Simplified generative model for malaria transmission networks in Senegal
- Learn simple functional forms to describe EMOD-like transmission
- Set up Maka-like sims (without interventions), and sweep these over transmission intensity
- Identify the transmission points to focus on (Wes: 300 cases/1000/yr, 100, 10, <10)
- For each of these, bin the population into age bins
- Look at age distributions of infection duration, infectiousness, and susceptibility in these bins
- Try to derive simple functional forms for these distributions
- Create new, simple transmission model that has EMOD-like descriptions
- Human population with infection duration, infectiousness, and susceptibility drawn from distributions
- Simplified vector layer that is parametrized version of EMOD vector populations (only need to keep track of vectors that actually transmit)
- No limit on complexity of infection in humans
- Identify scale above which we can use model to trust population-level genetics signals and not be too concerned about the individual level heterogeneity
- Use model to explore potential networks that have similar incidence but different genetic signals