The MMED program includes a number of parallel sessions for participants with different backgrounds. Track A is designed for those with a mathematical background, particularly those who have extensive training and/or experience with differential equation models of infectious disease dynamics. Track B is designed for those with a background in epidemiology and/or statistics, particularly those who are involved in data collection for infectious disease systems.

Schedule

Week 1

Monday

  • 8:00 – 8:30 Registration and welcome, AIMS lobby
  • 8:30 – 9:00 Introductions and Motivation for Workshop
  • 9:00 – 10:00 Lecture: Public Health, Epidemiology, and Models
  • 10:00 – 10:30 Coffee break
  • 10:30 – 10:45 Organizational session: MMED Road Map and programme overview
  • 10:45 – 11:30 Lecture: Introduction to Thinking About Data I
  • 11:30 – 12:30 Lecture: Introduction to dynamic modeling of infectious diseases
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:20 Exercise: Dynamical Fever and Model Worlds (in pairs) and discussion
  • 15:20 – 15:30 Discussion: Dynamical Fever and Model Worlds
  • 15:30 – 16:00 Tea and poster set-up
  • 16:00 – 17:00 Parallel sessions
    • Track A: Introduction to infectious disease data
    • Track B: Foundations of dynamic modeling
  • 17:00 – 18:00 Poster session I
  • 18:00 – 18:30 Dinner
  • 19:00 – 20:30 Social Activity

Tuesday

  • 8:30 – 9:15 Lecture: (Hidden) assumptions of simple ODE models
  • 9:15 – 10:00 Lecture and Computer Session: Introduction to model implementation
  • 10:00 – 10:30 Coffee break
  • 10:30 – 12:30 Computer Session: R Tutorials I-III
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 14:45 Parallel sessions
    • Track A: Lecture: Introduction to Thinking About Data II
    • Track B: Lecture: Basic stochastic simulation models
  • 14:45 – 15:30 Parallel sessions
    • Track A: Computer Session: R Tutorials I-III, Lab 1: ODE models in R, or Tutorial 4: Visualizing Infectious Disease Data in R (as needed)
    • Track B: Computer Session: Basic stochastic simulation models cnt’d
  • 15:30 – 16:00 Tea and poster set-up
  • 16:00 – 17:00 Computer Session: R Tutorials continued
  • 17:00 – 18:00 Poster session II
  • 18:00 – 18:30 Dinner
  • 19:00 – 20:00 Real-world example (optional lecture)

Wednesday

  • 8:30 – 9:15 Lecture: Consequences of heterogeneity, and modeling options
  • 9:15 – 10:00 Computer Session: Lab: consequences of heterogeneity
  • 10:00 – 10:30 Coffee break
  • 10:30 – 11:00 Lecture: Work with models as a group on projector
  • 11:00 – 12:30 Computer Session: Harare data in groups of <4.
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 14:30 Computer Session: Harare/other data in same groups.
  • 14:30 – 15:30 Discussion: Harare data and spreadsheet work
  • 15:30 – 16:00 Tea and poster set-up
  • 16:00 – 17:00 Parallel sessions
    • Track A: Formulating Research Questions A
    • Track B: Formulating Research Questions B
  • 17:00 – 18:00 Poster session III
  • 18:00 – 18:30 Dinner
  • 19:00 – 20:00 Real-world example (optional lecture)

Thursday

  • 8:30 – 10:00 Parallel sessions
    • Track A: Lecture and Computer Session: Study Design and Analysis in Epidemiology: Where does modeling fit? and Lab: Study Design in Epidemiology
    • Track B: Exercise: Creating a model world to address a research question
  • 10:00 – 10:30 Coffee break
  • 10:30 – 12:00 Lecture: Introduction to statistical philosophy
  • 12:00 – 12:30 Discussion: MMED research projects
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:30 Lecture: Participatory coding for Variability, Sampling Distributions, and Simulation Lecture
  • 15:30 – 16:00 Tea
  • 16:00 – 16:45 Lecture: Introduction to Likelihood
  • 16:45 – 18:00 Computer Session: Lab 5: Introduction to Likelihood Lab
  • 18:00 – 18:30 Dinner
  • 19:30 – 21:00 Social activity: Drumming

