How to identify oscillatory conditions in Julia ODEs?

I lost the file with the original conditions and I can’t find the parameters that replicate it. But I have a more generic model where each bacterium has a phage:

function Doppel!(du, u, p, t) 
    μ = p.μ   # bacterial growth rate
    κ = p.κ   # bacterial carrying capacity
    ω = p.ω   # system wash-out rate
    δ = p.δ   # phagial infection rate
    η = p.η   # phagial lysis rate (inverse latency)
    β = p.β   # phagial burst size
    λ = p.λ   # phagial decay rate
    #=
    du[1] = species A sensible
    du[2] = species A infected
    du[3] = phage a
    du[4] = species B sensible
    du[5] = species B infected
    du[6] = phage b
    =#
    N = u[1] + u[2] + u[4] + u[5]   # total bacteria
    ρ = 1 - N/κ                     # logistic term
    ϡ = (δ[1]*u[1]*u[3])            # upsampi: infected bacteria A
    ς = (δ[2]*u[4]*u[6])            # varsigma: infected bacteria B

    du[1] = (μ[1]*u[1]*ρ)       - ϡ                     - (ω*u[1])
    du[2] =                       ϡ     - (η[1]*u[2])   - (ω*u[2])
    du[3] = (η[1]*β[1]*u[2])    - ϡ     - (λ[1]*u[3])   - (ω*u[3])

    du[4] = (μ[2]*u[4]*ρ)       - ς                     - (ω*u[4])
    du[5] =                       ς     - (η[2]*u[5])   - (ω*u[5])
    du[6] = (η[2]*β[2]*u[4])    - ς     - (λ[2]*u[5])   - (ω*u[6])
end
# parameters
kappa   = 2e7               # carrying capacity (from Weitz)
omega   = 0.05              # outflow (from Weitz)
mu      = [0.16, 0.31]      # growth rate susceptible (pathogen)
beta    = [50.0, 75.0]      # burst size           (from Weitz)
delta   = [1e-9, 1e-9]      # adsorption rate (from Weitz)
eta     = [0.25, 0.75]      # reciprocal of latency   (from Weitz)
lambda  = [0, 0]            # decay rate in hours     (from Weitz)
As0     = 1e6               # initial susceptible density A
Ai0     = 0                 # initial infected density A
a0      = 1e5               # initial phage density a
Bs0     = 1e5               # initial susceptible density B
Bi0     = 0                 # initial infected density B
b0      = 1e4               # initial phage density b
t_mx  = 5e3
# implementation
u0 = [As0, Ai0, a0, Bs0, Bi0, b0]
tspan = (0.0, t_mx)
parms = ComponentArray(μ=mu, κ=kappa, ω=omega, δ=delta, η=eta, β=beta, λ=lambda)
prob = ODEProblem(Doppel!, u0, tspan, parms)
soln = solve(prob, Rosenbrock23())
# find steady state
eq = solve(prob, Rosenbrock23(), callback = TerminateSteadyState())

In this case, the carrying capacity makes quite a difference: if I use 30 000 000, I get:


eq gives the point of steady-state, as determined in a previous post.