age=c(seq(2.5,47.5,5),60)
deaths=c(105,64,118,562,921,352,157,58,50,34,54)
cases=c(256,264,617,2303,2765,971,338,124,91,53,68)
survivors=cases-deaths
sum(deaths)
sum(cases)
round(100*deaths/cases,0)

Age=age[3:11]; D=deaths[3:11]; S=survivors[3:11]

mult.risk.model = glm(cbind(D,S)~Age,family=binomial(link=log))
plot(Age,mult.risk.model$fitted.values,col="red",type="l")
points(Age,D/(D+S))

logistic.model=glm(cbind(D,S)~Age,family=binomial(link=logit))
points(Age,logistic.model$fitted.values,type="l",col="blue")