Skip to main content

Advertisement

Log in

Dynamical Analysis of a Model for Secondary Infection of the Dengue

  • Original Research
  • Published:
Differential Equations and Dynamical Systems Aims and scope Submit manuscript

Abstract

Dengue disease is a major public health problem in the world with a fast spreading rate. Human migration has contibute to spread of the different serotypes of dengue virus, incrementing the risk of dengue hemorrhagic fever and dengue shock syndrome. The disease immunological response is complex, with severe disease linked to the antibody-dependent enhancement. In this work we propose a system of differential equations to model the impact of human migration on the spread of two serotypes of dengue virus between two regions where only one of the serotypes was initially present. When the individuals to the other region they can contract a different serotype. Using the next generation matrix method, the basic reproductive number \(R_0\) is calculated and disease-free equilibrium stability is determined. In addition, conditions are obtained that guarantee the existence of an endemic equilibrium. These results provide conditions to predict an epidemic outbreak of dengue hemorrhagic due to a secondary infection of dengue.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data Availability

Not applicable.

References

  1. Aguiar M., Anam V., Blyuss K. B., Estadilla C. D. S., Guerrero B. V., Knopoff D., Stollenwerk N.: Mathematical models for dengue fever epidemiology: a 10-year systematic review. Phys. Life Rev. (2022)

  2. Agusto, F.B., Khan, M.A.: Optimal control strategies for dengue transmission in Pakistan. Math. Biosci. 305, 102–121 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  3. Alzahrani, E.O., Ahmad, W., Khan, M.A., Malebary, S.J.: Optimal control strategies of zika virus model with mutant. Commun. Nonlinear Sci. Numer. Simul. 93 (2020)

  4. Arino, J., Van den Driessche, P.: A multi-city epidemic model. Math. Pop. Stud. 10, 175–193 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  5. Ben-Shachar, R., Koelle, K.: Minimal within-host dengue models highlight the specific roles of the immune response in primary and secondary dengue infections. J. R. Soc. Interface 12 (2015)

  6. Ben-Shachar, R., Schmidler, S., Koelle, K.: Drivers of inter-individual variation in dengue viral load dynamics. PLoS Comput. Biol. 12 (2016)

  7. Bhatt, S., Gething, P.W., Brady, O.J.: The global distribution and burden of dengue. Nature 496, 1–4 (2013)

    Article  Google Scholar 

  8. Boulaaras, S., Jan, R., Khan, A., Ahsan, M.: Dynamical analysis of the transmission of dengue fever via Caputo-Fabrizio fractional derivative. Chaos Solitons Fract. X 8 (2022)

  9. Camargo, F.D.A., Adimy, M., Esteva, L., Métayer, C., Ferreira, C.P.: Modeling the relationship between antibody-dependent enhancement and disease severity in secondary dengue infection. Bull. Math. Biol. 8, 83–85 (2021)

    MathSciNet  MATH  Google Scholar 

  10. Clapham, H.E., Tricou, V., Van Vinh Chau, N., Simmons, C.P., Ferguson, N.M.: Within-host viral dynamics of dengue serotype 1 infection. J. R. Soc. 11 (2014)

  11. Coudeville, L., Baurin, N., Vergu, E.: Estimation of parameters related to vaccine efficacy and dengue transmission from two large phase III studies. Vaccine 34, 6417–6425 (2016)

    Article  Google Scholar 

  12. Diekmann, O., Heesterbeek, J.A.P.: Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation. Wiley, New York (2000)

    MATH  Google Scholar 

  13. Dorigatti, I., McCormack, C., Nedjati-Gilani, G., Ferguson, N.M.: Using Wolbachia for dengue control: insights from modelling. Cell Press 34, 102–113 (2018)

    Google Scholar 

  14. Feng, Z., Hernández, J.V.: Competitive exclusion in a vector-host model for the dengue fever. J. Math. Biol. 35, 523–544 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  15. Gakkhar, S., Mishra, A.: A dengue model incorporating saturation incidence and human migration. AIP Conf. Proc. 1651, 64–69 (2015)

    Article  Google Scholar 

  16. Gao, D., Ruan, S.: A multipach malaria model with logistic growth population. SIAM J. Appl. Math. 72(3), 819–841 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  17. Guzman, M., Gubler, D., Izquierdo, A., Martinez, E., Halstead, B.: Dengue infection. Nat. Rev. Dis. Primers (2016)

  18. Guzmán, M.G., Kourí, G., Valdés, L.: Enhanced severity of secondary dengue-2 infections: death rates in 1981 and 1997 Cuban outbreaks. Rev. Panam. Salud Pública. 11, 223–7 (2002)

    Article  Google Scholar 

  19. Instituto Nacional de Estadística, Geografía, e Informática, México, INEGI (2022). http://www3.inegi.org.mx

  20. Jan, R., Khan, M.A., Gómez-Aguilar, J.F.: Asymptomatic carriers in transmission dynamics of dengue with control interventions. Optim. Control Appl. Methods 41, 430–447 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  21. Khan, M.A., Ullah, S., Farhan, M.: The dynamics of Zika virus with Caputo fractional derivative. AIMS Math. 4, 134–146 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  22. Mishra, A., Gakkhar, S.: Non-linear dynamics of two-patch model incorporating secondary dengue infection. Appl. Comput. Math. 19, 1–22 (2018)

    MATH  Google Scholar 

  23. Nikin-Beers, R., Blackwood, J.C., Childs, L.M., Ciupe, S.M.: Unraveling within-host signatures of dengue infection at the population level. J. Theor. Biol. 446, 79–86 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  24. Ruan, S., Wang, W., Levin, S.A.: The effect of global travel on the spread of SARS. Math. Biosci. Eng. 3, 205–218 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  25. Sebayang, A.A., Fahlena, H., Anam, V., Knopoff, D., Stollenwerk, N., Aguiar, M., Soewono, E.: Modeling dengue immune responses mediated by antibodies: a qualitative study. Biology (2021)

  26. Shuai, Z., Van den Driessch, P.: Global stability of infectious disease model using Lyapunov functions. SIAM J. Appl. Math. 73, 1513–1532 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  27. Van den Driessche, P., Watmough, J.: Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 180, 29–48 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  28. Weiskopf, D., Sette, A.: T-cell immunity to infection with dengue virus in humans. Front. Immunol. (2014)

  29. World Health Organization: Dengue and severe dengue -key facts. https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue

  30. Yang, X.: Generalized form of Hurwitz-Routh criterion and Hopf bifurcation of higher order. Appl. Math. Lett. 15, 615–624 (2002)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The authors thank to the reviewers for their valuable comments that helped to improve the paper.

Funding

The first author thanks CONACYT for the scholarship granted.

Author information

Authors and Affiliations

Authors

Contributions

The authors have contributed equally to this work.

Corresponding author

Correspondence to G. Blé.

Ethics declarations

Conflict of interest

The authors do not have any conficts of interest.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

The authors agree to publish this work.

Code availability

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix A: Positive Invariant Set \(\Gamma\)

We will see that the vector field on the boundary of \(\Gamma\) does not point to the exterior of the region.

