An Introduction to Infectious Disease Modelling
Mathematical modelling is increasingly being applied to interpret and predict the dynamics and control of infectious diseases. Applications include predicting the impact of vaccination strategies against common infections and determining optimal control strategies against HIV and malaria.Though many public health and infectious disease researchers are aware that mathematical modelling would be of use to them, few have had any formal training in this area. As a result, they are ill-equipped either to use models or to even critically evaluate the modelling work of other researchers.Though several texts on the mathematical modelling of infectious disease transmission have been published to date, they have either been targeted at modellers, or they have illustrated how mathematical equations have informed the dynamics and control of infectious diseases without explaining howthese equations might be set up and solved. This book is designed to fill this gap. By reading the book and completing the accompanying exercises, readers will understand the basic methods for setting up mathematical models and how and where models can be applied. They will also gain an improved understanding of the factors which influencethe patterns and trends in infectious diseases. This book will be of interest to epidemiologists, public health researchers, policy makers, veterinary scientists, medical statisticians and infectious disease researchers.
What people are saying - Write a review
We haven't found any reviews in the usual places.
infections transmission and models
2 How are models set up? I An introduction to difference equations
3 How are models set up? II An introduction to differential equations
4 What do models tell us about the dynamics of infections?
5 Age patterns
6 An introduction to stochastic modelling
7 How do models deal with contact patterns?
8 Sexually transmitted infections
Other editions - View all
activity groups age at infection age groups Anderson RM average force average number basic reproduction number become infectious cent Chapter children and adults difference equations differential equations effective contact Epidemiol epidemiology equals estimates example expression following the introduction force of infection given gonorrhoea herd immunity high-activity group HIV infection immunizing infections impact increases individuals become individuals mix randomly infectious disease infectious individuals infectious persons low-activity group mathematical matrix measles mixing patterns MMR vaccination model described model predictions mumps number of individuals number of infectious number of secondary number of susceptible obtain the following Panel partner change rate partnerships period prevalence proportion of individuals random number rate of change result risk of infection rubella secondary infections serial interval sexual activity sexually transmitted diseases sexually transmitted infections step susceptible individuals tion total number totally susceptible population transmission dynamics transmission probability tuberculosis with-like mixing with-unlike