Generating network age-specific
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- a target population age-structure
- contact distribution (Mossong et al Plos Medicine)
- contact matrix (Mossong et al Plos Medicine)
N <- 1000
seed <- 123Assign age: depends on the target population age distribution
SR <- dget("./data/SR") # Sierra Leon population
if (!is.null(seed)) set.seed(seed)
age <- sample(SR$age, N, TRUE, SR$prob)
# add ages 70/80+
age[age==70] <- sample(70:80, length(age[age==70]), replace=1)Assign #contacts: depends on both target age and POLYMOD data
agecont <- orderBy(dget("./data/POLYMODtab1"), 1) # POLYMOD Tab.1
agecont$rk <- rank(agecont$age) # Rank age-group by contact
POLYMODbreak <- c(0,4,9,14,19,29,39,49,59,69,80)
ageGrp <- cut(age, breaks=POLYMODbreak, include.lowest=1)
ageGrp <- as.numeric(ageGrp) # mapping age to ageGrp
agerk <- sapply(ageGrp, function(x) agecont$rk[x==agecont$nmr])
age <- rev(orderBy(cbind(age, agerk), 2)[, 1]) # large to smallSampling from contact distribution
distCont <- dget("./data/distCont")
ncont <- sort(sample(distCont$freq, N, 1, distCont$prob), TRUE)Load contact matrix (as probability) POLYMOD data: averaging all countries
M <- dget("./data/M") # image(M)
Mbrk <- c(0,4,9,14,19,24,29,34,39,44,49,54,59,64,69,70)
Mnmr <- 1:15
Grp <- as.numeric(cut(age, breaks=Mbrk, include.lowest=1))
Grp[is.na(Grp)] <- 15 # 70+ age-grpRun
source("gennet.R")
g <- genNet(N, age)plotNet(g)Compare age- and contact-distribution
ks.test(age, vertex_attr(g, "age"))
Two-sample Kolmogorov-Smirnov test
data: age and vertex_attr(g, "age")
D = 0, p-value = 1
ks.test(degree(g), ncont)
Two-sample Kolmogorov-Smirnov test
data: degree(g) and ncont
D = 0, p-value = 1
put(1,2)
qqplot(degree(g), ncont, main="QQ Plot", ylab="Target contact distribution")
qqplot(age, vertex_attr(g, "age"), main="QQ Plot", ylab="Target age distribution")Compare contact-matrix