Abstract
In recent times, several infectious diseases that breakthrough contagiousness in vaccinated people and reinfections in primarily infected counterparts have become more common. In most cases, reinfection occurs as a result of viral mutations. The mutated pathogens may possess alternate modes of transmission, and even the exposure period may vary in some cases. Hence, to gain a deeper understanding of disease transmission dynamics, it becomes eminent to incorporate a dedicated compartment for reinfection within a mathematical model. To account for these vital factors, this research presents an epidemic model that includes a specific compartment for individuals experiencing reinfection. The model also incorporates two separate time delay parameters that account for the incubation periods for the initial infection and the subsequent reinfection. The study reveals that the system exhibits forward bifurcation with respect to the parameter \(\beta _1\) in the absence of time delays. However, in the presence of time delay, Hopf bifurcation is identified when the delays exceed corresponding cut-off values. The research further highlights that an extension in the exposure period leads to a rise in the reinfected population, thereby contributing to the persistence of the disease over an extended timeframe. To demonstrate the practical applicability of the proposed model, we have fitted our model with the data of real-time vaccination cases for COVID-19 in India. Notably, the constructed model can be readily adapted for other infectious diseases by selecting appropriate parameter values based on pertinent real-time data. The theoretical results are validated via numerical simulation.
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Data availability statement
The data that support the findings of this study are openly available from the website https://github.com/owid/covid-19-data/blob/master/public/data/vaccinations/country_data/India.csv#L1.
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Acknowledgements
The research work of P. Tamilalagan and B. Krithika is supported by National Board for Higher Mathematics, Department of Atomic Energy, Mumbai, India under the Grant no. 02011/8/2020/NBHM/R &D-II/8071.
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Appendices
Appendix 1
Appendix 2
Proof of Theorem 3(c)
For \(\tau _1=0\), the Eq. (11) becomes
where
If \(\lambda =im\) is a root of the Eq. (19), we obtain
Where,
Let \(m^2=t\). Then Eq. (20) becomes
Consider that Hypothesis 2: \(t_{20}\) is a positive root of Eq. (21). Then Eq. (20) has a positive root \(m_{20}=\sqrt{t_{20}}\) and further we obtain the following
with
Also, we obtain, Re\([d\lambda /d\tau _2]^{-1}_{\lambda =im_{20}}\ne 0\) if \(\left. \varUpsilon _2^{'}(t)=\frac{d\varUpsilon _2(t)}{dt}\right| _{t=t_{20}}\ne 0\) holds, where \(\varUpsilon _2(t)=t^5+P_{61}t^4+P_{62}t^3+P_{63}t^2+P_{64}t+P_{65}.\) Thus according to the Hopf bifurcation theorem in [45], the system undergoes Hopf bifurcation whenever the above transversality condition holds. \(\hfill\square\)
Proof of Theorem 3(d)
When \(\tau _1=\tau _2=\tau >0\), the Eq. (11) becomes
where
Multipliying \(e^{\lambda \tau }\) on both sides of Eq. (22), we get the following
Let \(\lambda =im\) is a root of the Eq. (23), then we get the following equations
Where,
From the above set of equations, we obtain,
with,
Where we obtain the following equation,
We consider the Hypothesis 3: \(m_{0}\) is a positive root of Eq. (25). If the Hypothesis 3 holds, then, we arrive at the following
Following in similar manner as in the above cases, we see that Re\([d\lambda /d\tau ]^{-1}_{\lambda =im_{30}}\ne 0\) if \(\left. \varUpsilon _3^{'}(t)=\frac{d\varUpsilon _3(t)}{dt}\right| _{t=t_{0}}\ne 0\) holds, where \(\varUpsilon _3(t)=t^5+P_{71}t^4+P_{72}t^3+P_{73}t^2+P_{74}t+P_{75}.\) with \(P_{71}=-{A_{{31}}}^{2}+2\,{\alpha _{{11}}}^{2}-4\,\alpha _{{12}}\), \(P_{72}=2M_{{33}} \left( \alpha _{{15}}-f_{{14}} \right) \left( \alpha _{{14} }-f_{{13}} \right) A_{{35}}+2\, \left( \alpha _{{15}}+f_{{14}} \right) A_{{35}}M_{{33}} \left( -\alpha _{{14}}-f_{{13}} \right)\), \(P_{73}=- \left( \alpha _{{14}}-f_{{13}} \right) A_{{33}}+ \left( -\alpha _{{12} }+f_{{11}} \right) A_{{35}}\), \(P_{74}=- \left( \alpha _{{15}}+f_{{14}} \right) A_{{31}}+ \left( -\alpha _{{13} }-f_{{12}} \right) A_{{33}}-\alpha _{{11}}A_{{35}}\) and \(P_{75}=2\,\alpha _{{11}} \left( -\alpha _{{13}}+f_{{12}} \right)\). Thus according to the Hopf bifurcation theorem in [45], we determine the existence of Hopf bifurcation whenever the Hypothesis 3 and the above transversality condition holds. \(\hfill\square\)
Proof of Theorem 3(e)
When \(\tau _1\ge 0\) and \(\tau _2\in (0,\tau _{20})\). Letting \(\lambda =im\) in Eq. (11) and simplifying further we obtain
Where,
By simple calculation, we obtain the following characteristic equation
where,
We consider the Hypothesis 4: \(m_{100}\) is a positive root of Eq. (30). If the Hypothesis 4 holds, then, we arrive at the following
Following in similar manner as in the above cases, we see that Re\([d\lambda /d\tau ]^{-1}_{\lambda =im_{100}}\ne 0\) if \(\left. \varUpsilon _4^{'}(t)=\frac{d\varUpsilon _4(t)}{dt}\right| _{t=t_{0}}\ne 0\) holds, where \(\varUpsilon _4(t)=t^5+P_{81}t^4+P_{82}t^3+P_{83}t^2+P_{84}t+P_{85}\). Thus according to the Hopf bifurcation theorem in [45], we determine the existence of Hopf bifurcation whenever the Hypothesis 4 and the above transversality condition holds. \(\hfill\square\)
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Krithika, B., Tamilalagan, P. Unveiling the spread of epidemics involving partial immunity and reinfection: insights from a time-delayed mathematical model. Eur. Phys. J. Spec. Top. 232, 2657–2673 (2023). https://doi.org/10.1140/epjs/s11734-023-00995-2
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DOI: https://doi.org/10.1140/epjs/s11734-023-00995-2