It can be seen that in the hyperplanes \(S_i=0\), \(I_i=0\), \(R_i=0\), \(I_{ij}=0\), \(Z{ij}=0\), \(U_i=0\), \(V_i=0, \; i,j=1,2\) the components \(S_i\), \(I_i\), \(R_i\), \(I_{ij}\), Z ij, \(U_i\), \(V_i\) of vector field are positive and therefore the vector field points to the interior of \(\Gamma\).

Now, adding components of the human and vector population in system (1) we get

$$\begin{aligned} \dfrac{dN_h}{dt}=\mu \left( \dfrac{\Lambda _1+\Lambda _2}{\mu } -N_h\right) \; \text{ y } \; \dfrac{dN_v}{dt}=\mu \left( \dfrac{\Omega _1+\Omega _2}{\nu } -N_v\right) , \end{aligned}$$

Using Gronwall inequality we have

$$\begin{aligned} \limsup \limits _{t \rightarrow \infty } N_h(t) \le \dfrac{\Lambda _1+\Lambda _2}{\mu } \; \text{ and } \; \limsup \limits _{t \rightarrow \infty } N_v(t) \le \dfrac{\Omega _1+\Omega _2}{\nu } . \end{aligned}$$

Also

$$\begin{aligned} \dfrac{dN_h}{dt}<0 \text{ and } \dfrac{dN_v}{dt}<0 \text{ for } N_h>\dfrac{\Lambda _1+\Lambda _2}{\mu } \text{ and } \dfrac{\Omega _1+\Omega _2}{\nu }, \text{ respectively }. \end{aligned}$$

This shows that the solutions of system (1) remain in the set \(\Gamma .\)

Appendix B: Existence of an Endemic Equilibrium Point

An endemic equilibrium point \(P_3\) exists, if the conditions of the following propositions are satisfied.

Proposition 7

The values \(I_{12}^*\), \(I_{21}^*\), \(I_2^*\) and \(S_2^*\) are positive if

i):

\(0<I_2^*<\dfrac{(m_{21}+\mu )(\gamma _1+\mu )\left( \mu \nu (\alpha (I_1^*+I_{21}^*)+\nu )+\alpha \beta _{21}\rho _1\Omega _1\right) I_{21}^*}{\alpha \beta _{21}\gamma _2m_{21} \rho _1 \Omega _1 (I_1^*+I_{21}^*)},\) and

ii):

\(\dfrac{R_{01} S_1^*}{S_{01}}-1<\frac{\alpha I_1^*}{\nu }<\frac{R_{01} S_1^*}{S_{01}}, \text{ and } 0<I_1^*<r_{01}.\)

where \(r_{01}\) is the positive root of quadratic polinomial \(N_1\) (it is described in the proof).

Proof

From (2)

$$\begin{aligned} I_{12}^*=\frac{h_{02}I_2^*+h_{01}}{m_{21}\alpha \beta _{21}\gamma _2 \rho _1 \Omega _1(I_1^*+I_{21}^*)}. \end{aligned}$$

where

$$\begin{aligned} h_{02}=&-\alpha \beta _{21}\gamma _2m_{21} \rho _1 \Omega _1 (I_1^*+I_{21}^*)<0,\\ h_{01}=&(m_{21}+\mu )(\gamma _1+\mu )\left( \mu \nu (\alpha (I_1^*+I_{21}^*)+\nu ) +\alpha \beta _{21}\rho _1\Omega _1\right) I_{21}^*>0. \end{aligned}$$

Then \(I_{12}^*>0,\) if \(h_{02}I_2^*>-h_{01}\), which is hypothesis i).

On the other hand, since

$$\begin{aligned} I_{21}^*=-\dfrac{ I_1^*\nu (\gamma _1+\mu )}{\nu (\gamma _1+\mu )I_1^*-\beta _1 \Omega _1S_1^*}\left( I_1^*+\frac{\nu }{\alpha }-\dfrac{\beta _1\Omega _1S_1^*}{(\gamma _1+\mu )\nu }\right) >0, \end{aligned}$$

if \(\dfrac{\beta _1\Omega _1S_1^*}{(\gamma _1+\mu )\nu }-\dfrac{\nu }{\alpha }<I_1^* <\dfrac{\beta _1\Omega _1S_1^*}{(\gamma _1+\mu )\nu }.\) Substituting \(R_{01}=\frac{\alpha \beta _1 S_{01}^* U_{01}^*}{(\gamma _1+\mu )\nu }\) in \(\dfrac{\beta _1\Omega _1S_1^*}{(\gamma _1+\mu )\nu }\), we have \(\dfrac{R_{01} S_1^*}{S_{01}}-1<\frac{\alpha I_1^*}{\nu }<\frac{R_{01} S_1^*}{S_{01}},\) which is hypothesis ii).

By (2) we have that the sign of \(I_2^*\) and \(S_2^*\) are given by the sign of \(N_1\) and \(N_2\). Since \(N_2=\alpha \beta _{21}\gamma _2 m_{21}\rho _1\Omega _1(I_1^*+I_{21}^*)(\mu +m_{12}) \Big (I_1^*\left( \alpha I_{21}^*(\gamma _1+\mu ) (\mu +m_{21}) (\beta _{12} \rho _2\Omega _2+\mu \nu ) (\beta _{21}\rho _1\Omega _1+\mu \nu )+\beta _{21} \gamma _2\mu \nu ^2 m_{21}\rho _1 \Omega _1 \right) +I_{21}^*\left( \alpha I_{21}^* (\gamma _1+\mu ) (\mu +m_{21}) (\beta _{12} \rho _2 \Omega _2+\mu \nu ) (\beta _{21} \rho _1 \Omega _1+\mu \nu )+\mu \nu ^2 (\mu (\gamma _1+\mu ) (\beta _{12} \rho _2 \Omega _2+\mu \nu )+m_{21} ((\gamma _1+\mu ) (\beta _{12} \rho _2 \Omega _2+\mu \nu ) +\beta _{21} \gamma _2 \rho _1 \Omega _1)) \right) \Big )>0,\)

then \(I_2^*>0\) and \(S_2^*>0\) if \(N_1>0.\)

