Analysis of latent CHIKV dynamics models with general incidence rate and time delays

Figures & data

Figure 1. CHIKV replication cycle [34].

Table 1. The data of system (42(42) $\begin{array}{rl}\dot{S}\left(t\right)& =\mu -aS\left(t\right)-\frac{\beta S^h\left(t\right)V\left(t\right)}{\left({\alpha }_1+S^{h_1}\left(t\right)\right)\left({\alpha }_2+V^n\left(t\right)\right)},\end{array}$(42) )–(46(46) $\begin{array}{rl}\dot{B}\left(t\right)& =\eta +cB\left(t\right)V\left(t\right)-\delta B\left(t\right),\end{array}$(46) ).

Parameter	Value	Parameter	Value
μ	1.826	m	2.02
${\alpha }_1$	1.0	q	0.5964
${\alpha }_2$	3.0	r	0.4418
a	0.7979	η	1.402
θ	0.5	${\delta }_1,{\delta }_2$	0.5
λ	0.1	${\tau }_1,{\tau }_2$	varied
ε	0.4441	$h_1$	1.0
δ	1.251	h	2.0
ρ	0.5	c	1.2129
n	0.5	b	varied

Figure 2. The concentration of uninfected monocytes.

Figure 3. The concentration of latently infected monocytes.

Figure 4. The concentration of actively infected monocytes.

Figure 5. The concentration of free CHIKV particles.

Figure 6. The concentration of B cells.

Figure 7. The concentration of uninfected monocytes.

Figure 8. The concentration of latently infected monocytes.

Figure 9. The concentration of actively infected monocytes.

Figure 10. The concentration of free CHIKV particles.

Figure 11. The concentration of B cells.

Table 2. The values of steady states, ${\mathcal{R}}_0$ for model (42(42) $\begin{array}{rl}\dot{S}\left(t\right)& =\mu -aS\left(t\right)-\frac{\beta S^h\left(t\right)V\left(t\right)}{\left({\alpha }_1+S^{h_1}\left(t\right)\right)\left({\alpha }_2+V^n\left(t\right)\right)},\end{array}$(42) )–(46(46) $\begin{array}{rl}\dot{B}\left(t\right)& =\eta +cB\left(t\right)V\left(t\right)-\delta B\left(t\right),\end{array}$(46) ) with different values of ${\tau }_e$.

${\tau }_e$	Steady states	$R_0$
0.0	$Q_1=(1.7510,0.3574,0.5634,0.5790,2.5549)$	3.1717
0.5	$Q_1=(1.8243,0.2404,0.3790,0.4627,2.0326)$	2.4703
1.0	$Q_1=(1.9230,0.1474,0.2324,0.3296,1.6470)$	1.9238
1.5	$Q_1=(2.0520,0.0743,0.1171,0.1879,1.3703)$	1.4983
2.0	$Q_1=(2.2085,0.0196,0.0309,0.0543,1.1830)$	1.1669
2.3086	$Q_0=(2.2885,0,0,0,1.1207)$	1.0000
2.5	$Q_0=(2.2885,0,0,0,1.1207)$	0.9088
3.0	$Q_0=(2.2885,0,0,0,1.1207)$	0.7077
3.5	$Q_0=(2.2885,0,0,0,1.1207)$	0.5512
4.0	$Q_0=(2.2885,0,0,0,1.1207)$	0.4293
4.5	$Q_0=(2.2885,0,0,0,1.1207)$	0.3343
5.0	$Q_0=(2.2885,0,0,0,1.1207)$	0.2604

F.M. Lum and L.F.P. Ng, Cellular and molecular mechanisms of Chikungunya pathogenesis, Antiviral Res. 120 (2015), pp. 165–174. doi: 10.1016/j.antiviral.2015.06.009

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