The Global Centre for Risk and Innovation (GCRI)
The methods Health Nexus relies on, the assumptions they carry and the limits of what they can show.
GCRI · Established · service level R0
The Health Nexus methods page sets out the methods the platform relies on, among them epidemiology and public health science, molecular and life sciences, and probability and statistics, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.
Fig.How a finding is reviewed before it is published. Design, not a record.
How far each division sits from a large city, with the roads and airports that carry patients and supplies, shown for Indonesia as an example geography for this subject.
| Source | Why it matters here | How it is reported |
|---|---|---|
| Case ascertainment | Reported cases depend on testing and care-seeking | Corrections for reporting, with assumptions stated |
| Transmission parameters | Estimated early in an outbreak from few data | Ranges, updated as data accrue |
| Behaviour | Contact patterns and compliance change during an epidemic | Scenarios rather than fixed parameters |
| Health-system capacity | Staffed beds differ from physical beds | Capacity ranges from facility data |
| Excess mortality baselines | Depend on the counterfactual model | Multiple baselines compared |
Health evidence is graded with GRADE where recommendations are concerned, and modelled projections are always labelled as scenarios.
Each analysis lists its assumptions and the data it depends on.
Ranges and confidence are reported alongside central estimates.
Models are checked against observations and, where possible, against other models.
What an analysis cannot show is stated beside what it can.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Uncertainty quantification | Characterising and propagating the uncertainties in a model to state confidence in its outputs. |
| Sensitivity analysis | Repeating an analysis under different assumptions to show how much the result depends on them. |
| Model validation | Comparing model predictions with independent observations to judge fitness for a stated use. |
| Epidemiology and public health science | Epidemiology studies the distribution and determinants of health and disease in populations. |
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
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.