
In classical epidemic models, a neglected aspect is the heterogeneity of disease transmission and progression linked to the viral load of each infected individual. Here, we investigate the interplay between the evolution of individuals' viral load and the epidemic dynamics from a theoretical point of view. We propose a stochastic particle model describing the infection transmission and the individual physiological course of the disease. Agents have a double microscopic state: a discrete label, that denotes the epidemiological compartment to which they belong and switches in consequence of a Markovian process, and a microscopic trait, measuring their viral load, that changes in consequence of binary interactions or interactions with a background. Specifically, we consider Susceptible–Infected–Removed–like dynamics where infectious individuals may be isolated and the isolation rate may depend on the viral load–sensitivity and frequency of tests. We derive kinetic evolution equations for the distribution functions of the viral load of the individuals in each compartment, whence, via upscaling procedures, we obtain macroscopic equations for the densities and viral load momentum. We perform then a qualitative analysis of the ensuing macroscopic model. Finally, we present numerical tests in the case of both constant and viral load–dependent isolation control.
Citation: Rossella Della Marca, Nadia Loy, Andrea Tosin. An SIR–like kinetic model tracking individuals' viral load[J]. Networks and Heterogeneous Media, 2022, 17(3): 467-494. doi: 10.3934/nhm.2022017
[1] | Francesca Marcellini . Existence of solutions to a boundary value problem for a phase transition traffic model. Networks and Heterogeneous Media, 2017, 12(2): 259-275. doi: 10.3934/nhm.2017011 |
[2] | Mauro Garavello . Boundary value problem for a phase transition model. Networks and Heterogeneous Media, 2016, 11(1): 89-105. doi: 10.3934/nhm.2016.11.89 |
[3] | Frederike Kissling, Christian Rohde . The computation of nonclassical shock waves with a heterogeneous multiscale method. Networks and Heterogeneous Media, 2010, 5(3): 661-674. doi: 10.3934/nhm.2010.5.661 |
[4] | Tong Li . Qualitative analysis of some PDE models of traffic flow. Networks and Heterogeneous Media, 2013, 8(3): 773-781. doi: 10.3934/nhm.2013.8.773 |
[5] | Alexandre M. Bayen, Alexander Keimer, Nils Müller . A proof of Kirchhoff's first law for hyperbolic conservation laws on networks. Networks and Heterogeneous Media, 2023, 18(4): 1799-1819. doi: 10.3934/nhm.2023078 |
[6] | Simone Göttlich, Camill Harter . A weakly coupled model of differential equations for thief tracking. Networks and Heterogeneous Media, 2016, 11(3): 447-469. doi: 10.3934/nhm.2016004 |
[7] | Benjamin Seibold, Morris R. Flynn, Aslan R. Kasimov, Rodolfo R. Rosales . Constructing set-valued fundamental diagrams from Jamiton solutions in second order traffic models. Networks and Heterogeneous Media, 2013, 8(3): 745-772. doi: 10.3934/nhm.2013.8.745 |
[8] | Alberto Bressan, Khai T. Nguyen . Conservation law models for traffic flow on a network of roads. Networks and Heterogeneous Media, 2015, 10(2): 255-293. doi: 10.3934/nhm.2015.10.255 |
[9] | Maya Briani, Emiliano Cristiani . An easy-to-use algorithm for simulating traffic flow on networks: Theoretical study. Networks and Heterogeneous Media, 2014, 9(3): 519-552. doi: 10.3934/nhm.2014.9.519 |
[10] | Mauro Garavello, Roberto Natalini, Benedetto Piccoli, Andrea Terracina . Conservation laws with discontinuous flux. Networks and Heterogeneous Media, 2007, 2(1): 159-179. doi: 10.3934/nhm.2007.2.159 |
In classical epidemic models, a neglected aspect is the heterogeneity of disease transmission and progression linked to the viral load of each infected individual. Here, we investigate the interplay between the evolution of individuals' viral load and the epidemic dynamics from a theoretical point of view. We propose a stochastic particle model describing the infection transmission and the individual physiological course of the disease. Agents have a double microscopic state: a discrete label, that denotes the epidemiological compartment to which they belong and switches in consequence of a Markovian process, and a microscopic trait, measuring their viral load, that changes in consequence of binary interactions or interactions with a background. Specifically, we consider Susceptible–Infected–Removed–like dynamics where infectious individuals may be isolated and the isolation rate may depend on the viral load–sensitivity and frequency of tests. We derive kinetic evolution equations for the distribution functions of the viral load of the individuals in each compartment, whence, via upscaling procedures, we obtain macroscopic equations for the densities and viral load momentum. We perform then a qualitative analysis of the ensuing macroscopic model. Finally, we present numerical tests in the case of both constant and viral load–dependent isolation control.
