The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Network and Epidemic Model
|
|
Copyright: 2023
Pages: 48
Source title:
Controlling Epidemics With Mathematical and Machine Learning Models
Source Author(s)/Editor(s): Abraham Varghese (University of Technology and Applied Sciences, Muscat, Oman), Eduardo M. Lacap, Jr. (University of Technology and Applied Sciences, Muscat, Oman), Ibrahim Sajath (University of Technology and Applied Sciences, Muscat, Oman), M. Kamal Kumar (University of Technology and Applied Sciences, Muscat, Oman) and Shajidmon Kolamban (University of Technology and Applied Sciences, Muscat, Oman)
DOI: 10.4018/978-1-7998-8343-2.ch007
Purchase
|
Abstract
Infectious diseases transmitted and networks and the epidemiology are fundamentally linked. Population-wide random mixing is the fundamentals for the epidemiology and its models, but in reality, each person will have a countable set of contacts, which is the root cause for the spread of the diseases. The mixing network is nothing but the collections of all such contacts. From the point of view of the individual-level behaviors, the network computes the epidemic dynamics of a complex population. Hence, for the prediction of epidemic patterns, its dynamics and the characteristics of the population can be understood only with the help of the deep study of the networks. Hence, the study of the networks is critical for the epidemiologist for understanding the spread of the diseases.
Related Content
|
.
© 2023.
12 pages.
|
|
.
© 2023.
43 pages.
|
|
.
© 2023.
29 pages.
|
|
.
© 2023.
11 pages.
|
|
.
© 2023.
23 pages.
|
|
.
© 2023.
26 pages.
|
|
.
© 2023.
48 pages.
|
|
|