Note that \(N_1=h_{12}I_1^*{^2}+h_{11}I_1^*+h_{10}\) where

$$\begin{aligned} h_{12}= & {} -\alpha \beta _{12} \beta _{21} \gamma _1 \gamma _2 m_{12} m_{21} \rho _1\rho _2\Omega _1 \Omega _2,\\ h_{11}= & {} \alpha I_{21}^* (m_{12} (\mu (\gamma _1+\mu ) (\gamma _2+\mu ) (\beta _{12} \rho _2\Omega _2+\mu \nu ) (\beta _{21} \rho _1\Omega _1+\mu \nu )+\beta _{12} m_{21} \rho _2\Omega _2 \left( \beta _{21} \rho _1\Omega _1 (\mu (\gamma _1+\gamma _2) -\gamma _1 \gamma _2+\mu ^2)+\mu \nu (\gamma _1+\mu ) (\gamma _2+\mu )\right) +\mu \nu m_{21} (\gamma _1+\mu ) (\gamma _2+\mu ) (\beta _{21} \rho _1\Omega _1+\mu \nu ))+\mu (\gamma _1+\mu ) (\gamma _2+\mu ) (\mu +m_{21}) (\beta _{12} \rho _2\Omega _2+\mu \nu ) (\beta _{21} \rho _1\Omega _1+\mu \nu ))+\beta _{21} \gamma _2 \mu \nu ^2 m_{21} \rho _1\Omega _1 (\gamma _2+\mu ) (\mu +m_{12}),\\ h_{10}= & {} \mu I_{21}^*\Big ( \alpha I_{21}^* (m_{12} (\beta _{12} \rho _2\Omega _2 (\beta _{21} \rho _1\Omega _1 ((\gamma _1+\mu ) (\gamma _2+\mu )+m_{21} (\gamma _1+\gamma _2+\mu ))+\nu (\gamma _1+\mu ) (\gamma _2+\mu ) (\mu +m_{21}))+\nu (\gamma _1+\mu ) (\gamma _2+\mu ) (\mu +m_{21}) (\beta _{21} \rho _1\Omega _1+\mu \nu ))+(\gamma _1+\mu ) (\gamma _2+\mu ) (\mu +m_{21}) (\beta _{12} \rho _2\Omega _2+\mu \nu ) (\beta _{21} \rho _1\Omega _1+\mu \nu ))+\nu ^2 (\gamma _2+\mu ) (\mu +m_{12}) (\mu (\gamma _1+\mu ) (\beta _{12} \rho _2\Omega _2+\mu \nu )+m_{21} ((\gamma _1+\mu ) (\beta _{12} \rho _2\Omega _2+\mu \nu )+\beta _{21} \gamma _2 \rho _1\Omega _1)) \Big ). \end{aligned}$$

Furthermore, \(N_1=h_{12}(I_1^*-r_{00})(I_1^*-r_{01}),\) where

\(r_{00}=\frac{-h_{11}+\sqrt{h_{11}^2-4h_{12}h_{10}}}{2h_{12}}\) and \(r_{01}=\frac{-h_{11}-\sqrt{h_{11}^2-4h_{12}h_{10}}}{2h_{12}}.\)

Since

$$\begin{aligned} h_{12}<0 \text{ and } h_{10}>0, \end{aligned}$$

then \(N_1>0\) if \(0<I_1^*<r_{01}\), which is hypothesis ii). Therefore \(I_2^*>0\) and \(S_2^*>0.\) \(\square\)

Now, we will show that the polynomial equations of system (3) can have a positive solution. The quartic and constant coefficients of system (3) are

$$\begin{aligned} e_4=&\alpha ^2\nu ^2\rho ^2\beta _{21}^2(m_{12}+\mu )(m_{21}+\mu )^2 (\gamma _1+\mu )^4(\gamma _2+\mu )((m_{21}+\mu )\nu +\beta _2\rho _2),\\ f_4=&-\alpha ^2\Omega _1^2\beta _1^3\mu (m_{12}+\mu )(m_{21}+\mu ) (\mu \nu +\beta _{12}\rho _2\Omega _2)(m_{21}\beta _1\mu (\gamma _2+\mu )\nu \\&+\beta _1\mu ^2(\gamma _2+\mu )\nu +\beta _2\beta _{21}\gamma _2\rho _1\Omega _2(m_{12}+\mu )),\\ e_0=&-\beta _1^2 \mu (\mu +m_{12}) (a_0-a_1 S_1) (b_0+b_1 S_1)S_1^2,\\ f_0=&I_1^2\beta _{21}^2\rho ^2\nu (\gamma _1+\mu )(c_2I_1^2+c_1 I_1+c_0), \end{aligned}$$

where

$$\begin{aligned} a_1= & {} \alpha \beta _1\Omega _1(m_{21}+\mu )(\mu \nu +\beta _{12}\rho _2\Omega _2),\\ a_0= & {} \nu ^2\left( \mu \nu (m_{21}+\mu )(\gamma _1+\mu )+\beta _{12}\rho _2\Omega _2(m_{21}+\mu )(\gamma _1+\mu )+m_{21}\beta _{21}\gamma _2\rho _1\Omega _1\right) ,\\ b_1= & {} \alpha \Omega _1\left( \beta _1\mu \nu (m_{21}+\mu )^2(\gamma _2+\mu )+\beta _2\Omega _2(\beta _1\mu (m_{21}+\mu )(\gamma _2+\mu )+m_{12}m_{21}\beta _{21}\gamma _2\rho _1)\right) ,\\ b_0= & {} -m_{21}^2\nu ^2(\gamma _2+\mu )(\mu \nu (\gamma _1+\mu )+\beta _{21}\gamma _2\rho _1\Omega _1)+m_{21}(-\beta _2 \Omega _2(\mu \nu ^2 (\gamma _1+\mu ) (\gamma _2+\mu ) -\alpha \beta _{21}\gamma _2 \Lambda _2 \rho _1 \Omega _1)-\mu \nu ^2 (\gamma _2+\mu ) (\beta _{21} \gamma _2 \rho _1 \Omega _1+2 \mu \nu (\gamma _1+\mu ))) -\mu ^2\nu ^2(\gamma _1+\mu )(\gamma _2+\mu )(\mu \nu +\beta _2\Omega _2),\\ c_2= & {} -\alpha (m_{12}+\mu )(m_{21}+\mu )(\gamma _1+\mu )^2(\mu \nu +\beta _{12}\rho _2\Omega _2)((m_{21}+\mu )(\gamma _2+\mu )\nu +\beta _2\gamma _2\Omega _2),\\ c_1= & {} -\alpha (\gamma _1+\mu )\left( \mu (2\mu (m_{21}+\mu )(\gamma _2+\mu )(\mu (\gamma _1+\mu )+m_{21}(\gamma _1-\gamma _2+\mu ))\nu ^3 +\nu \Omega _2(\beta _2\gamma _2\mu (\nu (\mu (\gamma _1+\mu )+m_{21} (\gamma _1-\gamma _2+\mu ))-\alpha \Lambda _1 (\mu +m_{21})) +\beta _{12}(m_{21}+\nu )(\gamma _2+\mu )(2\mu (\gamma _1+\mu )+m_{21} (2 \gamma _1-\gamma _2+2\mu ))\nu \rho _2)+\beta _{12}\beta _2 \gamma _2 \rho _2 \Omega _2^2 (\mu +m_{21})(\nu (\gamma _1+\mu )-\alpha \Lambda _1)+m_{12}(\beta _{12}\beta _2 \gamma _2\rho _2 \Omega _2^2 (\mu +m_{21})(\nu (\gamma _1+\mu )-\alpha \Lambda _1)+ \nu \Omega _2 (\beta _2 \gamma _2\mu (\nu (\mu (\gamma _1+\mu )+m_{21}(\gamma _1-\gamma _2+\mu ))-\alpha \Lambda _1 (\mu +m_{21}))+\beta _{12} \nu \rho _2(\mu +m_{21}) (2\mu (\gamma _1+\mu )(\gamma _2+\mu )+m_{21}(\gamma _1 (\gamma _2+2 \mu )-(\gamma _2-2 \mu )(\gamma _2+\mu ))))+2 \mu \nu ^3 (\gamma _2+\mu ) (\mu +m_{21}) (\mu (\gamma _1+\mu )+m_{21} (\gamma _1-\gamma _2+\mu ))))\right) . \end{aligned}$$

And the expression \(c_0\) is given below in the proof of Proposition 9.

