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Optimal time to intervene: The case of measles child immunization

  • * Corresponding author: Zuzana Chladná

    * Corresponding author: Zuzana Chladná
Abstract / Introduction Full Text(HTML) Figure(5) / Table(3) Related Papers Cited by
  • The recent measles outbreaks in US and Germany emphasize the importance of sustaining and increasing vaccination rates. In Slovakia, despite mandatory vaccination scheme, decrease in the vaccination rates against measles has been observed in recent years. Different kinds of intervention at the state level, like a law making vaccination a requirement for school entry or education and advertising seem to be the only strategies to improve vaccination coverage. This study aims to analyze the economic effectiveness of intervention in Slovakia. Using real options techniques we determine the level of vaccination rate at which it is optimal to perform intervention. We represent immunization rate of newborns as a stochastic process and intervention as a one-period jump of this process. Sensitivity analysis shows the importance of early intervention in the population with high initial average vaccination coverage. Furthermore, our numerical results demonstrate that the less certain we are about the future development of the immunization rate of newborns, the more valuable is the option to intervene.

    Mathematics Subject Classification: Primary: 91B70; Secondary: 90C15.


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  • Figure 1.  Measles in Slovakia: number of cases and immunization rate of newborns. Source: [19] and [9].

    Figure 2.  Time development of the average vaccination coverage under different evolution scenarios of immunization rate of newborns.

    Figure 3.  Expected costs as function of initial average vaccination coverage (left) and initial immunization rate of newborns (right), respectively.

    Figure 4.  Optimal decisions for different levels of intervention costs: grey = do intervene, black = do not intervene, $t=10$, $\sigma = 0.057$.

    Figure 5.  Value of the option to intervene. Initial immunization rate of newborns $90\%$ and initial average vaccination coverage $95\%$.

    Table 1.  Model inputs.

    Time horizon $T=20$ years
    Population size $N=400000$
    Reproduction number $R_0=17$
    Recovery rate $\gamma=0.1$
    Birth/death rate $\mu=0.01$
    Expected cases $a_0=0.9789$$ N$, $a_1=1.04$
    Costs per measles case $c_0=600$€
    Intervention costs $P\in \langle 0,500000 \rangle $€
    Probability of potential outbreak $p_{epi}=0.1$
    Drift term of immunization rate of newborns $\alpha = 0.0076$
    Volatility of immunization rate of newborns $\sigma = 0.057$
    Discount rate $r=1\%$
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    Table 2.  Savings induced by intervention.

    intervention costs(in thousands of €) savings in exp. costs inital average vacc coverage savings in expected costs
    0 8.8% 92% 2.3%
    2 6.7% 93% 2.9%
    4 4.0% 94% 4.4%
    8 3.5% 95% 55.9%
    10 2.3% 96% 72.5%
    20 2.0% 97% 78.6%
    30 1.8% 98% 79.9%
    (A) Initial immunization rate of newborns $90\%$, initial average vaccination coverage $92\%$, $\sigma =0.057$. (B) Initial immunization rate of newborns $90\%$, initial coverage 10000€, $\sigma =0.057$.
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    Table 3.  Expected time of first intervention and the expected number of interventions. Intervention costs $P=10000$€, initial average vaccination coverage $\bar x=95\%$ and $\sigma=0.057$.

    Initial immunization rate of newborns Time of first intervention Number of interventionss
    expected s.e. expected s.e.
    $90\%$ 6.87 3.79 3.48 3.05
    $91\%$ 6.89 3.86 3.20 2.79
    $92\%$ 7.92 4.26 3.36 2.81
    $93\%$ 7.92 4.34 3.10 2.68
    $94\%$ 7.96 4.44 2.89 2.51
    $95\%$ 9.19 4.13 3.19 2.71
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