Comparing emergency health law
Public health emergency powers, review provisions and their use are coded across countries, so legislatures can see options and their record.
GRF · Health and Biosecurity Governance
Policy, institutional and decision science for health and biosecurity governance
Policy and institutional science studies how laws, agencies and international bodies shape public decisions. In health and biosecurity governance it compares emergency law, One Health mechanisms, regulatory systems and cooperation agreements, and traces why lessons from past emergencies were or were not applied.
01Contents
Policy, institutional and decision science for health and biosecurity governance in five parts.
02Application
What policy, institutional and decision science does here.
Policy, institutional and decision science studies how public decisions are made, implemented and evaluated. It examines how institutions coordinate across sectors and levels of government when facing shared risks. In health and biosecurity, policy science identifies governance gaps where responsibility for cross-sector risk is unclear. It supports the design of mandates, coordination mechanisms and accountability. The canonical description is on the STEM Commons.
Tracing review recommendations
Recommendations from pandemic reviews are tracked against later reforms to show which were adopted and which stalled.
Mapping cooperation
Regional and global health institutions are mapped by mandate, membership and funding to show overlaps and gaps.
03Monitor
Survey analysis.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Survey analysis
Health and biosecurity governance · Policy, institutional and decision · Run R-6966
Estimates stableGRF · Health and Biosecurity Governance
Estimates
robust standard errors
| IHR core capacity score | 0.13 | 0.12 | [−0.6, 0.4] | No |
| Events assessed under Annex 2 | 0.52 | 0.18 | [−0.3, 0.6] | No |
| Notifications within 24 hours | 0.14 | 0.11 | [−0.3, 0.8] | Yes |
| Simulation exercises held | 0.15 | 0.08 | [−0.4, 0.7] | No |
Method card
- Method
- Policy, institutional and decision science
- Sample
- 7732 obs
- Design
- stratified, weighted
- Label
- MODELLED
Residuals by group
04Data
What the method consumes.
Datasets and records used by policy, institutional and decision science on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Health legislation | Legal frameworks | Published statistics |
| Review and inquiry reports | Lessons and recommendations | REPORTED |
| Treaty records | International commitments | Published statistics |
| IHR assessments | Capacity records | DECLARED |
05Decision model
When measures start, and how much they buy.
How the start day and the strength of contact measures change the size and timing of the peak and the share ever infected, the trade-off a public health decision weighs. Teaching model with stated illustrative values, not a prediction.
Controls
- Basic reproduction number R0
- 2.5
- Latent period
- 3.0 days
- Infectious period
- 5.0 days
- Share of contacts made in other places
- 8%
- Places in the network
- 24
- Measures start on day
- 40
- Contact reduction from measures
- 40%
- Days simulated
- 240 days
Readouts
- Peak new infections
- 6.72 per 1,000 a day
- Day of the peak
- 116
- Share ever infected
- 59%
- Places reached
- 100%
- Reproduction number under measures
- 1.50
Numbers, methods and sources
| Day | New infections per 1,000 | Cumulative infected (%) |
|---|---|---|
| 0 | 0.00 | 0.0 |
| 17 | 0.05 | 0.0 |
| 34 | 0.71 | 0.5 |
| 51 | 1.98 | 3.1 |
| 68 | 3.13 | 7.4 |
| 85 | 4.55 | 14.0 |
| 102 | 6.14 | 23.2 |
| 119 | 6.68 | 34.3 |
| 136 | 5.40 | 44.8 |
| 153 | 3.25 | 52.0 |
| 170 | 1.58 | 55.9 |
| 187 | 0.69 | 57.7 |
| 204 | 0.29 | 58.5 |
| 221 | 0.12 | 58.8 |
| 238 | 0.05 | 59.0 |
Methods
- SEIR compartments Kermack and McKendrick (1927), Proc. R. Soc. A 115
- Metapopulation coupling by mobility Balcan and others (2009), PNAS 106
- Small-world network Watts and Strogatz (1998), Nature 393
- Modelling infectious diseases Keeling and Rohani (2008), Princeton University Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page's map can draw:
- Cities Natural Earth
- Airports Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Health and Biosecurity Governance in Foundry
- Tested at Health and Biosecurity Governance in Universe
- Codified in Health and Biosecurity in Standards
- Published in Health and Biosecurity Governance in Reports
- Taught in Faculty of Health and Society in Academy
06Validation
How results are checked.