Since \(e_4>0\) and \(f_4<0\), in order to have a positive solution, it is enough to find conditions to have \(e_0<0\) and \(f_0>0\).

Proposition 8

\(e_0<0\) if any of the following conditions are satisfied:

  • \(b_0\ge 0\) and \(S_1<\dfrac{a_0}{a_1},\)

  • \(b_0< 0\) and \(\Big (-\dfrac{b_0}{b_1}<S_1 \text{ and } S_1<\dfrac{a_0}{a_1}\Big ) \text{ or } \Big (-\dfrac{b_0}{b_1}>S_1 \text{ and } S_1>\dfrac{a_0}{a_1}\Big ).\)

Proof

Remember that

$$\begin{aligned} e_0=-\beta _1^2 \mu (\mu +m_{12}) (a_0-a_1 S_1) (b_0+b_1 S_1)S_1^2. \end{aligned}$$

Since \(a_0>0\) , \(a_1>0\) and \(b_1>0\) then,

$$\begin{aligned} a_0-a_1 S_1>0, \text{ if } S_1<\dfrac{a_0}{a_1}, \end{aligned}$$

and

$$\begin{aligned} b_0+b_1 S_1>0, \text{ if } b_0\ge 0 \text{ or } b_0<0 \text{ and } S_1>-\dfrac{b_0}{b_1}. \end{aligned}$$

On the other hand, \(a_0-a_1 S_1<0, \text{ if } S_1>\dfrac{a_0}{a_1},\)

and

$$\begin{aligned} b_0+b_1 S_1<0 \text{ if } b_0<0 \text{ and } S_1<-\dfrac{b_0}{b_1}. \end{aligned}$$

\(\square\)

Proposition 9

\(f_0>0,\) if the following conditions are satisfied:

  • \(\gamma _1+\mu \ge \gamma _2\) and \(\alpha >-\dfrac{c_{00}}{c_{01}},\)

  • \(0<I_1<r_{02}.\)

Proof

Since

$$\begin{aligned} f_0=I_1^2\beta _{21}^2\rho ^2\nu (\gamma _1+\mu )(c_2I_1^2+c_1I_1+c_0), \end{aligned}$$

we are going to show that the expression

$$\begin{aligned} c_2I_1^2+c_1I_1+c_0 \end{aligned}$$
(B1)

is positive. Since

$$\begin{aligned} c_0=c_{00}+c_{01}\alpha , \end{aligned}$$

where

$$\begin{aligned} c_{01}= & {} \beta _2\gamma _2\nu \Lambda _1\Omega _2(m_{12}+\mu )\Big (\mu \nu \left( \mu (\gamma _1+\mu )+m_{21} (\gamma _1-\gamma _2+\mu )\right) +\beta _{12}\rho _2\Omega _2(m_{21}+\nu )(\gamma _1+\nu )\Big ),\\ c_{00}= & {} -\mu \nu ^3\left( \mu (\gamma _1+\mu )+m_{21}(\gamma _1-\gamma _2+\mu )\right) \Big (\beta _{12}\rho _2\Omega _2\left( m_{12} ((\gamma _1+\mu ) (\gamma _2+\mu )+m_{21} (\gamma _1+\gamma _2+\mu )) +(\gamma _1+\mu ) (\gamma _2+\mu ) (\mu +m_{21} \right) +\nu (m_{12}+\mu )(\gamma _2+\mu )\left( \mu (\gamma _1+\mu )+m_{21} (\gamma _1-\gamma _2+\mu )\right) \Big ). \end{aligned}$$

If \(\gamma _1+\mu \ge \gamma _2\) then

$$\begin{aligned} c_{01}>0 \text{ and } c_{00}<0. \end{aligned}$$

Thus

$$\begin{aligned} c_0>0 \text{ if } \alpha >-\dfrac{c_{00}}{c_{01}}. \end{aligned}$$

Since \(c_2<0,\) the parabola corresponding to the expression (B1) opens downwards. Therefore

$$\begin{aligned} c_2I_1^2+c_1I_1+c_0=c_2( I_1-r_{02})(I_1-r_{03})>0 \text{ if } 0<I_1<r_{02}, \end{aligned}$$

where \(r_{02}\) is the positive root of (B1) \(\square\)

Appendix C: Global Stability of the Disease-Free Equilibrium

We define the following function to demonstrate the global stability of the equilibrium point \(P_0\):

$$\begin{aligned} f(x,&y)=(F-T)x-\mathcal {F}+\mathcal {T}\\ =&\begin{pmatrix} -(\gamma _1+\mu ) &{}\beta _1S_{01}^* &{}0 &{}0\\ \alpha U_{01}^* &{}-\nu &{}0 &{}0\\ 0 &{}0 &{}-(\gamma _2+\mu ) &{}\beta _2 S_{02}^*\\ 0 &{}0 &{}\alpha U_{02}^* &{}-\nu \\ \end{pmatrix} \begin{pmatrix} I_1\\ V_1\\ I_2\\ V_2\\ \end{pmatrix}-\begin{pmatrix} \beta _1S_1V_1\\ \alpha I_1 U_1\\ \beta _2S_2V_2\\ \alpha I_2U_2\ \end{pmatrix} + \begin{pmatrix} (\gamma _1+\mu )I_1 \\ \nu V_1\\ (\gamma _2+\mu )I_2 \\ \nu V_2\\ \end{pmatrix}, \\ =&\begin{pmatrix} \beta _1S_{01}^*V_1-(\gamma _1+\mu )I_1 \\ \alpha I_1 U_{01}^*-\nu V_1\\ \beta _2S_{02}^*V_2-(\gamma _2+\mu )I_2 \\ \alpha I_2 U_{02}^*-\nu V_2\\ \end{pmatrix}-\begin{pmatrix} \beta _1S_1V_1\\ \alpha I_1U_1\\ \beta _2S_2V_2\\ \alpha I_2 U_2\ \end{pmatrix}+ \begin{pmatrix} (\gamma _1+\mu )I_1 \\ \nu V_1\\ (\gamma _2+\mu )I_2 \\ \nu V_2\\ \end{pmatrix},\\ =&\begin{pmatrix} \beta _1V_1(S_{01}^*-S_1) \\ \alpha I_1(U_{01}^*-U_1)\\ \beta _2V_2(S_{02}^*-S_2) \\ \alpha I_2(U_{02}^*-U_2)\\ \end{pmatrix}. \end{aligned}$$

From the above, we note that \(f(x,y)\ge 0\), for (xy) in \(\Gamma .\)

We will built a Lyapunov function following Shuai and van den Driessche technique [26, 27]. For this, we consider the following matrix.

$$\begin{aligned} T^{-1}F=\begin{pmatrix} 0 &{} \frac{\beta _1 S_{01}^*}{\gamma _1+\mu }&{}0 &{}0\\ \dfrac{\alpha U_{01}^*}{\nu }&{}0 &{}0 &{}0\\ 0 &{}0 &{}0 &{}\frac{\beta _2 S_{02}^*}{\gamma _2+\mu }\\ 0 &{}0 &{}\frac{\alpha U_{02}^*}{\nu } &{}0\\ \end{pmatrix}. \end{aligned}$$

