Showing posts with label stochastic models. Show all posts
Showing posts with label stochastic models. Show all posts

Friday, 15 July 2022

Epidemiological Models for Infectious Diseases and Applications in COVID-19 | Chapter 14 | Current Overview on Disease and Health Research Vol. 1

Humans are always at risk from infectious illnesses, including the continuing COVID-19 epidemic. One approach used in the field of epidemiology to research infectious illnesses is disease modelling. Both mathematical and computer simulation models are used to forecast the spread of an illness and suggest methods of infection control. To analyse diverse infectious illnesses, models with one to several compartments have been developed. Several models were developed to analyse the COVID-19's effects in the current situation of the epidemic that is affecting the entire world. Countries have implemented a variety of controls, such as lockdowns and limits, to limit the spread of the COVID-19. This chapter describes the different compartmental models used to simulate diseases and how they are used in the COVID-19 scenario as it stands right now.


Author (s) Details:

S. Manju Devi,
Department of Biochemistry, Bhavan’s Vivekananda College, Sainikpuri, Secunderabad, Telangana, India.

A. Sai Padma,
Department of Biochemistry, Bhavan’s Vivekananda College, Sainikpuri, Secunderabad, Telangana, India.

Please see the link here:
https://stm.bookpi.org/CODHR-V1/article/view/7436

Monday, 24 May 2021

Stochastics Growth Model | Chapter 1 | Theory and Practice of Mathematics and Computer Science Vol. 10

 The goal is to create a mathematical model that takes into account genetic defects while evaluating the development rate of roan antelopes in Kenya's Ruma National Park.

Methodology: To estimate the population growth rate of roans, this work modified Oksendal and Lungu's stochastic logistic model by integrating genetic defects not included by Magin and Cock. Vortex version 9.99, a computer simulation programme used to mimic the extinction process, was adjusted appropriately.

Inbreeding has a high-level impact on population expansion (survival) in tiny communities, according to the findings. Juvenile and adult roans were supplemented to promote population survival for a longer period of time.

Conclusion: To combat inbreeding, which is a serious concern to tiny populations, this paper proposes supplements rather than predator control because of the unknown implications to the environment and conflicts with wildlife management plans in protected areas. Supplementation should be done in stages so that social groupings are not disrupted. Genetic research should be conducted to determine the extent to which inbreeding influences population increase, according to this study.

Author(s) Details

Daniel Ochieng Achola
Department of Mathematics, Kabarak University, Private Bag-20157, Nakuru, Kenya.

View Book :- https://stm.bookpi.org/TPMCS-V10/article/view/1071