<p>There are four individuals/nodes in the contact network and five edges. Different colors indicate different health states. Also each node is randomly assigned an incubation and infectious period sampled from a discrete distribution. For simplicity, each of the nodes in this example has an incubation period of 0 days and an infectious period of 2 days. On day 0, node <i>A</i> is infectious while all other nodes are susceptible. On day one, node <i>C</i> is infected due to contact with node <i>A</i> and on day two, node <i>A</i> recovers, while nodes <i>B</i>, <i>C</i> and <i>D</i> are infectious. There are no susceptible nodes after day two. On day three, node C recovers. Finally on day four, all nodes recover. Unlike this example, the n...
Mathematical models of infectious disease dynamics focus primarily on two basic parameters that gove...
One of the motivating questions for many epidemiologists is “how quickly or widely will a particular...
In mathematical epidemiology, the standard compartmental models assume homogeneous mixing in the hos...
Abstract Background The spread of infectious diseases crucially depends on the pattern of contacts b...
International audienceABSTRACT: BACKGROUND: The spread of infectious diseases crucially depends on t...
The transition rates from susceptible to incubating are expressed in number of infections per 2 week...
Networks and graphs offer a suitable and powerful framework for studying the spread of infection in ...
Over the past century, mathematical epidemiology has grown to be one of the triumphs of applied math...
An adaptive complex network based on a susceptible–exposed–infectious–quarantine–recovered (SEIQR) f...
Advances in the fields of mathematics, physics, epidemiology, and computing have led to an incredibl...
Our model still finds parameters that approximately match the data, even when the network topology c...
Background: The integration of empirical data in computational frameworks designed to model the spre...
This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment mo...
The spread of an infectious disease depends on intrinsic properties of the disease as well as the co...
Mathematical models of infectious disease dynamics focus primarily on two basic parameters that gove...
One of the motivating questions for many epidemiologists is “how quickly or widely will a particular...
In mathematical epidemiology, the standard compartmental models assume homogeneous mixing in the hos...
Abstract Background The spread of infectious diseases crucially depends on the pattern of contacts b...
International audienceABSTRACT: BACKGROUND: The spread of infectious diseases crucially depends on t...
The transition rates from susceptible to incubating are expressed in number of infections per 2 week...
Networks and graphs offer a suitable and powerful framework for studying the spread of infection in ...
Over the past century, mathematical epidemiology has grown to be one of the triumphs of applied math...
An adaptive complex network based on a susceptible–exposed–infectious–quarantine–recovered (SEIQR) f...
Advances in the fields of mathematics, physics, epidemiology, and computing have led to an incredibl...
Our model still finds parameters that approximately match the data, even when the network topology c...
Background: The integration of empirical data in computational frameworks designed to model the spre...
This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment mo...
The spread of an infectious disease depends on intrinsic properties of the disease as well as the co...
Mathematical models of infectious disease dynamics focus primarily on two basic parameters that gove...
One of the motivating questions for many epidemiologists is “how quickly or widely will a particular...
In mathematical epidemiology, the standard compartmental models assume homogeneous mixing in the hos...