The characteristic polynomial of \(T^{-1}F\) is,

$$\begin{aligned} \left( \lambda ^2-\frac{\alpha \beta _1 S_{01}^* U_{01}^*}{(\gamma _1+\mu )\nu }\right) \left( \lambda ^2-\frac{\alpha \beta _2 S_{02}^* U_{02}^*}{(\gamma _2+\mu )\nu } \right) =0. \end{aligned}$$

Therefore the spectral radius of \(T^{-1}F\) is equal to

$$\begin{aligned} R_0=max(\sqrt{R_{01}},\sqrt{R_{02}}). \end{aligned}$$

where

$$\begin{aligned} R_{01}=\frac{\alpha \beta _1 S_{01}^* U_{01}^*}{(\gamma _1+\mu )\nu } \text{ and } R_{02}=\frac{\alpha \beta _2 S_{02}^* U_{02}^*}{(\gamma _2+\mu )\nu }. \end{aligned}$$

If \(w=(w_1,w_2,w_3,w_4)\) is a left eigenvector associated with the eigenvalue \(R_0\) of \(T^{-1}F\) then it satisfies the following equations.

$$\begin{aligned}&w_1=\frac{\alpha U_{01}^*}{R_0 \nu }w_2, \end{aligned}$$
(C2)
$$\begin{aligned}&w_3=\dfrac{\alpha U_{02}^*}{R_0 \nu }w_4, \end{aligned}$$
(C3)
$$\begin{aligned}&\Big (R_0-\dfrac{R_{01}}{R_0}\Big )w_2=0, \end{aligned}$$
(C4)
$$\begin{aligned}&\Big (R_0-\dfrac{R_{02}}{R_0}\Big )w_4=0. \end{aligned}$$
(C5)

We have three cases \(R_0=\sqrt{R_{01}}\) or \(R_0=\displaystyle \sqrt{R_{02}}\) with \(\displaystyle \sqrt{R_{01}} \ne \sqrt{R_{02}}\). And \(R_0=\displaystyle \sqrt{R_{01}}=\sqrt{R_{02}}\)

Case \(R_0=\sqrt{R_{01}}>\sqrt{R_{02}}.\)

From (C4), \(\Big (R_0-\dfrac{R_{01}}{R_0}\Big )=\Big (\sqrt{R_{01}}-\sqrt{R_{01}}\Big )=0.\)

From (C5), \(\Big (R_0-\dfrac{R_{02}}{R_0}\Big )=\dfrac{1}{\sqrt{R_{01}}}\Big (R_{01}-R_{02}\Big )\ne 0\) if \(R_{01} \ne R_{02}.\) Therefore \(w_4=0.\)

Taking \(w_2=1\) and substituting in (C2) and (C3) we have

$$\begin{aligned} w^T=\Big (\dfrac{\alpha U_{01}^*}{R_0\nu },1,0,0 \Big ). \end{aligned}$$

Since \(x^T=\left( I_1,V_1,I_2,V_2\right) ,\) we define the Lyapunov function as

$$\begin{aligned} Q_1(x)=w^T T^{-1} x=\dfrac{\alpha U_{01}^*I_1}{R_0 \nu (\gamma _1+\mu )}+\dfrac{V_1}{\nu }. \end{aligned}$$

It is clear that \(Q_1(x)\ge 0\) and \(Q_1(x)=0\) if and only if \(x=0.\)

Moreover,

$$\begin{aligned} \begin{aligned} \dot{Q_1}=&\dfrac{\alpha U_{01}^*\dot{I}_1}{R_0\nu (\gamma _1+\mu )}+\dfrac{\dot{V}_1}{\nu },\\ =&\dfrac{\alpha U_{01}^*}{R_0\nu (\gamma _1+\mu )}\Big (\beta _1 S_1V_1-I_1(\gamma _1+\mu )\Big )+\dfrac{1}{\nu }\Big (\alpha I_1U_1-\nu V_1\Big ),\\ =&\dfrac{\alpha U_{01}^*}{R_0\nu (\gamma _1+\mu )}\Big (\beta _1 S_{01}^*V_1-I_1(\gamma _1+\mu )-(S_{01}^*-S_1)\beta _1V_1\Big )\\&+\dfrac{1}{\nu }\Big (\alpha I_1U_{01}^*-\nu V_1-(U_{01}^*-U_1)\alpha I_1\Big ),\\ =&\dfrac{\alpha \beta _1S_{01}^* U_{01}^*}{\nu (\gamma _1+\mu )}\dfrac{V_1}{R_0}-\dfrac{\alpha U_{01}^*I_1}{R_0 \nu }+\dfrac{\alpha U_{01}^*I_1}{\nu }-V_1-A_1,\\ =&(R_0-1)V_1+(R_0-1)V_1\dfrac{\alpha U_{01}^*I_1}{R_0 \nu }-A_1,\\ =&(R_0-1)(V_1+\dfrac{\alpha U_{01}^* I_1}{R_0 \nu })-A_1. \end{aligned} \end{aligned}$$

where \(A_1=\left( S_{01}^*-S_1\right) \frac{\alpha U_{01}^*\beta _1V_1}{R_0\nu (\gamma _1+\mu )}+\left( U_{01}^*-U_1\right) \dfrac{\alpha I_1}{\nu }\ge 0\), since \((x,y) \in \Gamma .\)

Therefore \(\dot{Q_1}<0\) if \(R_0<1.\)

Case \(R_0=\sqrt{R_{02}}>\sqrt{R_{01}}.\)

In the same way as above, we have that the Lyapunov function is

$$\begin{aligned} Q_2(x)= & {} w^T T^{-1} x=\dfrac{\alpha U_{02}^*I_2}{R_0 \nu (\gamma _2+\mu )}+\dfrac{V_2}{\nu } \; \text{ and } \\ \dot{Q_2}= & {} (R_0-1)(V_2+\dfrac{\alpha U_{02}^* I_2}{R_0 \nu })-A_2<0, \; \text{ if } R_0<1 , \end{aligned}$$

where \(A_2=\left( S_{02}^*-S_2\right) \frac{\alpha U_{02}^*\beta _2V_2}{R_0\nu (\gamma _2+\mu )}+\left( U_{02}^*-U_2\right) \dfrac{\alpha I_2}{\nu }\ge 0\), since \((x,y) \in \Gamma .\)

Case \(R_0=\sqrt{R_{01}}=\sqrt{R_{02}}.\)

The left eigenvector associated with the eigenvalue \(R_0\) of \(T^{-1}F\) is

$$\begin{aligned} w^T=\Big (\dfrac{\alpha U_{01}^*}{R_0\nu },1,\dfrac{\alpha U_{02}^*}{R_0\nu },1 \Big ). \end{aligned}$$

From above we have that

$$\begin{aligned} Q(x)=w^T T^{-1} x=\dfrac{\alpha U_{01}^*I_1}{R_0 \nu (\gamma _1+\mu )}+\dfrac{V_1}{\nu } +\dfrac{\alpha U_{02}^*I_2}{R_0 \nu (\gamma _2+\mu )}+\dfrac{V_2}{\nu }=Q_1(x)+Q_2(x), \end{aligned}$$

is a Lyapunov function. Moreover \(\dot{Q}<0\) since \((x,y) \in \Gamma .\)

