function(bypass1 = 0)
{
#Begin program project()
#
#All inputs defined globally, set by input utility programs.
#bypass = 1 bypasses calculation of lamda.f and lamda.m, allowing exogenously
#specified values.
#
	for(t in 1:(tt - 1)) {
#
#BEGIN UPDATE CALCULATIONS FOR YEAR t
#
#   #SECTION 1: COMPUTE NUMBERS OF DEATHS AND MOVEMENTS
#
#       #numbers of inactive females dying or becoming active
#
		force.sum <- mu.f[, t] + upsilon.f[, t]	#
		factor <- (xf[, t] * (1 - exp( - force.sum)))/force.sum
		xdf[, t] <- factor * mu.f[, t]	#
		xyf[, t] <- factor * upsilon.f[, t]	#
#
		force.sum <- mu.m[, t] + upsilon.m[, t]	#
		factor <- (xm[, t] * (1 - exp( - force.sum)))/force.sum	#
		xdm[, t] <- factor * mu.m[, t]	#
		xym[, t] <- factor * upsilon.m[, t]	#
#
#       #numbers of active females dying, becoming inactive, or becoming infected
#
#       #lamda.f, lamda.m
#
		pi <- sum(zm[,  , t])/(sum(zm[,  , t]) + sum(ym[, t]))	#
		lamda.f[, t] <- iota.f[, t] + (kappa.f + theta.f[, t]) * pi	#
		pi <- sum(zf[,  , t])/(sum(zf[,  , t]) + sum(yf[, t]))	#
		lamda.m[, t] <- iota.m[, t] + (kappa.m + theta.m[, 1]) * pi	#
#
#       #numbers active who die, become active, or become infected
#
		force.sum <- mu.f[, t] + tau.f[, t] + lamda.f[, t]	#
		factor <- (yf[, t] * (1 - exp( - force.sum)))/force.sum	#
		ydf[, t] <- factor * mu.f[, t]	#
		yxf[, t] <- factor * tau.f[, t]	#
#       #print(c(sum(force.sum), sum(factor), sum(yxf[, t])))   ##################
		yzf[, t] <- factor * lamda.f[, t]	#
#
		force.sum <- mu.m[, t] + tau.m[, t] + lamda.m[, t]	#
		factor <- (ym[, t] * (1 - exp( - force.sum)))/force.sum	#
		ydm[, t] <- factor * mu.m[, t]	#
		yxm[, t] <- factor * tau.m[, t]	#
#       #print(c(sum(force.sum), sum(factor), sum(yxm[, t])))   ####################
		yzm[, t] <- factor * lamda.m[, t]	#
#
#       #numbers infected who die of non-HIV related or of HIV-related causes
#
		force.sum <- array(data = mu.f[, t], dim = c(aa, dd)) + alpha[,  , t]	#
		factor <- (zf[,  , t] * (1 - exp( - force.sum)))/force.sum	#
		zdf[,  , t] <- factor * array(data = mu.f[, t], dim = dim(factor))	#
		zaf[,  , t] <- factor * alpha[,  , t]	#
#
		force.sum <- array(data = mu.m[, t], dim = c(aa, dd)) + alpha[,  , t]	#
		factor <- (zm[,  , t] * (1 - exp( - force.sum)))/force.sum	#
		zdm[,  , t] <- factor * array(data = mu.m[, t], dim = dim(factor))	#
		zam[,  , t] <- factor * alpha[,  , t]	#
#
#       #numbers of births, uinfected and infected, break out by sex
#
		ybirths <- sum(yf[, t] * beta.y[, t])	#
		zbirths <- sum(apply(zf[,  , t], 1, sum) * beta.z[, t])	#
#
		ubirths <- ybirths + (1 - zeta[t]) * zbirths	#
		ibirths <- zeta[t] * zbirths	#
#
		ubf[t] <- sigma.f * ubirths	#
		ubm[t] <- sigma.m * ubirths	#
		ibf[t] <- sigma.f * ibirths	#
