
	Ndia
	Nbia
	Natasha
	Norma
	Nina
	Nataly
	Noelma
	Otaviana
	Paula
	Patrcia
	Paloma
	Paris
	Regina
	Roberta
	Rogria
	Raquel
	Rebeca
	Raimunda
	Romana
	Rose
	Rosely
	Solange
	Sandra
	Simone
	Sara
	Telma
	Tara
	Quilma
	Karen
]

; *******************************************************************************
; * Sobrenomes usados para compor o nome dos pacientes 
; *******************************************************************************
lastNames = [
	Antunes
	Araujo
	da Silva
	Batista
	Bolivar
	Brasil
	Bottino
	Dianno
	da Costa
	Copala
	Cortez
	Costeau
	da Costa Saldanha
	Dutra
	Boon
	Bernardes
	Busht
	Ford
	Farias
	Fernandes
	Fernandez
	Gallet
	Gomes
	Gump
	Greenhill
	Garcia
	Gusmo
	Gabriell
	Himan
	Hutson
	Huston
	Julia
	Xavier
	Silveira
	Silva e Souza
	de Souza
	Harris
	Keravec
	Bastos
	Lima
	Dantas
	Dickinson
	Medeiros
	Marques
	Moraes
	Mc Brain
	Murray
	Moore
	Neves
	Nunes
	Noodle
	Noir
	de Oliveira
	Roque
	Runderberg
	Rosario
	Ribeiro
	Souza da Silva
	Soares Brito
	Soares
	Smith
	Talimbard
	Tavares
	Timberland
	Timoteo
	Ribeiro da Silva
	Romeo
]