Therefore \(P_0\) is globally asymptotically stable if \(R_0<1.\)

Appendix D: Stability at \(P_1\) or \(P_2\)

The characteristic polynomial of Jacobian matrix evaluated at the equilibrium point \(P_{1}\) is

$$\begin{aligned}&\frac{1}{\nu }(L+\mu ) (L+\nu ) (L+\gamma _1+\mu ) (L+\gamma _2+\mu ) (L+\mu +m_{12}) (L+\mu +m_{21}) (L+\mu + \beta _{12} \rho _2 V_{12}^{*}) \Big (L ^2 \nu + L\nu (\gamma _1+\mu +\nu )\\&\quad +\nu ^2 (\gamma _1+\mu )- \alpha \Omega _1 (\beta _1 S_{11}^{*}+\beta _{21} \rho _{1} Z_{121}^{*}) \Big )\\&\quad \Big (L^4+q_1 L^3 +q_2 L^2 +q_3 L +q_4\Big )=0. \end{aligned}$$

Where

$$\begin{aligned} q_1= & {} \gamma _2+\alpha I_{22}^{*}+3 \mu +\nu +m_{12}+m_{21}+\beta _2 V_{12}^{*},\\ q_2= & {} 2 \gamma _2 \mu +\alpha I_{22}^{*} (\gamma _2+3 \mu +m_{12}+m_{21}\\&+ \, \beta _2 V_{12}^{*})+3 \mu ^2+2 \mu \nu +m_{12} (\gamma _2+2 \mu +\nu +\beta _2 V_{12}^{*})\\&+\, \gamma _2 m_{21}+2 \mu m_{21}+\nu m_{21}+\beta _2 \gamma _2 V_{12}^{*}+2 \beta _2 \mu V_{12}^{*}+\beta _2 \nu V_{12}^{*},\\ q_3= & {} \alpha I_{22}^{*} \Big (3 \mu ^2+\gamma _2 m_{12}+2 \mu (\gamma _2+m_{12}+m_{21}\\&+\, \beta _2 V_{12}^{*})+\beta _2 m_{12} V_{12}^{*}+\gamma _2 m_{21}+\beta _2 \gamma _2 V_{12}^{*}\Big )\\&+\, m_{12} (\gamma _2+\mu +\nu ) (\mu +\beta _2 V_{12}^{*})+\nu (\mu (\mu +m_{21})\\&+ \, \beta _2 V_{12}^{*} (\gamma _2+2 \mu ))+\mu (\gamma _2+\mu ) (\mu +m_{21}+\beta _2 V_{12}^{*}),\\ q_4= & {} (\gamma _2+\mu ) (\alpha I_{22}^{*} (m_{12} (\mu +\beta _2 V_{12}^{*})+\mu (\mu +m_{21}\\&+\beta _2 V_{12}^{*}))+\beta _2 \nu V_{12}^{*} (\mu +m_{12})). \end{aligned}$$

Note that \(q_1, q_2, q_3, q_4 \in \mathbb {R}^{+}\) and

$$\begin{aligned} D_2= & {} q_1 q_2-q_3=\alpha ^2 I_{22}^{*2} (\gamma _2+3 \mu +m_{12}+m_{21}+\beta _2 V_{12}^{*})+\alpha I_{22}^{*} \left( \nu (\gamma _2+5 \mu +2 m_{12}+2 m_{21}+ 2 \beta _2 V_{12}^{*})\right. \\&\left. +\, (\gamma _2+3 \mu +m_{12}+m_{21}+\beta _2 V_{12}^{*})^2\right) +m_{12}^2(\gamma _2+2 \mu +\nu +\beta _2 V_{12}^{*})+m_{12}\left( m_{21} (2 (\gamma _2+2 \mu +\nu )\right. \\&\left. +\, \beta _2 V_{12}^{*})+(\gamma _2+2 \mu +\nu +\beta _2 V_{12}^{*}) (\gamma _2+4 \mu +\nu +\beta _2 V_{12}^{*})\right) +\nu \left( 8 \mu ^2+m_{21}^2+2 m_{21} (\gamma _2+3 \mu +\beta _2 V_{12}^{*})\right. \\&\left. +\, \mu (4 \gamma _2+5 \beta _2 V_{12}^{*})+\beta _2 V_{12}^{*} (\gamma _2+\beta _2 V_{12}^{*})\right) +(\gamma _2+2 \mu ) (2 \mu +m_{21}+\beta _2 V_{12}^{*}) (\gamma _2+2 \mu +m_{21}+\beta _2 V_{12}^{*})+\nu ^2 (2 \mu +m_{21}+\beta _2 V_{12}^{*})>0. \end{aligned}$$