This paper deals with the initial boundary value problem for the phase transition model introduced in [9], consisting of the following
{∂tρ+∂x(ρv(ρ,η))=0∂tη+∂x(ηv(ρ,η))=0, | (1.1) |
where
The system in (1.1) belongs to the class of macroscopic second order traffic models, see [3,23], and it is characterized by two different phases: the Free one and the Congested one. A peculiarity of
In this paper we consider an initial boundary value problem for the model in (1.1) and we prove existence of solutions, provided the initial data and the boundary conditions have finite total variation. More precisely, we fix
{{∂tρ+∂x(ρv(ρ,η))=0∂tη+∂x(ηv(ρ,η))=0 if x∈(a,b),t>0,(ρ,η)(t,a)=(ρa(t),ηa(t)) if t>0,(ρ,η)(t,b)=(ρb(t),ηb(t)) if t>0,(ρ,η)(0,x)=(ρ0(x),η0(x)) if x∈(a,b). | (1.2) |
The initial datum is
In [12] Garavello considered an IBVP for the phase transition model introduced in [4]. We remark here that the model in [9], considered in this paper, and that one in [4], although similar, are different. Indeed Riemann problems for the two systems are solved, in general, in a different way and with a different number of waves. Another difference relies in the derivation: the model in [4] is based on the two phases, the free and the congested, while in [9] the two phases are a consequence of the model by imposing the speed limit
In this paper we use the wave front tracking technique, that is we explicitly construct a piecewise constant approximate solution, we prove that there exists an uniform bound on a functional measuring the strength of the waves and then, we conclude with the existence of a solution obtained by a compactness argument. We remark that, as in [12], the phase transition system with boundary considered in this paper is characteristic, since there are phase transitions waves with zero speed. In general, as usual in conservation laws, imposing characteristic boundary conditions is a delicate topic, see [1,2,11] and Remark 2.
The paper is organized as follows: in the next section we briefly recall the phase transition traffic model introduced in [9]. In Section 3, following the approach in [12], we state and prove the main result concerning the boundary value problem; the proof is divided into three different subsections.
We recall at first the phase transition model introduced in [9]. This model has been derived as an extension of the LWR model, given by the following single conservation law:
∂tρ+∂x(ρV)=0, | (2.1) |
where
{∂tρ+∂x(ρv)=0∂tw+v∂xw=0, | (2.2) |
where
As in [9,14], we recall the following assumptions:
(H-1):
(H-2):
(H-3):
Here,
In (1.1), the two phases, free and congested, are described by the sets
F={(ρ,w)∈[0,R]×[ˇw,ˆw]:v(ρ,ρw)=Vmax}, | (2.3) |
C={(ρ,w)∈[0,R]×[ˇw,ˆw]:v(ρ,ρw)=wψ(ρ)}, | (2.4) |
represented in Figure 1. Note that
We remark that, in the free phase
{∂tρ+∂x(ρVmax)=0∂tη+∂x(ηVmax)=0, | (2.5) |
while, in the congested phase
{∂tρ+∂x(ηψ(ρ))=0∂tη+∂x(η2ρψ(ρ))=0. | (2.6) |
We recall also the eigenvalues, right eigenvectors, and Lax curves
λ1(ρ,η)=ηψ′(ρ)+v(ρ,η),λ2(ρ,η)=v(ρ,η),r1(ρ,η)=[−ρ−η],r2(ρ,η)=[1η(1ρ−ψ′(ρ)ψ(ρ))],∇λ1⋅r1=−d2 dρ2[ρψ(ρ)],∇λ2⋅r2=0,L1(ρ;ρo,ηo)=ηoρρo,L2(ρ;ρo,ηo)=ρv(ρo,ηo)ψ(ρ),ρo<R. |
When
Finally, we list the waves and the notations that we will use in the present paper.
● First family wave: a wave connecting a left state
● Second family wave: a wave connecting a left state
● Linear wave: a wave connecting two states in the free phase.
● Phase transition wave: a wave connecting a left state
Remark 1. We remark hare that model (1.1), considered in this paper, and that one in [4], although similar, are different.
