# Script 5: Internal Migration

>  Internal Migration is modeled calculating origin-destination matrices by age group and sex. For easier parameterization, parameters are split up in probabilities to leave and the distributions of destination by origin.

## File output

The code below generates 3 model parameters stored in a Modgen .dat file

- Migration probability by sex, age group and district
- Migration destination by origin, sex, and age group
- Turn module on/off

![*Figure: Internal Migration Parameters*](Figures/ParaMigration.png)


## Code

```{r, message=FALSE, warning=FALSE}
####################################################################################################
#
#  DYNAMIS-POP Parameter Generation File 5 - Internal Migration
#  This file is generic and works for all country contexts.
#  Input file: globals_for_analysis.RData (To generate such a file run the setup script)
#  Last Update: Martin Spielauer 2018-06-29
#
####################################################################################################

####################################################################################################
# Clear work space, load required packages and the input object file
####################################################################################################

rm(list=ls())

library(haven)
library(dplyr)
library(data.table)
library(sp)
library(maptools)
library(survival)
library(fmsb)
library(eha)


load(file="globals_for_analysis.RData")
dat <- g_residents_dat

# Set Parameter Output File
parafile <- file(g_para_migration, "w")

# Constants
n_maxdist       <- max(dat$M_DOB)

# Add an integer variable for age a year ago
dat$m_ageago <- as.integer(dat$M_AGE)-1

# remove those not born a year ago
dat <- dat[!(dat$m_ageago<0),]

# Age groups 5 years ago, up to 60+
dat$m_agegr5 <- as.integer(dat$m_ageago/5) * 5
dat$m_agegr5[dat$m_agegr5>60] <- 60

# Remove those not in the country 12 months ago (previous district was max value of districts)
dat <- dat[dat$M_PDIST<n_maxdist,]

# Person is internal migrant (moved within the country)
dat$is_migrant <- FALSE
dat$is_migrant[dat$M_DOR != dat$M_PDIST] <- TRUE

# Keep only what's needed
dat <- dat[,c("M_WEIGHT", "M_MALE", "M_EDUC", "M_DOR", "M_PDIST", "m_agegr5", "is_migrant" )]

####################################################################################################
# Create and append a dataset of all possible migrations for each age group
# This is to avoid empty cells in origin-destination matrices
# The records have very low weights which do not affect overall migration
####################################################################################################

umale <- unique(dat$M_MALE)
udist <- sort(unique(dat$M_DOR))
uage <- sort(unique(dat$m_agegr5))
ueduc <- sort(unique(dat$M_EDUC))
allmigs <- expand.grid(M_MALE=umale, M_DOR=udist, M_PDIST=udist, m_agegr5=uage, M_EDUC=ueduc )
allmigs <- allmigs[allmigs$M_DOR != allmigs$M_PDIST,]
allmigs$M_WEIGHT <- 0.0000001
allmigs$is_migrant <- TRUE
dat <- rbind(dat, allmigs)

####################################################################################################
# Calculate the parameter MigrationProbability[SEX][AGE5_PART][DISTRICT_NAT]                      
####################################################################################################

# Create the parameter for probability of out-migration by sex, age group and province of origin

popall   <- xtabs(dat$M_WEIGHT ~ dat$M_MALE + dat$m_agegr5 + dat$M_PDIST)
migs     <- dat[dat$is_migrant==TRUE,]
popmig   <- xtabs(migs$M_WEIGHT ~ migs$M_MALE + migs$m_agegr5 + migs$M_PDIST)
propmig  <- as.data.frame(popmig/popall)
propmig  <- propmig[order(propmig$migs.M_MALE, propmig$migs.m_agegr5, propmig$migs.M_PDIST),]