Using Mathematica we obtain

$$\begin{aligned} D_3= & {} \left( V_{12}^{*2}(\gamma _2+\mu +\nu ) \beta _2^2+V_{12}^{*} \left( \gamma _2^2+(4 \mu +\nu ) \gamma _2+3 \mu ^2+\nu ^2+3\mu \nu \right) \beta _2\right. \\&\left. +\,\mu (\gamma _2+\mu +\nu ) (\gamma _2+2\mu +\nu )\right) m_{12}^3+\left( (V_{12}^{*} \beta _2+\gamma _2+5 \mu +\nu ) \left( V_{12}^{*2} (\gamma _2+\mu +\nu ) \beta _2^2\right. \right. \\&\left. \left. +\,V_{12}^{*} \left( \gamma _2^2+4 \mu \gamma _2+\nu \gamma _2+3 \mu ^2+\nu ^2+3 \mu \nu \right) \beta _2+\mu (\gamma _2+\mu +\nu ) (\gamma _2+2 \mu +\nu )\right) \right. \\&\left. +\,m_{21} \left( V_{12}^{*2} (\gamma _2+\mu +\nu ) \beta _2^2+2 V_{12}^{*} \left( \gamma _2^2+4 \mu \gamma _2+\nu \gamma _2+3 \mu ^2+\nu ^2+3 \mu \nu \right) \beta _2\right. \right. \\&\left. \left. +\,3 \mu (\gamma _2+\mu +\nu ) (\gamma _2+2 \mu +\nu )\right) \right) m_{12}^2\\&+\left( \left( 3 \mu (\gamma _2+\mu +\nu ) (\gamma _2+2 \mu +\nu )+V_{12}^{*} \beta _2 \left( \gamma _2^2+4 \mu \gamma _2+\nu \gamma _2+3 \mu ^2+\nu ^2+3 \mu \nu \right) \right) m_{21}^2\right. \\&\left. +\, \left( (V_{12}^{*} \beta _2+2 \mu ) \nu ^3+\left( 16 \mu ^2+(13 V_{12}^{*} \beta _2+6 \gamma _2) \mu +V_{12}^{*} \beta _2 (2 V_{12}^{*} \beta _2+3 \gamma _2)\right) \nu ^2\right. \right. \\&\left. \left. +\,(V_{12}^{*} \beta _2+2 \mu ) \left( 17 \mu ^2+(7 V_{12}^{*} \beta _2+16 \gamma _2) \mu +3 \gamma _2 (V_{12}^{*} \beta _2+\gamma _2)\right) \nu \right. \right. \\&\left. +\,(\gamma _2+\mu ) (2 V_{12}^{*} \beta _2+\gamma _2+5 \mu ) (2 \mu (\gamma _2+2 \mu )+V_{12}^{*} \beta _2 (\gamma _2+3 \mu ))\right) m_{21}\\&+\,(V_{12}^{*} \beta _2 (\gamma _2+3 \mu +\nu )+\mu (3 \gamma _2+8 \mu +3 \nu )) \left( V_{12}^{*2} (\gamma _2+\mu +\nu ) \beta _2^2\right. \\&\left. \left. +\,V_{12}^{*} \left( \gamma _2^2+4 \mu \gamma _2+\nu \gamma _2+3 \mu ^2+\nu ^2+3 \mu \nu \right) \beta _2+\mu (\gamma _2+\mu +\nu ) (\gamma _2+2 \mu +\nu )\right) \right) m_{12}\\&+\,I_{22}^{*3} \alpha ^3 (m_{12}+m_{21}+V_{12}^{*} \beta _2+2 \mu ) (m_{12} (V_{12}^{*} \beta _2+\gamma _2+2 \mu )+(\gamma _2+2 \mu ) (m_{21}\\&+\,V_{12}^{*} \beta _2+\gamma _2+2 \mu ))+\left( (m_{21}+V_{12}^{*} \beta _2+\mu ) \nu ^2\right. \\&\left. +\,\left( m_{21}^2+2 (V_{12}^{*} \beta _2+\gamma _2+2 \mu ) m_{21}+3 \mu ^2+V_{12}^{*} \beta _2 (V_{12}^{*} \beta _2+\gamma _2)+(3 V_{12}^{*} \beta _2+2 \gamma _2) \mu \right) \nu \right. \\&\left. +\,(m_{21}+V_{12}^{*} \beta _2+\mu ) (\gamma _2+\mu ) (m_{21}+V_{12}^{*} \beta _2+\gamma _2+2 \mu )\right) \left( 2 (\gamma _2+2 \mu +\nu ) \mu ^2+m_{21} (\gamma _2+2 \mu +\nu ) \mu \right. \\&\left. +\,V_{12}^{*} \beta _2 (\gamma _2+2 \mu ) (\mu +\nu )\right) +I_{22}^{*2} \alpha ^2 \left( (V_{12}^{*} \beta _2+\gamma _2+2 \mu ) m_{12}^3\right. \\&+\,\left( 2 V_{12}^{*2} \beta _2^2+V_{12}^{*} (4 \gamma _2+11 \mu +3 \nu ) \beta _2+2 \gamma _2^2+14 \mu ^2+11 \gamma _2 \mu +m_{21} (2 V_{12}^{*} \beta _2+3 \gamma _2+6 \mu )\right. \\&\left. +\,2 \gamma _2 \nu +5 \mu \nu \right) m_{12}^2+\left( V_{12}^{*3} \beta _2^3+V_{12}^{*2} (4 \gamma _2+11 \mu +3 \nu ) \beta _2^2\right. \\&\left. +\,2 V_{12}^{*} \left( 2 \gamma _2^2+2 (6 \mu +\nu ) \gamma _2+\mu (17 \mu +8 \nu )\right) \beta _2+\gamma _2^3+32 \mu ^3+34 \gamma _2 \mu ^2+11 \gamma _2^2 \mu \right. \\&\left. +\,m_{21}^2 (V_{12}^{*} \beta _2+3 \gamma _2+6 \mu )+\left( \gamma _2^2+10 \mu \gamma _2+18 \mu ^2\right) \nu +m_{21} \left( 2 V_{12}^{*2} \beta _2^2+V_{12}^{*} (7 \gamma _2+17 \mu +3 \nu ) \beta _2\right. \right. \\&\left. \left. +\,4 \gamma _2^2+28 \mu ^2+22 \gamma _2 \mu +4 \gamma _2 \nu +10 \mu \nu \right) \right) m_{12}\\&+\,m_{21}^3 (\gamma _2+2 \mu )+(V_{12}^{*} \beta _2+2 \mu ) (\gamma _2+2 \mu ) (V_{12}^{*} \beta _2+\gamma _2+2 \mu ) (V_{12}^{*} \beta _2+\gamma _2+3\mu )\\&+\,m_{21} (\gamma _2+2 \mu ) \left( 3 V_{12}^{*2} \beta _2^2+2 V_{12}^{*} (2 \gamma _2+7 \mu ) \beta _2+\gamma _2^2+16 \mu ^2+9 \gamma _2 \mu \right) \\&+\,\left( 3 V_{12}^{*2} (\gamma _2+2 \mu ) \beta _2^2+V_{12}^{*} (\gamma _2+4 \mu ) (2 \gamma _2+5 \mu ) \beta _2+2 \mu (\gamma _2+2 \mu ) (\gamma _2+4 \mu )\right) \nu +m_{21} \left( \gamma _2^2+10 \mu \gamma _2+18 \mu ^2+V_{12}^{*} \beta _2 (5 \gamma _2+11 \mu )\right) \nu \\&\left. +\,m_{21}^2 ((\gamma _2+2 \mu ) (3 V_{12}^{*} \beta _2+2 \gamma _2+7 \mu )+(2 \gamma _2+5 \mu ) \nu )\right) +I_{22}^{*} \alpha \left( \left( (V_{12}^{*} \beta _2+\gamma _2+2 \mu )^2+(2 V_{12}^{*} \beta _2+\gamma _2+3 \mu ) \nu \right) m_{12}^3+\left( (3 V_{12}^{*} \beta _2+\gamma _2+4 \mu ) \nu ^2+\left( m_{21} (4 V_{12}^{*} \beta _2+3 \gamma _2+9 \mu )+2 \left( 2 V_{12}^{*2} \beta _2^2\right. \right. \right. \right. \\&\left. \left. +\,V_{12}^{*} (3 \gamma _2+10 \mu ) \beta _2+\gamma _2^2+11 \mu ^2+7 \gamma _2 \mu \right) \right) \nu \\&\left. +\,(V_{12}^{*} \beta _2+\gamma _2+2 \mu ) \left( V_{12}^{*2} \beta _2^2+3 V_{12}^{*} \gamma _2 \beta _2+\gamma _2^2+11 \mu ^2+8 (V_{12}^{*} \beta _2+\gamma _2) \mu +m_{21} (V_{12}^{*} \beta _2+3 \gamma _2+6 \mu )\right) \right) m_{12}^2 \end{aligned}$$
$$\begin{aligned}&+\,\left( 2 V_{12}^{*3} (\gamma _2+2 \mu +\nu ) \beta _2^3+V_{12}^{*2} \left( 4 \gamma _2^2+22 \mu \gamma _2+6 \nu \gamma _2+27 \mu ^2+3 \nu ^2+20 \mu \nu \right) \beta _2^2\right. \\&+\,V_{12}^{*} \left( 2 (\gamma _2+7 \mu ) \nu ^2+(3 \gamma _2+7 \mu ) (\gamma _2+8 \mu ) \nu +2 \left( \gamma _2^3+11 \mu \gamma _2^2+33 \mu ^2 \gamma _2+29 \mu ^3\right) \right) \beta _2\\&+\,\mu \left( 4 \gamma _2^3+27 \mu \gamma _2^2+58 \mu ^2 \gamma _2+40 \mu ^3+(4 \gamma _2+13 \mu ) \nu ^2+8 (\gamma _2+2 \mu ) (\gamma _2+3 \mu ) \nu \right) \\&+\,m_{21}^2 \left( 2 V_{12}^{*} \beta _2 (\gamma _2+2 \mu +\nu )+3 \left( (\gamma _2+2 \mu )^2+(\gamma _2+3 \mu ) \nu \right) \right) \\&+\,m_{21} \left( 4 V_{12}^{*2} (\gamma _2+2 \mu +\nu ) \beta _2^2+V_{12}^{*} \left( 7 \gamma _2^2+34 \mu \gamma _2+39 \mu ^2+3 \nu ^2+10 (\gamma _2+3 \mu ) \nu \right) \beta _2\right. \\&+\,2 \left( \gamma _2^3+10 \mu \gamma _2^2+27 \mu ^2 \gamma _2+22 \mu ^3+(\gamma _2+4 \mu ) \nu ^2\right. \\&\left. \left. \left. +\,2 \left( \gamma _2^2+7 \mu \gamma _2+11 \mu ^2\right) \nu \right) \right) \right) m_{12}\\&+\,\left( 3 V_{12}^{*2} (\gamma _2+2 \mu ) \beta _2^2+V_{12}^{*} (\gamma _2+4 \mu )^2 \beta _2+2 \mu ^2 (2 \gamma _2+5 \mu )\right) \nu ^2\\&+\,(V_{12}^{*} \beta _2+2 \mu ) (\gamma _2+2 \mu ) (V_{12}^{*} \beta _2+\gamma _2+2 \mu ) (V_{12}^{*} \beta _2 (\gamma _2+2 \mu )+\mu (2 \gamma _2+3 \mu )) \end{aligned}$$
$$\begin{aligned}&+\,(V_{12}^{*} \beta _2+\gamma _2+2 \mu ) \left( 16 \mu ^3+8 (2 V_{12}^{*} \beta _2+\gamma _2) \mu ^2\right. \\&\left. +\,V_{12}^{*} \beta _2 (4 V_{12}^{*} \beta _2+9 \gamma _2) \mu +V_{12}^{*} \beta _2 \gamma _2 (2 V_{12}^{*} \beta _2+\gamma _2)\right) \nu +m_{21}^3 \left( (\gamma _2+2 \mu )^2+(\gamma _2+3 \mu ) \nu \right) \\&+\,m_{21}^2 \left( (\gamma _2+4 \mu ) \nu ^2+2 \left( \gamma _2^2+7 \mu \gamma _2+11 \mu ^2+V_{12}^{*} \beta _2 (2 \gamma _2+5 \mu )\right) \nu +(\gamma _2+2 \mu ) \left( \gamma _2^2+8 \mu \gamma _2+11 \mu ^2\right. \right. \\&\left. \left. +\,3 V_{12}^{*} \beta _2 (\gamma _2+2 \mu )\right) \right) +m_{21} \left( (2 V_{12}^{*} \beta _2 (2 \gamma _2+5 \mu )+\,\mu (4 \gamma _2+13 \mu )) \nu ^2\right. \\&+\,\left( V_{12}^{*2} (5 \gamma _2+11 \mu ) \beta _2^2+V_{12}^{*} \left( 5 \gamma _2^2+31 \mu \gamma _2+46 \mu ^2\right) \beta _2+8 \mu (\gamma _2+2 \mu ) (\gamma _2+3 \mu )\right) \nu \\&+\,(\gamma _2+2 \mu ) \left( 3 V_{12}^{*2} (\gamma _2+2 \mu ) \beta _2^2\right. \\&\left. \left. \left. +\,2 V_{12}^{*} \left( \gamma _2^2+8 \mu \gamma _2+11 \mu ^2\right) \beta _2+\mu \left( 4 \gamma _2^2+19 \mu \gamma _2+20 \mu ^2\right) \right) \right) \right) , \end{aligned}$$