Both models are described by two intersecting phases: the free phase and the two-dimensional congested phase. Note however that, in the model (1.1) the free phase is two-dimensional in the conserved quantity coordinates
The main diffference lies in the solution of the Riemann problem, in particular when the left state belongs to the free phase and the right state to the congested one. In this case the Riemann problem for model (1.1) is solved with at most two waves, while the Riemann problem for the model considered in [4] is solved with at most three waves. See [13,Proposition 3.1,Proposition 3.2].
Also the derivation of the two models is completely different: the construction of the model in [4] is done imposing a priori two phases, the free and the congested one, while in [9] the two phases are obtained as a consequence of the speed limit
Before stating the main result, we introduce the definition of solution to the initial boundary value problem (1.2).
Definition 3.1. The function
(ρ∗,η∗)∈C0([0,+∞[;L1((a,b);F∪C)) |
is a solution to (1.2) if
1. the function
2. for a.e.
3. for a.e.
{{∂tρ+∂x(ρv(ρ,η))=0∂tη+∂x(ηv(ρ,η))=0 if τ>0,x∈R,(ρ,η)(0,x)={(ρa,ηa)(t) if x<a(ρ∗,η∗)(t,a+) if x>a |
admits a self similar solution
(˜ρ,˜η)(τ,a+)=(ρ∗,η∗)(t,a+). |
4. for a.e.
{{∂tρ+∂x(ρv(ρ,η))=0∂tη+∂x(ηv(ρ,η))=0 if τ>0,x∈R,(ρ,η)(0,x)={(ρ∗,η∗)(t,b−) if x<b(ρb,ηb)(t) if x>b |
admits a self similar solution
(˜ρ,˜η)(τ,b−)=(ρ∗,η∗)(t,b−). |
5.
Remark 2. The boundaries treated in this paper are characteristic, since there are phase transition waves with zero speed. Conditions 3 and 4 of Definition 3.1 are exactly the same as the boundary condition in the characteristic case in [1].
We can now state the main result of the paper:
Theorem 3.2. Let assumptions (H-1), (H-2) and (H-3) hold. Fix the initial condition
The proof is contained in the following subsections.
In this subsection we construct piecewise constant approximations via the wave-front tracking algoritm, which is a set of techniques to obtain approximate solutions to hyperbolic conservation laws in one space dimension. These tools were first introduced by Dafermos [10], see also [5,18] for the general theory. We show that every limit point is indeed a solution of the differential problem. The key estimate for compactness of the approximated solutions is a uniform bound of a functional measuring the strength of waves.
At first, we give the following definition of an
Definition 3.3. Given
1.
2.
3.
4. It holds that
{||(ˉρε(0,⋅),ˉηε(0,⋅))−(ρ0(⋅),η0(⋅))||L1(a,b)<ε||(ˉρa,ε,ˉηa,ε)−(ρa,ηa)||L1(0,+∞)<ε||(ˉρb,ε,ˉηb,ε)−(ρb,ηb)||L1(0,+∞)<εTV(ˉρε(0,⋅),ˉηε(0,⋅))≤TV(ρ0(⋅),η0(⋅))TV(ˉρa,ε,ˉηa,ε)≤TV(ρa,ηa)TV(ˉρb,ε,ˉηb,ε)≤TV(ρb,ηb). |
5. It holds that, for a.e.
{(ρa,ε,ηa,ε)(t) if x<a(ˉρε,ˉηε)(t,a+) if x>a |
is solved with waves with negative speed.
6. It holds that, for a.e.
{(ˉρε,ˉηε)(t,b−) if x<b(ρb,ε,ηb,ε)(t) if x>b |
is solved with waves with positive speed.
We consider now three sequences
1.
2. the following limits hold
limν→+∞(ρ0,ν,η0,ν)=(ρ0,η0) in L1((a,b);F∪C)limν→+∞(ρa,ν,ηa,ν)=(ρa,ηa) in L1((0,+∞);F∪C)limν→+∞(ρb,ν,ηb,ν)=(ρb,ηb) in L1((0,+∞);F∪C); |
3. the following inequalities hold
TV(ρ0,ν,η0,ν)≤TV(ρ0,η0)TV(ρa,ν,ηa,ν)≤TV(ρa,ηa)TV(ρb,ν,ηb,ν)≤TV(ρb,ηb). |
Next, for every
Remark 3. We may assume that, at every positive time
1. two waves interact together at a point
2. a wave interacts with the boundary
3.
