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Related Experiment Video

Updated: Jun 23, 2026

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

Memory mechanisms for behavioural change in Bayesian individual-level spatial epidemic models.

Yicheng Mao1,2, Rob Deardon2,3, Lorna E Deeth4

  • 1Department of Data Analytics and Digitalization, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, the Netherlands.

Infectious Disease Modelling
|June 22, 2026
PubMed
Summary

This study introduces memory-enhanced behavioral change models for infectious disease transmission. These models accurately capture how past epidemic information influences current behavior, improving disease prediction.

Keywords:
Bayesian inferenceBehavioural changeIndividual-level modelsInfectious disease modellingSIR models

Related Experiment Videos

Last Updated: Jun 23, 2026

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Behavioral Science

Background:

  • Accurate infectious disease modeling requires understanding behavioral adjustments to epidemic conditions.
  • Existing models often treat memory's role in risk perception simplistically.

Purpose of the Study:

  • To develop a data-driven framework for memory-enhanced behavioral change individual-level models (MEBC-ILMs).
  • To incorporate and evaluate four distinct memory specifications within these models.
  • To infer memory features from epidemic data for more realistic risk perception modeling.

Main Methods:

  • Developed MEBC-ILMs with memoryless, sliding window, power-law decay, and exponential decay specifications.
  • Used simulation experiments to test model performance and parameter recovery.
  • Applied the framework to real-world data from the 2001 U.K. foot and mouth disease epidemic.

Main Results:

  • MEBC-ILMs reliably recover transmission and behavioral parameters across different memory settings.
  • Models show robust predictive performance even with mismatched memory structures.
  • The basic behavioral change individual-level model (BC-ILM) underperforms when memory is significant but unmodeled.

Conclusions:

  • The developed framework provides a robust method for incorporating memory into epidemic models.
  • MEBC-ILMs offer improved accuracy in modeling infectious disease transmission dynamics.
  • The framework facilitates the exploration of memory structures using real-world epidemic data.