Conclusions are tested through comparative cases, counterfactual evaluation and peer review. Implementation outcomes are monitored against stated objectives.
| Check | How it is done |
|---|---|
| Case selection | Comparisons state which countries were chosen and why |
| Text versus practice | Legal text is distinguished from evidence of implementation |
| Currency | Treaty and law status is dated |
Findings are often context specific and difficult to transfer. Political dynamics can override technically preferred options.
07Implementation
From mandate to evaluation, by pillar.
The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction.
- Mandate and problem framing Competent authority (outside the programme)
A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009) - Evidence and system model Foundry
The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2 - Options appraised with scenarios Foundry
Instruments are compared under scenarios, with uncertainty shown. Hood (1983) - Exercise with stakeholders Universe
The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3 - Standard or guidance drafted Nexus Standards
What works is codified as a standard or guidance, open to comment. Nexus Standards process - Decision by the authority Competent authority (outside the programme)
The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009) - Capacity and training Risk Academy
Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2 - Monitoring and public report Reports
Indicators are published with sources, limits and corrections. OECD (2014), principle 5 - Evaluation and revision Nexus Standards
Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)
Methods
- Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
- Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Health and Biosecurity Governance in Foundry
- Tested at Health and Biosecurity Governance in Universe
- Codified in Health and Biosecurity in Standards
- Published in Health and Biosecurity Governance in Reports
- Taught in Faculty of Health and Society in Academy
09Sector signature
Who a decision on policy, institutional and decision science for health and biosecurity governance reaches.
The sectors a policy on policy, institutional and decision science for health and biosecurity governance has to coordinate: a choice in one ministry lands in the others.
Select corners · hover lines6 / 15 relations
Signature
Health and its partners
Health gives workforce for operations to infrastructure (0.3), farm labour to food (0.3) and utility workforce to water (0.2).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.42 share of total
Strongest relations in play
- Water → Food · irrigation0.8
- Food → Health · nutrition0.7
- Infrastructure → Water · pipes, dams and treatment works0.6
- Water → Health · drinking water and sanitation0.7
10Stewardship
Who maintains the method.
Policy Nexus stewards policy, institutional and decision science for the Consortium and reviews how it is applied across platforms.
11Instruments and commitments
Instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Policy instrument matrix
The kinds of instrument available on policy, institutional and decision science for health and biosecurity governance, by level of government and cooperation.
| Instrument type | Local | National | Regional | Global |
|---|---|---|---|---|
| Regulatory | Zoning, building codes | Laws, standards, licensing | Harmonised rules | Conventions and treaties |
| Economic | Local levies, grants | Budget lines, taxes, insurance schemes | Risk pools, regional funds | Financing mechanisms |
| Information | Local warnings | Disclosure, early warning, statistics | Data sharing arrangements | Global monitoring and reporting |
| Institutional | Local committees | Lead agencies, coordination councils | Regional bodies and secretariats | Multilateral mandates |
| Cooperative | Community agreements | Partnership compacts | Memoranda and joint programmes | Agreements and joint commitments |
Sendai Framework for Disaster Risk Reduction · UNDRRParis Agreement · UNFCCC2030 Agenda and the Sustainable Development Goals · United NationsInternational Health Regulations · WHO
12Connected
Where this page leads across the Consortium.
13Questions
Questions and answers.
What are the limits of policy, institutional and decision science in this field?
Findings are often context specific and difficult to transfer. Political dynamics can override technically preferred options.
How are results checked?
Conclusions are tested through comparative cases, counterfactual evaluation and peer review. Implementation outcomes are monitored against stated objectives.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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