Given an
Fw(t)=∑x∈Ii|w(ˉuε(t,x+))−w(ˉuε(t,x−))| | (3.1) |
F˜v(t)=∑x∈Ii|˜v(ˉuε(t,x+))−˜v(ˉuε(t,x−))| | (3.2) |
Fa(t)=|w(ˉuε(t,a+))−w(ˉua,ε(t))|+|˜v(ˉuε(t,a+))−˜v(ˉua,ε(t))| | (3.3) |
Fb(t)=|w(ˉuε(t,b−))−w(ˉub,ε(t))|+|˜v(ˉuε(t,b−))−˜v(ˉub,ε(t))| | (3.4) |
F(t)=Fw(t)+F˜v(t)+Fa(t)+Fb(t), | (3.5) |
where, we denote by
The functional
Next we consider interactions estimates of waves. We describe wave interactions by the nature of the involved waves, see [15,16]. For example, if a wave of the second family hits a wave of the first family producing a phase-transition wave, we write
Lemma 3.4. Assume that the wave
Proof. For simplicity, we define
vl=˜v(ρl,ηl),vm=˜v(ρm,ηm),vr=˜v(ρr,ηr),wl=w(ρl,ηl),wm=w(ρm,ηm),wr=w(ρr,ηr). | (3.6) |
We have four different cases.
1. The case
Fw(ˉt+)−Fw(ˉt−)=|wl−wi|+|wi−wr|−|wl−wm|−|wm−wr|. |
Now
Fw(ˉt+)−Fw(ˉt−)=|wl−wr|−|wl−wr|=0. |
Analogously for the functional (3.2), we have that
Fv(ˉt+)−Fv(ˉt−)=|vl−vi|+|vi−vr|−|vl−vm|−|vm−vr| |
and since
Fv(ˉt+)−Fv(ˉt−)=|vl−vr|−|vl−vr|=0. |
Since
2. The case
Fw(ˉt+)−Fw(ˉt−)=|wl−wi|+|wi−wr|−|wl−wm|−|wm−wr|. |
Similarly as before,
Fw(ˉt+)−Fw(ˉt−)=|wl−wr|−|wl−wr|=0. |
For the functional (3.2), we have that
Fv(ˉt+)−Fv(ˉt−)=|vl−vi|+|vi−vr|−|vl−vm|−|vm−vr|. |
Since
Fv(ˉt+)−Fv(ˉt−)=|vl−vr|−|vl−vm|−|vm−vr|=|vl+vm−vm−vr|−|vl−vm|−|vm−vr|≤0. |
Since
3. The case
Fw(ˉt+)−Fw(ˉt−)=|wl−wr|−|wl−wm|−|wm−wr|=0, |
since
Fv(ˉt+)−Fv(ˉt−)=|vl−vr|−|vl−vm|−|vm−vr|≤0. |
Since
4. The case
Fw(ˉt+)−Fw(ˉt−)=|wl−wr|−|wl−wm|−|wm−wr|=0. |
since
Fv(ˉt+)−Fv(ˉt−)=|vl−vr|−|vl−vm|−|vm−vr|≤0. |
Since
The proof is thus completed.
Lemma 3.5. Assume that the wave
Proof. First note that
va,ε=˜v(ˉua,ε(t)),wa,ε=w(ˉua,ε(t)). | (3.7) |
We have the following cases.
1. The case
Since the wave
ΔF(ˉt)=ΔFw(ˉt)+ΔF˜v(ˉt)+ΔFa(ˉt)+ΔFb(ˉt)=0. |
2. The case when the states
In this situation both the states
Thus we have
ΔF(ˉt)=|va,ε−vr|−|va,ε−vl|−|vl−vr|≤0. |
3. The case when the states
In this situation the state
In the case no wave is produced at time
In the case a phase transition wave with positive speed, connecting the states
ΔF(ˉt)=|va,ε−vr|−|vl−vr|−|va,ε−vl|≤0. |
The proof is thus completed.
