HLTC07-Lecture 5 (oct 17).docx

4 Pages
Unlock Document

University of Toronto St. George
Trinity College Courses
Barakat- Haddad

Lecture 5- Disease Modelling HLTC05- Oct 17  Tool for the analysis of policy options 1. Complexity of infectious disease dynamics (they’re different for different diseases); link between agent and environment 2. Not possible to decide by pure reasoning 3. Process requires quantitative estimates (eg. lets increase the vaccination rate of the flu) What is Involved?  Mechanistic description of the transmission-> trying to get a system that tells us how is transmission happening; how are things preceeding and if thigns change, what will it come up to  Connect the individual-level process of transmission with a population-level description (population goes up to 8 bill, arnaught might by 25)  Detail requirements of all the dynamic processes (the dynamic processes are different – symptomatic and asymptomatic) - Focus on essential processes involved in shaping the epidemiology of an infectious disease (death rate matters, birth rates important) - Reveals the parameters that are most influential and amenable for control (you can identity which of those factors in the models can be changed; can be the target for interventions) -> if we can reduce the rate of smoking by 50%, our cancer rates will go down 10-15% What has fuelled the applicability of mathematical disease modelling?  Bernoulli - 18 century  Hamer in 1906 used modelling to argue that an epidemic can come to an end  Kermack and Mckendrick (1927) - basis for SIR modelling and R o  Based on your knowledge, which diseases require or make use of mathematical modelling? SIR Model  Basic assumption: human population is subdivided into 3 groups: - susceptible persons (S) - infected persons (I) -> if they have acquired immunity, they’ll move to the R group - removed persons (R) -> not longer part of the infectious disease  Movements in and out of these groups via: - Birth -> a flow into the susceptible group - Death - Transmission of infection -> movement from the S to the I group - Recovery -> I group to recovery  Birth rate, ν; if p=fraction of vaccinated newborns, then birth rate=(1-p)ν  Death rate, µ  Recovery rate, γ  ϐ , mass action term where Β = κq; κ=contact rate, q=probability of transmission  Force of infection, λ = ϐ I  Where N=total population size, λ = ϐ I / N  I= rate of infection occurring (how many people are getting infected) dS/dt = ν(1-p) - ϐS(I/N) - µS (death rate of those susceptible) dI/dt = ϐS (I/N) – γI (those that are recovering) - µI (die out in the infected group) dR/dt = νp + γI - µR Basic Concepts  If an infectious disease that spreads on a much faster time scale than the demographic process, how do we
More Less

Related notes for TRN125Y1

Log In


Don't have an account?

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.