Friday

  • 8:30 – 10:00 Parallel sessions
    • Track A: Lecture and Computer Session: Study Design and Analysis in Epidemiology II: RCT’s and Lab: Study Design for Clinical Trials
    • Track B: Exercise: Description of proposed model and assumptions
  • 10:00 – 10:30 Coffee break
  • 10:30 – 11:15 Lecture: Likelihood fitting and dynamic models, Part 1: Dynamic Model Fitting and Inference Robustness
  • 11:15 – 12:30 Computer session: MLE fitting of an SIR model to prevalence data
    • Additional info: Parameter transformation
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:30 Mentor presentations
  • 15:30 – 16:00 Tea
  • 16:00 – 17:00 MMED Projects
  • 17:00 – 18:00 Mid-session Feedback
  • 18:00 – 18:30 Dinner
  • 19:30 – 21:30 Social Activity

Saturday

  • 9:00 – 10:30 Lecture: Participatory coding of a dynamical model
  • 10:30 – 11:00 First chance to sign up for project groups and Coffee break
  • 11:00 – 12:30 Exercise: Working with Git and GitHub
  • 12:30 – 14:00 Social Activity: Group lunch at Kalky’s
  • 14:00 – Free/working afternoon

Sunday

  • Free day – optional group trip to Cape Point

Week 2

Monday

  • 8:30 – 9:15 Lecture: Doing Science
  • 9:15 – 9:30 Organizational Session: Schedule and goals for the second week
  • 9:30 – 10:00 Work Session: Project groups meet for the first time
  • 10:00 – 10:30 Coffee break
  • 10:30 – 11:30 Computer Session: Introduction to GitHub
  • 11:30 – 12:30 Computer Session: GitHub repos for group projects
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:30 Lecture: Likelihood fitting and dynamic models II
  • 15:30 – 16:00 Tea
  • 16:00 – 17:30 Work Session & Mentoring Session
  • 18:00 – 18:30 Dinner
  • 19:00 – 20:00 Real-world example (optional lecture)

Tuesday

  • 8:30 – 10:00 Lecture: Introduction to Monte Carlo Markov Chains
  • 10:00 – 10:30 Coffee break
  • 10:30 - 11:30 Computer session: MCMC fitting Labs 7-8
  • 11:30 – 12:30 Work Session
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:30 Lecture: Working with databases: management and manipulation in R
  • 15:30 – 16:00 Tea
  • 16:00 – 17:30 Work Session & Mentoring Session
  • 18:00 – 18:30 Dinner
  • 19:00 – 20:00 Real-world example (optional lecture)

Wednesday

  • 8:30 – 10:00 Reading Session (all groups)
  • 10:00 – 10:30 Coffee break
  • 10:30 – 12:30 Work Session (All instructors)
    • 10:45 – 11:15 Optional Session: Resolving merge conflicts
    • 11:30 – 12:00 Optional Session: Data cleaning
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:30 Work Session
    • 14:00 – 15:30 Optional Session: Model assessment
  • 15:30 – 16:00 Tea
  • 16:00 – 17:30 Work Session & Mentoring Session
  • 18:00 – 18:30 Dinner
  • 19:00 – 20:00 Real-world example (optional lecture)

Thursday

  • 8:30 – 10:00 Lecture: Modeling for policy
  • 10:00 – 10:30 Coffee break
  • 10:30 – 12:30 Work Session (Mentors)
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:30 Work Session
  • 15:30 – 16:00 Tea
  • 16:00 – 17:30 Work Session & Mentoring Session
  • 18:00 – 18:30 Dinner

Friday

  • 8:30 – 10:00 Work Session
  • 10:00 – 10:30 Coffee break
  • 10:30 – 12:30 Work Session
  • 12:30 – 14:00 Lunch break (Lunch is served from 12:30 to 13:00.)
  • 14:00 – 15:45 Final presentations
  • 15:45 – 16:00 Tea
  • 16:05 – 17:05 Final Feedback Session
  • 17:15 – 17:45 Closing session
  • 18:00 – 18:30 Dinner
  • 21:00 – 23:00 Social Activity

Saturday

  • Clinic officially ends on Friday, but there will be an optional group trip on Saturday.

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