Mariana Pinheiro | Searcharxiv

arXiv2020

Epidemic analysis of COVID-19 in Brazil by a generalized SEIR model

We shall apply a generalized SEIR model to study the outbreak of COVID-19 in Brazil. In particular, we would like to explain the projections of the increase in the level of infection over a long period of time, overlapping large local outbreaks in the most populous states in the country. A time-dependent dynamic SEIR model inspired in a model previously used during the outbreak in China was used to analyses the time trajectories of infected, recovered, and deaths. The model has parameters that vary with time and are fitted considering a nonlinear least-squares method. The simulations starting from April 8, 2020, concluded that the time for a peak in Brazil will be in July 21, 2020 with total cumulative infected cases around 982K people; in addition, an estimated total death case will reach to 192K in the end. Besides that, Brazil will reach a peak in terms of daily new infected cases and death cases around the middle of July with 50K cases of infected and almost 6.0K daily deaths.

q-bio.PE↗

arXiv2013

Adapted random perturbations for non-uniformly expanding maps

We obtain stochastic stability of C2 non-uniformly expanding one-dimensional endomorphisms, requiring only that the first hyperbolic time map be L^{p}-integrable for p>3. We show that, under this condition (which depends only on the unperturbed dynamics), we can construct a random perturbation that preserves the original hyperbolic times of the unperturbed map and, therefore, to obtain non-uniform expansion for random orbits. This ensures that the first hyperbolic time map is uniformly integrable for all small enough noise levels, which is known to imply stochastic stability. The method enables us to obtain stochastic stability for a class of maps with infinitely many critical points. For higher dimensional endomorphisms, a similar result is obtained, but under stronger assumptions.

math.DS↗