####################################################################################################
# Write the parameter MigrationProbability[SEX][AGE5_PART][DISTRICT_NAT]
####################################################################################################

cat("parameters { \n  //EN Migration probability \ndouble MigrationProbability[SEX][AGE5_PART][DISTRICT_NAT] = {\n", file=parafile)
cat(format(round(propmig$Freq,5),scientific=FALSE), file=parafile, sep=", ", append=TRUE)
cat("\n}; \n\n", file=parafile, append=TRUE)

####################################################################################################
# Calculate the parameter MigrationProbabilityEduc[PRIMARY_LEVEL][SEX][AGE5_PART][DISTRICT_NAT]              
####################################################################################################

popall    <- xtabs(dat$M_WEIGHT ~ dat$M_MALE + dat$m_agegr5 + dat$M_PDIST + dat$M_EDUC)
migs      <- dat[dat$is_migrant==TRUE,]
popmig    <- xtabs(migs$M_WEIGHT ~ migs$M_MALE + migs$m_agegr5 + migs$M_PDIST + migs$M_EDUC)
propmigE  <- as.data.frame(popmig/popall)
# for those below age 10 use the overall rates from above
propmigE  <- propmigE[propmigE$migs.m_agegr5 != "0" & propmigE$migs.m_agegr5 != "5",]
propmigN  <- propmig[propmig$migs.m_agegr5 == "0" | propmig$migs.m_agegr5 == "5",]

propmigN1 <- cbind(migs.M_EDUC ="0",propmigN)
propmigN2 <- cbind(migs.M_EDUC ="1",propmigN)
propmigN3 <- cbind(migs.M_EDUC ="2",propmigN)
propmigN  <- rbind(propmigN1, propmigN2, propmigN3)

propmig   <- rbind(propmigE, propmigN)
propmig   <- propmig[order(propmig$migs.M_EDUC, propmig$migs.M_MALE, propmig$migs.m_agegr5, propmig$migs.M_PDIST),]

####################################################################################################
# Write the parameter MigrationProbabilityEduc[PRIMARY_LEVEL][SEX][AGE5_PART][DISTRICT_NAT]
####################################################################################################

#cat("\n\n//EN Migration probability by Education\ndouble MigrationProbabilityEduc[PRIMARY_LEVEL][SEX][AGE5_PART][DISTRICT_NAT] = {\n", file=parafile, append=TRUE)
#cat(format(round(propmig$Freq,5),scientific=FALSE), file=parafile, sep=", ", append=TRUE)
#cat("\n}; \n\n", file=parafile, append=TRUE)

####################################################################################################
# Calculate the parameter cumrate MigrationDestination[SEX][DISTRICT_NAT][AGE5_PART][DISTRICT_NAT]    
####################################################################################################

popmig <- dat[dat$is_migrant==TRUE,]
popmig <- xtabs(popmig$M_WEIGHT ~ popmig$M_MALE + popmig$m_agegr5 + popmig$M_PDIST + popmig$M_DOR)
popmig <- as.data.frame(popmig)

popmig$groupsum  <- ave(popmig$Freq, popmig$popmig.M_MALE, popmig$popmig.m_agegr5, popmig$popmig.M_PDIST,FUN=sum)
popmig$paravalue <- popmig$Freq / popmig$groupsum
popmig           <- popmig[order(popmig$popmig.M_MALE, popmig$popmig.M_PDIST, popmig$popmig.m_agegr5),]

####################################################################################################
# Write the parameter MigrationDestination[SEX][DISTRICT_NAT][AGE5_PART][DISTRICT_NAT]
####################################################################################################

cat("\n\n//EN Migration Destination\ncumrate MigrationDestination[SEX][DISTRICT_NAT][AGE5_PART][DISTRICT_NAT] = {\n", file=parafile, append=TRUE)
cat(format(round(popmig$paravalue,10),scientific=FALSE), file=parafile, sep=", ", append=TRUE)
cat("\n};\n", file=parafile, append=TRUE)

cat("  logical ModelMigration = TRUE; //EN Migration switched on/off\n", file=parafile, append=TRUE)
cat("\n};\n", file=parafile, append=TRUE)

close(parafile)
```