Contact and mobility networks
Agent-based models represent households, schools, workplaces and travel, so the effect of contact patterns and public health measures on transmission can be explored under stated parameters.
The Global Centre for Risk and Innovation (GCRI)
Complex systems methods show how health risk emerges from interactions: people mixing and moving, hospitals sharing patients and staff, supply networks sharing suppliers, and health services depending on power and water. Agent-based and system dynamics models let these interactions be explored as scenarios, with every assumption visible.
GCRI · Established · service level R0
Agent-based and system dynamics models are complex systems methods that represent individuals, institutions and their interactions to explore how health risk emerges. They are used for epidemics spreading through contact and mobility, cascades between hospitals and power or water, and patient transfer networks, always as scenarios with visible assumptions.
Complex systems and agent-based modelling study systems whose behaviour emerges from interactions among many components. They help explain nonlinear dynamics, tipping points and collective behaviour. In health and biosecurity, complex systems approaches explore how interacting risks can produce sudden, systemic shifts. They support stress testing of policies against emergent behaviour. The canonical description is on the STEM Commons.
Agent-based models represent households, schools, workplaces and travel, so the effect of contact patterns and public health measures on transmission can be explored under stated parameters.
System dynamics models link power, water, staff and supply buffers to service capacity, tracing how a grid outage or heatwave propagates into hospital functions over hours and days.
Networks of referrals and transfers between hospitals are analysed to see where surges concentrate and how resistant organisms can spread between facilities.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Agent-based model | A simulation of many individual agents following rules, from which population-level patterns emerge. |
| System dynamics | A modelling approach using stocks, flows and feedback loops to study how a system behaves over time. |
| Scenario | A plausible description of how the future may unfold under stated assumptions, not a prediction. |
How far each division sits from a large city, with the roads and airports that carry patients and supplies, shown for the Horn of Africa as an example geography for this subject.
Data from the source register feeds the methods; calibration and an independent test gate the estimate and its limits; the decision stays with the competent authority.
Fig. 01Nodes carry their type, metrics and state; connectors show what feeds what; the gates are the validation steps; the timeline is one application. Design of the method's use, not a record of a run.
Datasets and records used by complex systems and agent-based modelling on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Social contact surveys | Mixing matrices by age and setting | OBSERVED |
| Aggregated mobility data from transport and telecommunications | Movement between places | ESTIMATED |
| Hospital transfer records | Referral network structure | REPORTED |
| Facility dependency inventories | Buffers and failure thresholds | OFFICIAL |
Models are evaluated by matching multiple stylised facts and patterns at different scales. Sensitivity and robustness analysis test dependence on assumptions.
| Check | How it is done |
|---|---|
| Pattern-oriented validation | Models must reproduce several observed patterns at different scales, not a single curve |
| Global sensitivity analysis | The parameters that drive most of the outcome range are identified and reported |
| Structural alternatives | Results are compared with simpler or differently structured models before conclusions are drawn |
Many plausible models can reproduce the same patterns. Calibration and validation data are often limited.
Systems Science and Modelling stewards complex systems and agent-based modelling for the Consortium and reviews how it is applied across platforms.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.