Results 91 to 100 of about 70,485 (205)
Spatial correlations in SIR epidemic models
6 pages, 4 ...
Fukś, Henryk +2 more
openaire +2 more sources
A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models. [PDF]
We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random
David A Rolls +4 more
doaj +1 more source
Abstract Scholars have tended to interpret Thomas Nettleton's bestselling Virtue and Happiness (1729) as an Epicurean work. In contrast, I argue that this book was constructed partly from extensive paraphrases of the writings of Locke, Shaftesbury, and Hutcheson.
Jacob Donald Chatterjee
wiley +1 more source
Dynamic Behavior of Interacting between Epidemics and Cascades on Heterogeneous Networks
Epidemic spreading and cascading failure are two important dynamical processes over complex networks. They have been investigated separately for a long history. But in the real world, these two dynamics sometimes may interact with each other.
Jiang, Lurong +4 more
core +1 more source
Runge–Kutta pairs suited for SIR‐type epidemic models
Modeling the infectious diseases concludes in systems of ordinary differential equations (ODEs). The compartments in these equations (e.g., the numbers of susceptible, infectious, or immunized individuals) change in time. The ODEs arriving in these models are quadratic. Thus, we may apply special type of Runge–Kutta (RK) pairs for solving them.
Kovalnogov, Vladislav N. +2 more
openaire +2 more sources
Abstract Background Equine encephalosis (EE) is caused by an Orbivirus from the family Sedoreoviridae and is thus similar to African horse sickness (AHS) and Bluetongue viruses (BTV). These viruses are transmitted by Culicoides midges. Equine encephalosis can infect horses, donkeys and zebras sub‐clinically while only horses develop clinical disease ...
Graeme Piketh +2 more
wiley +1 more source
The evolution of RNA viruses such as HIV, Hepatitis C and Influenza virus occurs so rapidly that the viruses' genomes contain information on past ecological dynamics.
Drummond, Alexei J. +3 more
core +1 more source
Abstract It is well‐recognized in the sciences that a multitude of nonequivalent models are used by researchers to fulfill a range of goals, even for the same target system, a result known broadly as model pluralism. The possibility of the same form of pluralism occurring in logic, however, has not been adequately considered.
Ben Martin
wiley +1 more source
Disease outbreaks in stochastic SIR epidemic models are characterized as either minor or major. When ℛ01, they can be minor or major. In 1955, Whittle derived formulas for the probability of a minor or a major epidemic.
William Tritch, Linda J.S. Allen
doaj +1 more source
Predicting Epidemic Diseases using Mathematical Modelling of SIR
Epidemic diseases such as Tuberculosis (TB), AIDS (Acquired Immune Deficiency Syndrome) and CCHF (Crimean-Congo Hemorrhagic Fever) remain as a major global health problem. For example, in 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease reported by WHO (including 320 000 deaths among HIV (human immunodeficiency ...
ERGEN, KIVANÇ +2 more
openaire +4 more sources

