Welcome to JUNE-NZ

JUNE-NZ is a collobrative Artificial Intelligence (AI)-enabled Agent-Based Modeling (ABM) framework that has been adapted from the world-leading JUNE model led by Durham University (UK), which focuses on public health and epidemiology simulations. This collaborative framework incorporates cutting-edge AI technologies to facilitate dynamic simulations and analyses of complex systems in the context of New Zealand.

By leveraging JUNE-NZ, researchers and policymakers can gain valuable insights into various aspects of healthcare and the social system, enabling informed decision-making and effective planning strategies.

Note

JUNE-NZ is an ongoing project from Inisitute of Environmental Science and Research (ESR), New Zealand

The codes of JUNE-NZ can be accessed from here

Contents

• Installation
  • MAMBA Installation
  • JUNE_NZ environment
• Toy model for JUNE_NZ
• Workflow
  • Step 1. Creating the input dataset
  • Step 2. Running the model
  • Step 3. Generating the model diagnosis
• Model tuning
  • Base example
  • Increase the people is hospitalized and died
  • Make people to be infected quicker
    • Increase contact frequency
    • Change probability of infection
    • Reduce the symptom cycle
• Data
  • 1. Population data (demography)
  • 2. Geography data
  • 3. Group (activities) data
    • 3.1 Company
    • 3.2 Household
    • 3.3 Hospital
    • 3.4 School
    • 3.5 Leisure (cinema, grocery, pub, gym and household visit)
  • 4. Commute
  • 5. Interaction
  • 6. Disease data
    • 6.1 Comorbidities
    • 6.2 Virus intensity
    • 6.3 Symptom trajectory (infection outcome)
      • 6.3.1 Input infection outcome statistics
      • 6.3.2 Symptom trajectory (infection outcome)
    • 6.4 Transmission profile
      • 6.4.1 Base probability of infection
      • 6.4.2 Adjust max infectiousness
      • 6.4.3 Adjust mild/asymptomatic infectiousness
  • 7. Vaccination data
• Links
• Combinining ABM and Neural Network
  • Results comparisons
    • Experiment 1
    • Experiment 2
    • Experiment 3