		ibm[t] <- sigma.m * ibirths	#
#
#       #deaths of uninfected births, by sex
#
		ubdf[t] <- ubf[t] * (1 - exp( - mu.fb[t]))	#
		ubdm[t] <- ubm[t] * (1 - exp( - mu.mb[t]))	#
#
#       #deaths of infected births, by sex, from non-HIV-related and HIV-related causes
#
		force.sum <- mu.fb[t] + alpha.b[t]	#
		factor <- (1 - exp( - force.sum))/force.sum	#
#
		ibdf[t] <- ibf[t] * factor * mu.fb[t]	#
		ibaf[t] <- ibf[t] * factor * alpha.b[t]	#
#
		force.sum <- mu.mb[t] + alpha.b[t]	#
		factor <- (1 - exp( - force.sum))/force.sum	#
#
		ibdm[t] <- ibm[t] * factor * mu.mb[t]	#
		ibam[t] <- ibm[t] * factor * alpha.b[t]	#
#
#   #SECTION 2: UPDATE ARRAYS FROM t TO t+1
#
#       #inactive population age > 0
#
		xf[2:aa, t + 1] <- xf[1:(aa - 1), t] - (xdf[1:(aa - 1), t] + xyf[1:(aa - 1), t]) + yxf[1:(aa - 1), t]	#
		xm[2:aa, t + 1] <- xm[1:(aa - 1), t] - (xdm[1:(aa - 1), t] + xym[1:(aa - 1), t]) + yxm[1:(aa - 1), t]	#
#
#       #active uninfected population age > 0
#
		yf[2:aa, t + 1] <- yf[1:(aa - 1), t] - (ydf[1:(aa - 1), t] + yxf[1:(aa - 1), t] + yzf[1:(aa - 1), t]) + 
			xyf[1:(aa - 1), t]	#
		ym[2:aa, t + 1] <- ym[1:(aa - 1), t] - (ydm[1:(aa - 1), t] + yxm[1:(aa - 1), t] + yzm[1:(aa - 1), t]) + 
			xym[1:(aa - 1), t]	#  
#
#       #infected population duration 0, age > 0
#
		zf[2:aa, 1, t + 1] <- yzf[1:(aa - 1), t]	#
		zm[2:aa, 1, t + 1] <- yzm[1:(aa - 1), t]	#
#
#       #infected population of duration > 0, age > 0
#
		zf[2:aa, 2:dd, t + 1] <- zf[1:(aa - 1), 1:(dd - 1), t] - (zdf[1:(aa - 1), 1:(dd - 1), t] + zaf[1:(aa - 
			1), 1:(dd - 1), t])
		zm[2:aa, 2:dd, t + 1] <- zm[1:(aa - 1), 1:(dd - 1), t] - (zdm[1:(aa - 1), 1:(dd - 1), t] + zam[1:(aa - 
			1), 1:(dd - 1), t])	#
#
#       #update age = 0 (inactive and infected only)
#
		xf[1, t + 1] <- ubf[t] - ubdf[t]	#
		xm[1, t + 1] <- ubm[t] - ubdm[t]	#
		zf[1, 1, t + 1] <- ibf[t] - (ibdf[t] + ibaf[t])	#
		zm[1, 1, t + 1] <- ibm[t] - (ibdm[t] + ibam[t])	#
#
#   #END UPDATE CALCULATIONS FOR YEAR t
	}
#
#
#WRITE OUTPUT TO GLOBAL ARRAYS
#
#   #birth, death and movement arrays
#
	xdf <<- xdf	#
	xdm <<- xdm	#    
	xyf <<- xyf	#
	xym <<- xym	#
#    
	ydf <<- ydf	#
	ydm <<- ydm	#
	yxf <<- yxf	#
	yxm <<- yxm	#
	yzf <<- yzf	#
	yzm <<- yzm	#
#    
	zdf <<- zdf	#
	zdm <<- zdm	#
	zaf <<- zaf	#
	zam <<- zam	#
#
	ubf <<- ubf	#
	ubm <<- ubm	#
#
	ubdf <<- ubdf	#
	ubdm <<- ubdm	#
#
	ibf <<- ibf	#
	ibm <<- ibm	#
#
	ibdf <<- ibdf	#
	ibdm <<- ibdm	#
#
	ibaf <<- ibaf	#
	ibam <<- ibam	#
#
#   #population state arrays
#
	xf <<- xf	#
	xm <<- xm	#
	yf <<- yf	#
	ym <<- ym	#
	zf <<- zf	#
	zm <<- zm	#
#
#   #forces of new infection lamda
#
	lamda.f <<- lamda.f	#
	lamda.m <<- lamda.m	#
#
#end program project()
#
#write ascii copy to d:\aidsmodel\splustxt\project.txt
#
	write.ascii(project)
	"All done"
}