Mathematical models in population biology and epidemiology
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In Chapters 6, we consider the influence of seasonal fluctuations on disease transmission and develop a periodic infectious disease model where asymptomatic carriers are potential sources for disease transmission. We consider a general nonlinear incidence rate function with the asymptomatic carriage and latent periods.
We implement a case study regarding the meningococcal meningitis disease transmission in Dori, Burkina Faso. Our numerical simulation indicates an irregular pattern of epidemics varying size and duration, which is consistent with the reported data in Burkina Faso from to In summery, in population growth models, we find that the basic reproduction ration depends on maturation time, indicating that this key parameter can play an important role in population extinction and persistence.
In disease transmission model, we understand that latent period can play a positive role in eliminating or slowing a disease spread. Become A Student. Explore Our Campuses. Memorial University Research Repository. Browse By:.
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Description The goal of this book is to search for a balance between simple and analyzable models and unsolvable models which are capable of addressing important questions on population biology. Part I focusses on single species simple models including those which have been used to predict the growth of human and animal population in the past.dramekcurpoi.tk
Mathematical modelling of infectious disease - Wikipedia
Single population models are, in some sense, the building blocks of more realistic models -- the subject of Part II. Their role is fundamental to the study of ecological and demographic processes including the role of population structure and spatial heterogeneity -- the subject of Part III. This book, which will include both examples and exercises, is of use to practitioners, graduate students, and scientists working in the field. Product details Format Hardback pages Dimensions x x Other books in this series.
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Mathematical Models in Population Biology and Epidemiology: From Elementary to the Frontier
Numerical Mathematics Alfio Quarteroni. Introduction to Numerical Analysis Josef Stoer.
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Theoretical Numerical Analysis Kendall Atkinson. Back cover copy This textbook provides an introduction to the field of mathematical biology through the integration of classical applications in ecology with more recent applications to epidemiology, particularly in the context of spread of infectious diseases.
It integrates modeling, mathematics, and applications in a semi-rigorous way, stating theoretical results and giving references but not necessarily giving detailed proofs, providing a solid introduction to the field to undergraduates junior and senior level , graduate students in applied mathematics, ecology, epidemiology or evolutionary biology, sustainability scientists, and to researchers who must routinely read the practical and theoretical results that come from modeling in ecology and epidemiology.
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In particular the chapters on epidemiology have been updated and extended considerably, and there is a new chapter on spatially structured populations that incorporates dispersal. The number of problems has been increased and the number of projects has more than doubled, in particular those stressing connections to data. In addition some examples, exercises, and projects include use of Maple and Matlab. Review of first edition: "A strength of the book is the large number of biologically-motivated problem sets. These and the references to the original biological papers would be valuable resources for an instructor.
Fred Brauer is a Professor Emeritus of Mathematics at the University id Wisconsin, where he taught from to , and has also been an Honorary Professor of Mathematics at the University of British Columbia since Free supplementary material available on the author's website involving problems using both Mathematica and MapleText offers nice balance of theory and applicationConcentration is on applications in population biology, epidemiology, and resource management.
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