GCRI · Biotechnology and Biosecurity
Epidemiology and public health science for biotechnology and biosecurity
How epidemiology and public health science is applied in Biotechnology and Biosecurity. Epidemiology studies the distribution and determinants of health and disease in populations. It provides the evidence used to detect outbreaks, estimate burden and evaluate interventions.
Epidemiology and public health science for biotechnology and biosecurity on the record.
- MethodEpidemiology and public health science
- StewardHealth Nexus
- Applied inBiotechnology and Biosecurity
- Data5 inputs
- ChecksValidation
- Canonical pageSTEM Commons
What epidemiology and public health science does here.
Epidemiology studies the distribution and determinants of health and disease in populations. It provides the evidence used to detect outbreaks, estimate burden and evaluate interventions. In health and biosecurity and food and agriculture, epidemiological evidence informs preparedness, resource allocation and the economic consequences of disease. It shows how health shocks interact with travel, labour, supply chains and public finance. The canonical description is on the STEM Commons.
- 01
Methods used here
cohort and case-control studies; disease surveillance; transmission modelling; outbreak investigation; burden of disease estimation; spatial epidemiology.
- 02
Validation
Findings are checked through replication, sensitivity analyses and comparison of independent surveillance streams. Transmission models are assessed by out-of-sample forecasting of case counts.
Environmental exposure in West Africa.
Population density, daytime surface heat and haze over West Africa, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Environmental exposure, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS NOAA-20 Deep Blue AOD (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 2 km grid
- Uncertainty
- Satellite measure of haze, smoke and dust through the whole air column on the day shown; an exposure indicator, not ground-level PM2.5, an air quality index or a health warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra NDVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Environmental exposure, framed on West Africa.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS and VIIRS atmosphere products, NASA LANCE and LAADS DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (14 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
What the method consumes.
Datasets and records used by epidemiology and public health 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 |
|---|---|---|
| Notifiable disease reporting systems | Input | OBSERVED |
| Hospital and laboratory records | Input | OBSERVED |
| Household and health surveys | Input | OBSERVED |
| Vital registration | Input | OBSERVED |
| Genomic surveillance | Input | OBSERVED |
Epidemic model.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Epidemic model
Biotechnology and biosecurity · Epidemiology and public health · Run R-4141
Epidemic curve
Method card
- Method
- Epidemiology and public health science
- Model
- SEIR, fitted
- Generation time
- 4 days
- Label
- MODELLED
Parameters
| Rt | 1.3 | 0.89 | 1.6 |
| Doubling time (days) | 16 | 5 | 31 |
| Reporting fraction | 0.4 | 0.3 | 0.8 |
How results are checked.
Findings are checked through replication, sensitivity analyses and comparison of independent surveillance streams. Transmission models are assessed by out-of-sample forecasting of case counts.
Reporting delays, under-ascertainment and confounding bias estimates. Behaviour change during outbreaks alters the parameters models rely on.
SEIR on a network of places.
An outbreak seeded in one place spreads through a small-world network by the share of contacts people make elsewhere; play it to see the order of arrival and how the timing of measures moves the peak. Teaching model with stated illustrative values, not a prediction. The map on this page shows West Africa; the model itself is not tied to a place.
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
- 3.91 per 1,000 a day
- Day of the peak
- 129
- Share ever infected
- 57%
- 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 | 0.03 | 0.0 |
| 34 | 0.34 | 0.2 |
| 51 | 1.06 | 1.5 |
| 68 | 1.95 | 4.1 |
| 85 | 2.84 | 8.3 |
| 102 | 3.49 | 13.7 |
| 119 | 3.86 | 20.0 |
| 136 | 3.89 | 26.6 |
| 153 | 3.74 | 33.1 |
| 170 | 3.51 | 39.3 |
| 187 | 3.29 | 45.1 |
| 204 | 2.81 | 50.3 |
| 221 | 1.89 | 54.3 |
| 238 | 1.00 | 56.7 |
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 Biotechnology and Biosecurity in Foundry
- Tested at Biotechnology and Biosecurity in Universe
- Codified in Health and Biosecurity in Standards
- Published in Biotechnology and Biosecurity in Reports
- Taught in Faculty of Health and Society in Academy
Topics that rely on this method.
Build the system model. Run the cascade.
Assembled from the Nexus Standards area profile International Health Regulations alignment: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
Systems and couplings
Controls
NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H83Hazard family: Health system capacity failure (NHS-1 health.system)NRS-H41Hazard family: Animal-to-human spillover (NHS-1 health.zoonotic)NRS-H112Hazard family: Governance and institutional failure (NHS-1 soc.governance)NRS-H120Hazard family: Structural fragility of interconnected systems (NHS-1 sys.fragility)NRS-H29Hazard family: Air pollution episodes (NHS-1 poll.air-quality)NRS-H40Hazard family: Blood-borne and sexually transmitted infection (NHS-1 health.bloodborne)
Observation
- WHO Global Health Observatory OData API (including SPAR capacity scores) (listed for reference)
- e-SPAR public portal (listed for reference)
- WHO Disease Outbreak News (listed for reference)
- International Health Regulations (IHR) capacity and health emergency preparedness
Example geography
- West Africa: 59 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
Who maintains the method.
Health Nexus stewards epidemiology and public health science for the Consortium and reviews how it is applied across platforms.
Coupled risk, applied response.
The sectors pandemic touches and how strongly they depend on each other: what a study has to observe and model together.
Choose a context
Sectors · PandemicStress
Pillars · PandemicKPI
In this contextDependence or handoff, heavier is strongerOutside this context
Programme yearAll phases
Context
Pandemic
Workforce absence ripples from clinics into grid operations, logistics and farm labour.
W · E · I · F · H · B
Risk
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.41 share of total
Hover a corner, a line or a row to trace it across both sides.
Route
Applied to pandemic
L · F · U · S · R · A
Response
- Pillars
- 4 of 6
- Handoffs
- 10 of 18
- Loops
- 5 closed
Expected value
- What is at stake
- $60B+expected losses a yearCommission on a Global Health Risk Framework, 2016
- Return on resilience
- –no published benchmark
- Avoided loss
- –no published benchmark
Hover a pillar, a line or a row to read how it is applied.
A: a teaching cascade (shock 0.6, gain 0.35, four rounds) over teaching values for a typical city-region, not measurements. B: illustrative applications and the KPI each pillar answers for; values are published benchmarks, cited, not forecasts. Open events: NASA EONET, live.
Where this page leads across the Consortium.
The model, the data and the uncertainty.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Uncertainty bands
How far the outlook for epidemiology and public health science for biotechnology and biosecurity could spread, shown as ranges rather than a single line.
- Central estimate
- median of the ensemble
- Ranges
- likely and very likely, in IPCC calibrated language
- Ensemble
- members, scenarios and initial conditions stated
- Read with
- the sensitivity of the result to each input
Questions and answers.
What are the limits of epidemiology and public health science in this field?
How are results checked?
Are the values on this page real?
Where else is this method applied?
Contribute evidence from this page.
Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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Bring a method, a dataset or a question.
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