Dissipative partial differential equations that exhibit chaotic dynamics tend to evolve to
attractors that exist on finite-dimensional manifolds. We present a data-driven reduced-order …

In response to the COrona VIrus Disease 2019 (COVID-19) pandemic, extensive research
has been conducted to explore, understand, and model the dynamics of expelled respiratory …

When using SIR and related models, it is common to assume that the infection rate is
proportional to the product of susceptible and infected individuals. While this assumption …

Mathematical epidemiology has a long history of origin and development. In particular,
mathematical modeling and analysis of infectious diseases has become a fundamental and …

We adopt a maximum-likelihood framework to estimate parameters of a stochastic
susceptible–infected–recovered (SIR) model with contact tracing on a rooted random tree …

In this paper, we consider reaction-diffusion epidemic models with mass action or standard
incidence mechanism and study the impact of limiting population movement on disease …

The coronavirus infectious disease (or COVID-19) is a severe respiratory illness. Although
the infection incidence decreased significantly, still it remains a major panic for human …

In the context of natural disasters, human responses inevitably intertwine with natural
factors. The COVID-19 pandemic, as a significant stress factor, has brought to light profound …

We present a simple model for the spread of an infection that incorporates spatial variability
in population density. Starting from first-principle considerations, we explore how a novel …

In actual pandemic situations like COVID-19, it is important to understand the influence of
single mitigation measures as well as combinations to create most dynamic impact for …