Lemma 3.6. Assume that the wave
Proof. First note that
1. The case
Since the wave
If
ΔF(ˉt)=ΔFw(ˉt)+ΔF˜v(ˉt)+ΔFa(ˉt)+ΔFb(ˉt)=0. |
If
ΔF(ˉt)=0. |
2. The case when the states
In this situation both the states
If the interacting wave is of the second family, then no wave is generated at time
ΔF(ˉt)≤0. |
If the interacting wave is a phase transition wave with positive speed, then no wave is generated at time
ΔF(ˉt)=0. |
3. The case when the states
In this situation the state
In this case a phase transition wave with negative speed between the states
ΔF(ˉt)=|vl−vb,ε′|−|vl−vr|−|wl−wr|+|wb,ε−wb,ε′|−|vb,ε−vr|=|vl−vb,ε|−|vl−vr|−|vb,ε−vr|≤0. |
4. The case when the states
In this situation both the states
In this case no wave is generated at time
ΔF(ˉt)=|vl−vb,ε|+|wl−wb,ε|−|vr−vb,ε|−|wr−wb,ε|−|vl−vr|−|wl−wr|≤0. |
The proof is thus completed.
Lemma 3.7. Assume that
ΔF(ˉt)≤|w((ˉua,ε)(t+))−w((ˉua,ε)(t−))|+|˜v((ˉua,ε)(t+))−˜v((ˉua,ε)(t−))|. |
Proof. In general, at time
v+=˜v((ˉua,ε)(t+)),v−=˜v((ˉua,ε)(t−)),vm=˜v(um),vr=˜v(ur),w+=w((ˉua,ε)(t+)),w−=w((ˉua,ε)(t−)),wm=w(um),wr=w(ur), |
where
1. The states
If
ΔF(ˉt)=|wm−wr|+|v+−vm|−|v−−vr|=|w+−w−|+|v+−vm|−|v−−vm|≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
2. The states
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
3. The state
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
4. The state
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
The proof is so concluded.
Lemma 3.8. Assume that
ΔF(ˉt)≤|w((ˉua,ε)(t+))−w((ˉub,ε)(t−))|+|˜v((ˉub,ε)(t+))−˜v((ˉua,ε)(t−))|. |
Proof. In general, at time
v+=˜v((ˉub,ε)(t+)),v−=˜v((ˉub,ε)(t−)),vm=˜v(um),vl=˜v(ul),w+=w((ˉub,ε)(t+)),w−=w((ˉub,ε)(t−)),wm=w(um),wl=w(ul), |
where
1. The states
If
ΔF(ˉt)=|wm−w+|−|wl−w−|+|vl−vm|=|wm−w+|−|wm−w−|+|v+−v−|≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|wm−w+|−|vl−v−|+|vl−vm|=|w−−w+|−|vl−v−|+|vl−v+|≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
2. The states
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
3. The state
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)=|w+−w−|+|v+−v−|. |
4. The state
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
If
ΔF(ˉt)≤|w+−w−|+|v+−v−|. |
The proof is so concluded.
Proposition 1. The following estimate holds
F(t)≤M,a.e.t>0, | (3.8) |
where
Proof. This is a consequence of the previous Lemmas 3.4, 3.5, 3.6, 3.7, and 3.8.
Next we aim to bound the number of waves and of interactions. The following result holds.
Proposition 2. The construction in Subsection 3.1 can be done for every positive time and, for every
Proof. We consider the construction in Subsection 3.1 and the function
1. If at time
2. If at time
3. If at time
4. If the time
5. If the time
The number of waves can increase only in the cases 4., and 5. By construction, theese cases happen at most a finite number of times.
The interactions inside the domain
To prove that the number of interactions is finite, we have to consider and to bound the number of interactions of the following types:
1. Inside the domain:
2. Left boundary:
3. Right boundary:
Consider first the interaction
We can next conclude the proof of the Theorem 3.2.
Proof of Theorem 3.2. Fix an
F˜v+Fw≤M. |
The above inequality states that the functional
The author thanks Mauro Garavello for useful discussions. The author was partial supported by the INdAM-GNAMPA 2016 project "Balance Laws: Theory and Applications".
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Epidemic dynamics in absence of isolation control (
Contour plot of the basic reproduction number
Viral load–dependent vs. constant isolation control. Numerical solutions as predicted by the model (16) (solid lines) and by the particle model (5) (markers) in scenarios S1 (grey scale colour) and S2 (blue scale colour). Panel (a): compartment size of infectious individuals with increasing viral load,
Viral load–dependent vs. constant isolation control. Numerical solutions as predicted by the model (16) (solid lines) and by the particle model (5) (markers) in scenarios S1 (grey scale colour) and S2 (blue scale colour). Panel (a): mean viral load of infectious individuals with increasing viral load,
Viral load evolution from the time of infection exposure to the final time