which is always positive.

\(D_4=q_4D_3>0.\)

By the Routh-Hurwitz criterion [30], we obtain that all roots of \(L^4+q_1 L^3 +q_2 L^2 +q_3 L +q_4\) have negative real part. On the other hand

$$\begin{aligned} \nu ^2 (\gamma _1+\mu )-\alpha \Omega _1 (\beta _1 S_{11}^{*}+\beta _{21} \rho _{1} Z_{121}^{*})>0, \end{aligned}$$

if

$$\begin{aligned}&\frac{\alpha \Omega _1 (\beta _1 S_{11}^{*}+\beta _{21} \rho _{1} Z_{121}^{*})}{\nu ^2 (\gamma _1+\mu )}\\&\quad =R_1\left( \frac{S_{11}^*}{S_{01}^*}+\frac{\rho _1\beta _{21}Z_{121}^*}{\beta _1S_{01}^*}\right)&<1. \end{aligned}$$

By the Routh-Hurwitz criterion, we obtain that all roots of quadratic polynomial have negative real part.

Therefore, if \(R_1\left( \frac{S_{11}^*}{S_{01}^*}+\frac{\rho _1\beta _{21}Z_{121}^*}{\beta _1S_{01}^*}\right) <1\) then \(P_1\) is locally asymptotically stable.

In the same way, we have that if \(R_2\left( \frac{S_{22}^*}{S_{02}^*}+\frac{\rho _2\beta _{12}Z_{212}^*}{\beta _2 S_{02}^*} \right) <1\) then \(P_2\) is locally asymptotically stable at \(\Gamma .\)

Appendix E: Expressions for \(F_1\) and \(F_2\)

$$\begin{aligned} F_1(m_{21})= & {} \Big (m_{21} (m_{21} (m_{21} (3.04787\times 10^{204} m_{21}+6.0108\times 10^{204})+2.7477\times 10^{204})\\&-\,6.2832\times 10^{202})+3.6616\times 10^{200}\Big ) ^{\frac{1}{2}}\Big ( (8.5094\times 10^{-50} m_{21}+3.4102\times 10^{-52}) m_{21}\\&+\,2.5976\times 10^{-57}\Big ) +4.9705\times 10^{43}-1.4856\times 10^{53} m_{21}^4-1.4122\times 10^{53} m_{21}^3\\&+\,1.0647\times 10^{51} m_{21}^2+6.5213\times 10^{48} m_{21},\\ F_2(m_{21})= & {} m_{21} \Big (m_{21}(2.2879\times 10^{53} m_{21}+9.1691\times 10^{50})+6.9841\times 10^{45}\Big ). \end{aligned}$$

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vinagre, M.R., Blé, G. & Esteva, L. Dynamical Analysis of a Model for Secondary Infection of the Dengue. Differ Equ Dyn Syst (2023). https://doi.org/10.1007/s12591-022-00628-5

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12591-022-00628-5

Keywords

Mathematics Subject Classification

Navigation