Processing math: 100%
suppressMessages(library(knitr))
suppressMessages(library(ramp.xds))
#suppressMessages(library(ramp.library))
library(deSolve)
library(ramp.library)
#devtools::load_all()

Warning: workhorse is in development.

In the following, we present a stage of infection (SoI) model for malaria infection that recognizes an important difference between the two major phases of an infection: the acute phase characterized by geometrically increasing parasite numbers; and the chronic phase characterized by fluctuating parasite densities. The model explicitly considers superinfection, which moves individuals from an infected state into a parallel set of states.

  • Uninfected individuals are either susceptible to infection U or chemoprotected and not susceptible to infection.

  • Some recently treated, chemoprotected individuals remain infectious G. The remainder are chemoprotected and not infectious, P.

  • There are four chronic infection stages: I1,I2,I3 and I4 .

  • There are five acute infection stages: four (A1,A2,A3,A4) that correspond to an acute-phase infection concurrently infected with parasites in the chronic phase; and one (A0) that corresponds to carrying an acute phase infection but being otherwise uninfected.

  • All acutely infected individuals transition into I1

Variables

The variables are thus:

  • U

  • Chemoprotected states are P and G

  • Acute stages of infection: A0,A1,A2,A3,A4

  • Chronic stages of infection: I1,I2,I3,I4

Parameters

These are:

  • r - the rate of recovery from infection

  • σ - treatment rate

  • hτ - rate at which immunity is acquired

  • ζU - rate at which chemoprophylaxis is administered to uninfected individuals

  • ζA - rate at which chemoprophylaxis is administered to individuals in acute phase of infection

  • ϕ - rate at which individuals in acute phase move into chronic stage of infection

  • ζi,i=1,2,3,4 - rate at which individuals in chronic stages of infection obtain chemoprophylaxis

  • p(w) - the peak of infection

  • ξi,i=1,2,3,4 - rate at which individuals move through the different chronic stages of infection

  • δI - rate of loss of immunity

Active acute-phase infections become apparent after τ days, and:

Uninfected

dUda=riIi+σ(P+G)(hτ+ζU)UdA0da=riAi+hτU(ϕ+ζA+ζU)A0Chemoprotected

We are assuming that treatment as a result of an acute infection could leave a person infectious:

dPda=ζU(U+A0)+i2ζiIiσPdGda=ζ1I1+ζAiAiσG

Infected

Where ϕ is on the order of 1/10d and

At peak:

dI1da=p(w)ϕiAi(hτ+r+ξ1+ζ1)I1dI2da=(1p(w))ϕiAi+ξ1I1(hτ+r+ξ2+ζ2)I2dI3da=ξ2I2(hτ+r+ξ3+ζ3)I3dI4da=ξ3I3(hτ+r+ζ4)I4

Past peak, for n2,3,4:

dA1da=hτI1ϕA1(ζA+r+ζ1)A1dAnda=hτInϕAn(ζA+ζn)InImmune Tracking

dw0da=hτdwida=hτδIwi

#devtools::load_all()
wh <- xds_setup(dlay = 'dde', 
                Xname = "workhorse", 
                HPop=1000,
                Lname = "trivial", 
                Lopts = list(
                  Lambda = 3000, 
                  season = function(t){1+sin(2*pi*t/365)}
                  )
                )
wh <- xde_solve(wh, Tmax = 5*365, dt=10)
wh1 = wh 
wh1$Xpar[[1]]$zeta_1 = 0.02
wh1 <- xde_solve(wh1, Tmax = 5*365, dt=10)
xds_plot_X(wh)
xds_plot_X(wh1, llty=2, add=FALSE)
time = wh$outputs$time
with(wh$outputs$orbits$XH[[1]],{
  A = A0+A1+A2+A3+A4
  I = I1+I2+I3+I4
  plot(time, U + P + G, type = "l", ylim = range(0, H), col = "darkblue") 
  lines(time, A+I, col = "darkred") 
  lines(time, A, col = "purple") 
  lines(time, I-I1, col = "orange") 
  lines(time, P+G, col = "darkgreen") 
})

with(wh1$outputs$orbits$XH[[1]],{
  A = A0+A1+A2+A3+A4
  I = I1+I2+I3+I4
  lines(time, U + P + G, col = "darkblue", lty=2) 
  lines(time, A+I, col = "darkred", lty=2) 
  lines(time, A, col = "purple", lty=2) 
  lines(time, I-I1, col = "orange", lty=2) 
  lines(time, P+G, col = "darkgreen", lty=2) 
})