Abstract
A non-linear mechanistic model for the transmission dynamics of HIV/AIDS is developed and analyzed. The model classified the infected individuals based on their CD4 count level. Furthermore, education campaign, voluntary testing and counseling and treatment are considered as intervention strategies for controlling the disease. The analysis of the model reveals that imperfect public enlightenment campaign can induce backward bifurcation. It has been shown that when public enlightenment campaign is \(100\%\) effective, the disease free equilibrium is globally asymptotically stable for \(R_{eff} \le 1\), whereas for \(R_{eff} > 1\) the global stability of the endemic equilibrium is proved only in a special case. Time dependent controls of the intervention strategies mentioned above are incorporated into the model and the optimal control strategies with minimal implementation cost are identified. In addition, cost effectiveness analysis in the form of incremental cost effectiveness ratio is carried-out to identify the most cost effective strategies. The results suggest that out of the three non dominated strategies, the strategy of educating the newly entrants only or combination of newly entrants and susceptible individuals is very cost effective using per capita GDP of Nigeria as at 2018. However, the choice of which strategy to implement depends on budgetary allocation and resource availability.
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Appendix
Appendix
Proof of Theorem 4
To show the existenceof backward bifurcation in model (3) when \({\mathcal {R}}_{eff} = 1\), center manifold theorem is used as in Elbasha and Gumel (2006), Hussaini et al. (2011).
Consider model (3) as
where \(\phi \) is the bifurcation parameter and f is a continuously differentiable at least twice (both in x and \(\phi \)).
For ease of notation, let \(S_u=x_{1}\), \(S_e=x_{2}\), \(H_u=x_{3}\), \(H_a=x_{4}\), \(H_{ul}=x_{5}\) , \(H_t=x_{6}\), \(A_u=x_{7}\), and \(A_t=x_{8}\), thus \(N(t)= x_{1} +x_{2} +x_{3}+x_{4}+x_{5}+x_{6}+x_{7}+x_{8}\).
with force of infection \(\lambda \) defined as
where \(\theta \) and \(W_i, \quad i=0,1,2,\ldots , 6\) are defined in (9)
Now, consider the case when \({\mathcal {R}}_{eff}=1\). Suppose, that \(\beta \) is choosen as a bifurcation parameter, then solving for \(\beta \), we have
Then, the jacobian of \(f=(f_1,f_2,f_3,f_4,f_5,f_6,f_7,f_8)^T\) evaluated around disease free equilibrium \((E_0)\) denoted by \(J(E_0)_{\beta ^{c}}\) is given by:
where \(C_0=\beta ^{c}\,\eta _{{1}}\), \(C_1=\beta ^{c}\,\theta \,\eta _{{2}}\), \(C_2=\beta ^{c}\,\eta _{{4}}\), \(C_3=\beta ^{c}\,\theta \,\eta _{{3}}\), \(C_4=\beta ^{c}\,\theta \,\)\(Z_{{1}}={\frac{ \left( 1-p \right) \mu }{\mu +\xi }}\) \(Z_{{2}}={\frac{ \left( 1-k \right) \left( \mu \,p+\xi \right) }{\mu +\xi }}\) \(Z_{{3}}=Z_1+Z_2\) The Jacobian \(J(E_0)_{\beta ^{c}}\) of the linearized system (45) has a simple zero eigenvalue (meaning that the remaining eigenvalues have negative real part). Hence, by center manifold theorem developed in Castillo-Chavez and Song (2004), it is possible to analyze the dynamics of the system (45) within \(\beta =\beta ^{c}\).
Eigenvectors of \(J(E_0)_{\beta ^{c}}\):
Let \(w = [w_1, w_2, w_3, w_4, w_5, w_6, w_7, w_8]^T\) and \(v = [v_1, v_2, v_3, v_4, v_5, v_6, v_7, v_8]\) be the right and left eigenvectors respectively, associated with the zero eigenvalue of the Jacobian of linearized system \(J(E_0)_{\beta ^{c}}\), defined by
with \(v\cdot w=1\)
Following theorem 4.1 in Castillo-Chavez and Song (2004), we compute the associated backward bifurcation parameters a and b that are responsible for the direction of bifurcation,
After computing the non-zero second order partial derivatives of f as defined in (45), and evaluate around diseases free \(E_0\), we obtain:
and
where,
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\(L_1=k\left( (\xi +p\mu )W_{11}-w_2k\mu (1-p) \right) \)
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\(L_2=W_{11}(\mu +\xi )-(\xi +p\mu )w_1 k\)
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\(W_{11}=w_{{3}}+w_{{4}}+w_{{5}}+w_{{6}}+w_{{7}}+w_{{8}}\)
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\(W_{12}=\left( \theta \,\eta _{{2}}w_{{4}}+\theta \,\eta _{{3}}w_{{8}}+\theta \,\eta _{{5}} w_{{6}}+\eta _{{1}}w_{{3}}+\eta _{{4}}w_{{7}}+w_{{5}} \right) \)
Since, \(0\le k,p \le 1\), then \((1-kp)\ge 0\), implies \(b>0\). Hence, backward bifurcation exist only if \(a>0\). \(\square \)
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Ishaku, A., Gazali, A.M., Abdullahi, S.A. et al. Analysis and optimal control of an HIV model based on CD4 count. J. Math. Biol. 81, 209–241 (2020). https://doi.org/10.1007/s00285-020-01508-8
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DOI: https://doi.org/10.1007/s00285-020-01508-8