The future of policy with agent-based models

Arnau Quera-Bofarull

Institute for Computational Cosmology, Durham, UK

How I got involved into ABM

  • PhD student in computational Astrophysics
  • March 2020: Royal society call for modelers (RAMP)
    • JUNE project starts
  • 20+ collaborators, input into  
  • Development continues:
    long term plans with PHE

JUNE

  • 56 million agents
  • Resolution ~ English census
  • Millions of venues
  • Detailed customizable policies

Model fitting

We have

Model (tens of free parameters)

+

Data (quite messy)

It takes ~400 CPU hours to run one simulation....

How do we fit it?

Emulator

+

History Matching

Emulator + history matching

Train emulator

Run emulator

O(500k) times

Run full simulation O(100) times

Narrow parameter space search

Why we need the complexity

JUNE reproduces infection disparities among various demographic groups thanks to its granularity.

My contributions to JUNE

1) Main modeller, written ~60% of the code (25,000 lines)

2) Designed and implemented HPC parallelization structure.

3) Setup pipeline for model calibration against data

Interdisciplinary collaboration

1) Main modeller, written ~53% of the code (25,000 lines)

2) Designed and implemented HPC parallelization structure.

3) Setup pipeline for model calibration against data

The challenge of model initialization

Model calibration

Initial conditions

Latent (un-observable) variables.

Input parameters

JUNE latent variables

Observable

\theta_i

Simulator

latent variables include:

  • asymptomatic carriers
  • number of contacts
  • compliance to policies
  • current prevalence

Current emulation

Etalumis

Atılım Güneş Baydin,

Oxford

Calibration: A new approach

Etalumis

(Atılım Güneş Baydin, Oxford)

arXiv:1907.03382v2

Interface the simulator with a Probabilistic Programing Language

Etalumis

(Atılım Güneş Baydin, Oxford)

JUNE latent variables

Observable

Etalumis inference

We can reconstruct the microstate in JUNE.

This is crucial for policy making.

  • Which schools can reopen?
  • In which postcodes movement should be restricted?
  • What are the most vulnerable hospitals?
  • ...

Not limited to Epidemiology

JUNE is essentially a model of the English population and its dynamics

  • Housing policy
  • Public transport policy
  • Origin of inequalities
  • etc.

Challenging task, requires wide collaboration

Machine Learning

HPC

Specific domain knowledge

New programming languages

Bayesian statistics

Effective communication

Agent-based modelling

By arnauqb

Agent-based modelling

  • 456