Overview

Technical curriculum overview

Week 1: Overview of EMOD

Install PyCharm, dtk-tools, and dtk-tools malaria (Obj 2b)
Basic git
Clone example exercises
Learn development history of EMOD (Obj 2a)
Learn each part of EMOD software ecosystem and how they interact (Obj 2a)
Learn basic EMOD simulation workflow and run a barebones ExampleSim (Obj 2a, 2c)

Week 2: Basic building blocks of EMOD

Identify the three building blocks to run an EMOD simulation (Obj 2c)
- The basic inputs: Parameters, demographics and climates
- The reports/outputs: JSON/CSV outputs
- The interventions: dynamic creation of the campaign file
Create demographics and climate files, and incorporate into simulations (Obj 2d)
- Implement in own research project
- Run barebones version of own research project
Grab and plot outputs (Obj 2d)
- InsetChart
- MalariaSummaryReport
- Implement in own research project

Week 3: Interventions in EMOD

Learn how major malaria interventions are implemented in EMOD (Obj 2a, 2c)
- Case management for symptomatic malaria
- Vector control: ITNs, IRS, and larvicides
- Antimalarial drug campaigns
Learn about event reporting in EMOD (Obj 2d)
- Individual-level events
- Aggregated events
Run various interventions in the simulation and examine the output (Obj 2d, 2e)
- Implement in own research project
Learn about ModBuilder (Obj ??)
- Design and implement ModBuilder for own research project
- Run a multi-simulation experiment for own research project

Week 4: Analyzers and plotters

Walkthrough examples of analyzers (Obj 2a, 2c)
- Single simulation
- Multi-simulation experiment
- Saving to csv
- Plotting in analyzer
Write or adapt a customized analyzer to extract data from own research project (Obj 2d, 2g)
Plot analyzers’ output using R or Python (Obj 2d, 2e, 2g)

Week 5

no technical curriculum, prepping Aims and slide decks

Week 6: Serialization

Understand the concept and rationale of burn-in and serialization (Obj 2a, 2c)
Walkthrough example burnin and pickup code
Perform the following for own research project (Obj 2c):
- Serialization of simulation: create burnin
- Picking up a serialized population and run it forward

Week 7: Sweeping and calibration

Understand the concept and needs for sweeping and calibration to prevalence data (Obj 2f)
Perform the following for own research project (Obj 2f):
- Sweep through a range of values for a parameter
- Determine the best value for the parameter by calculating likelihood over observed data

Week 8: Individual properties

Understand the concept and use case for individual properties (Obj 2a)
Perform the following for own research project (Optional; Obj 2c)
- Enable individual properties
- Implement an intervention based on individual properties
- Implement reporting based on individual properties

Week 9: Infusing simulations with real data

Week 10

no technical curriculum, prepping Aims and slide decks

Week 11: Advanced EMOD: HBHI workflow as a complex example

Understand the context for HBHI modeling
Nigeria example: manuscript and HBHI-Nigeria Shiny app (Obj 3a, 3b)
Code walkthrough of HBHI analysis process
- Identify familiar components from previous weeks
- Identify new components: managing shared functions, reading intervention data from csv’s, multi-analyzers
Continue to refine own research projects

Week 12: Advanced EMOD: Spatial modeling in EMOD

Week 13: Advanced EMOD: gene drive and reactive interventions

Reactive interventions and surveillance in EMOD
Guest lecture: vector genetics and modeling gene drives in EMOD
Roundtable: Current limitations and future of EMOD and agent-based modeling of malaria
Continue to refine own research projects

Week 14: HPC

Using Quest
Roundtable: Technical difficulties and challenges to run EMOD experiments from home institution
- How can NUMM help before or after return?

Week 15

no technical curriculum, prepping Aims and slide decks

Week 16

no technical curriculum, final week presentations