mlsanityData to 7 Oct 2026

Differentiable Agent-based Epidemiology

arXiv 2207.09714 ↗First posted 20 Jul 2022cs.LG cs.AI cs.MAcited by 21

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Abstract (arXiv)

Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environments. Agent-based models (ABMs) are an increasingly popular simulation paradigm that can represent the heterogeneity of contact interactions with granular detail and agency of individual behavior. However, conventional ABM frameworks are not differentiable and present challenges in scalability; due to which it is non-trivial to connect them to auxiliary data sources. In this paper, we introduce GradABM: a scalable, differentiable design for agent-based modeling that is amenable to gradient-based learning with automatic differentiation. GradABM can quickly simulate million-size populations in few seconds on commodity hardware, integrate with deep neural networks and ingest heterogeneous data sources. This provides an array of practical benefits for calibration, forecasting, and evaluating policy interventions. We demonstrate the efficacy of GradABM via extensive experiments with real COVID-19 and influenza datasets.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 21 of its 82 references that are in the map. First posted on arXiv 20 Jul 2022.

Builds on

21 of 82 references.

References · 21

  1. 2017Attention Is All You Needcited by 59,932
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  9. 2020Interpretable Sequence Learning for COVID-19 Forecastingcited by 22
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  12. 2020When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processescited by 13
9 more
  1. 2020Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19cited by 12
  2. 2019Segregation Dynamics with Reinforcement Learning and Agent Based Modelingcited by 9
  3. 2021Differentiable Agent-Based Simulation for Gradient-Guided Simulation-Based Optimizationcited by 8
  4. 2022Data-Centric Epidemic Forecasting: A Surveycited by 8
  5. 2017A Framework for Evaluating Epidemic Forecastscited by 7
  6. 2021Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Futurecited by 7
  7. 2020Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)cited by 6
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 5; 2025: 6; 2026: 7.

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  1. 2022Automatic Differentiation of Programs with Discrete Randomnesscited by 28
  2. 2024On the limits of agency in agent-based modelscited by 20
  3. 2023Bayesian calibration of differentiable agent-based modelscited by 4
  4. 2024Bayesian calibration of stochastic agent based model via random forestcited by 4
  5. 2026Toward World Models for Epidemiologycited by 3
  6. 2023Some challenges of calibrating differentiable agent-based modelscited by 2
  7. 2025Improving Epidemic Analyses with Privacy-Preserving Integration of Sensitive Datacited by 2
  8. 2025Large Population Modelscited by 2
  9. 2025CALYPSO: Forecasting and Analyzing MRSA Infection Patterns with Community and Healthcare Transmission Dynamicscited by 2
  10. 2026Agentic Framework for Epidemiological Modelingcited by 2
  11. 2024Towards Learning Stochastic Population Models by Gradient Descentcited by 1
  12. 2024Fully Data-driven but Interpretable Human Behavioural Modelling with Differentiable Discrete Choice Modelcited by 1
9 more
  1. 2026Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Frameworkcited by 1
  2. 2024Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networkscited by 0
  3. 2025Designing Dynamic Pricing for Bike-sharing Systems via Differentiable Agent-based Simulationcited by 0
  4. 2025Control of dynamical systems with neural networkscited by 0
  5. 2025A differentiable model of supply-chain shockscited by 0
  6. 2026Ultra-fast Traffic Nowcasting and Control via Differentiable Agent-based Simulationcited by 0
  7. 2026Boundary Degree as a Node-level Feature for Epidemic Scenario Identification in Agent-based Cascade Simulationscited by 0
  8. 2026Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptopcited by 0
  9. 2026Learning Collective Dynamics with Differentiable Gaussian Representationscited by 0