-
MODULE 1: SIR Model Basics
Introduction to Compartmental Models for Infectious Disease -
Introduction to Ordinary Differential Equations (ODEs) and the SIR Model
-
Introduction to SIR Modelling in R
-
MODULE 2: SIR Model ExtensionsModelling Density-dependent vs. Frequency-dependent Transmission
-
SIR model with Demographics
-
CASE STUDY: Modelling with Real-World DataSEIR & SEIRW models for Hepatitis E Virus (HEV) Outbreaks: A Case Study
-
MODULE 3: Epidemic ThresholdsThe Basic Reproduction Number (R0)
-
The Effective Reproduction Number (Re)
-
Vaccination and Herd Immunity
-
Practical Example: Models for Infectious Disease Management & PolicyVaccination Strategies to Control Hepatitis E Outbreaks: A Modeling Study (Cooper et al. 2018)
SEIR & SEIRW models for Hepatitis E Virus (HEV) Outbreaks: A Case Study
Lesson Video
🚗 Video too fast or too slow? Click the gear icon ⚙️ at the bottom-right to change the speed!
Click here to view and download this video from Vimeo.
Lesson Code & Data
Please download the R Markdown script linked below to code along with the instructor.
You need to click the download button on the top right menu.
Am still failing to understand the beta = 120, how can we derive this?
Hello! Can you point to the section where beta=120?
Hi. When modelling the HEV outbreak in the IDP camp. (41:52 mins into the video)
I am having some trouble understanding sigma in the case study. At 42:00 in the video it is given as 52/5 corresponding to 1/latent period. This does not make sense if symptomatic incidence is p * sigma * E because if p =1/7 then p * sigma is greater than 1 indicating higher symptomatic cases than exposed cases.
Then at 54:00 in the video, sigma is given as 0.2 which makes more sense to me than 52/5, but I am not sure where 0.2 came from.
Could someone help with understanding the two different values for sigma?
I have the same question 🙂 she said sigma was 52/5 and then that sigma was 0.2 in the R model. I think 0.2 is another parameter?
Looking all over again now, 0.2 is probably 1/5, which is in WEEKS – meaning 20% of the exposed leave the compartment weekly. But the entire model is in years.. so I don’t know why she put sigma = 0.2 there! if the model is in years, it should be 52/5?
NEVERMIND HAHAHA, it has to be in weeks (=0.2), because this is just for the observation of the data! the model is in years indeed, but the original reports were per week, so we will ask the model to let us visualize the data in weeks even though we are modelling it yearly. Assuming sigma weekly is just for the observation of data, so it matches the Weekly Reports of the disease.