  How to prevent the spread of human diseases is a great challenge for the
scientific community and so far there are many studies in which immunization
strategies have been developed. However, these kind of strategies usually do
not consider that medical institutes may have limited vaccine resources
available. In this manuscript, we explore the Susceptible-Infected-Recovered
(SIR) model with local dynamic vaccination, and considering limited vaccines.
In this model, susceptibles in contact with an infected individual, are
vaccinated -with probability $\omega$- and then get infected -with probability
$\beta$. However, when the fraction of immunized individuals reaches a
threshold $V_L$, the vaccination stops, after which only the infection is
possible. In the steady state, besides the critical points $\beta_c$ and
$\omega_c$ that separate a non-epidemic from an epidemic phase, we find for a
range of $V_L$ another transition points, $\beta^*>\beta_c$ and
$\omega^*<\omega_c$, which correspond to a novel discontinuous phase
transition. This critical value separates a phase where the amount of vaccines
is sufficient, from a phase where the disease is strong enough to exhaust all
the vaccination units. For a disease with fixed $\beta$, the vaccination
probability $\omega$ can be controlled in order to drastically reduce the
number of infected individuals, using efficiently the available vaccines.
  Furthermore, the temporal evolution of the system close to $\beta^*$ or
$\omega^*$, shows that after a peak of infection the system enters into a
quasi-stationary state, with only a few infected cases. But if there are no
more vaccines, these few infected individuals could originate a second
outbreak, represented by a second peak of infection. This state of apparent
calm, could be dangerous since it may lead to misleading conclusions and to an
abandon of the strategies to control the disease.
