GCRI · Campaigns
Campaign evidence
A campaign produces activity that is easy to count, such as impressions, shares and attendance, and outcomes that are hard to establish, such as understanding, trust or safer practice. Campaign evidence is the discipline of measuring each level honestly and claiming no more than the design supports. This page sets out how reach, learning and outcomes are measured, why attribution is difficult, how metrics distort practice, and which evidence funders, agencies and evaluators can rely on.
Campaign evidence on the record.
Campaign evidence: how the risk develops.
Learning metrics and demonstrable outcomes. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Reach is not understanding
Exposure, attention, comprehension, intention and action are separate levels, and evidence at one does not establish the next. A logic model states which level each measure speaks to, so that impressions are not reported as learning or intentions as behaviour.
Attribution needs a comparison
Change during a campaign coincides with news, prices, seasons and other programmes. Without a comparison group, a credible counterfactual or a pre-registered design, a before-and-after difference cannot be credited to the campaign, however large it appears.
Metrics bend practice
When a measure becomes a target it stops measuring well. Campaigns optimised for engagement reward provocative content, platforms change how they count views, and easy metrics crowd out harder evidence. The choice of metric shapes what the campaign becomes.
Evidence travels poorly
Effects found in one country, medium or period often do not replicate elsewhere. Positive evaluations are published more often than null ones, so reviews of the literature can overstate what campaigns achieve. Context has to travel with every result.
Connected activity in South Asia.
Night lights, population density and land cover over South Asia, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Connected activity, for this page
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
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
- 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 EVI (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 vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
- 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.
Connected activity, framed on South Asia.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/NOAA VIIRS · 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
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. 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 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.
- Observed (EO): NASA/NOAA VIIRS (Suomi NPP). 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).
- 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).
- Optional layers (5 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
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- 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
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
Campaign evidence asks whether understanding or behaviour changed.
Evaluations are designed for the Evidence Brief series using OECD DAC criteria (2019). Reach is never reported as impact.
- Evaluation designs.
- Raw evaluation data under terms.
Campaign wave tracker.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Campaign wave tracker
Campaign evidence · Wave 2 · Campaign area North
- People reached14076Active
- Consent complete, % of participants97Normal
- Knowledge score change0.8pointsNormal
- Open feedback items12Watch
Preparedness actions by area
Messages under test
| Prepare a water reserve | A | 61 | Keep |
| Know your warning levels | B | 57 | Revise |
| Check on neighbours | A | 74 | Keep |
Safeguarding and consent
- S-1Minor enrolled without guardian recordPause and verify1 d
- S-2Withdrawal requestData deleted, logged5 d
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Deduplicated reach | persons or accounts reached | per campaign | Platform and site analytics | ESTIMATED |
| Message recall | percent of a sampled audience recalling the message | per survey wave | Post-campaign survey | REPORTED |
| Comprehension gain | difference in test scores before and after | per cohort | Pre and post assessment | OBSERVED |
| Intention to act | mean score on a validated scale | per survey wave | Survey instrument | REPORTED |
| Observed protective action | proportion of a sample observed taking the action | per study | Observation or administrative records | OBSERVED |
| Effect estimate | standardised difference with confidence interval | per evaluation | Controlled or quasi-experimental evaluation | ESTIMATED |
| Pre-registration status | registered or not, with registry and date | per evaluation | Trial and study registries | DECLARED |
| Cost per person reached | currency per person | per campaign | Budget and reach records | ESTIMATED |
Model campaign evidence as a system. Run the cascade.
Assembled from the Nexus Standards area profile Information integrity and trust: 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
- Civil unrest
- Ice-jam flood
- Tropical cyclone
- Heatwave
- HIV epidemic
- Dam failure
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-2Citation and attribution format for UNIsNS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H52Hazard family: Information-integrity attacks (NHS-1 cyber.integrity)NRS-X7Information integrity and public trustNRS-U23Universe platform profile: ReportsNRS-A4Zero-trust verification of standards and conformanceNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H72Hazard family: Novel entities and emerging contaminants (NHS-1 poll.novel-entities)
Observation
- GDELT event database and global knowledge graph (listed for reference)
- Our World in Data datasets (listed for reference)
- Number of countries that adopt and implement guarantees for public access to information
Example geography
- The Horn of Africa: 253 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| 3ie Development Evidence Portal | Impact evaluations and systematic reviews of development interventions, including communication | Free to read |
| Campbell Collaboration systematic reviews | Reviews of social interventions with stated methods and certainty of evidence | Open access, CC BY |
| AEA RCT Registry | Pre-registered randomised trials in the social sciences | Free to read; metadata openly available |
| OSF Registries | Pre-registered study designs and analysis plans | Free to read; metadata CC0 |
| Vetted-researcher data access under the EU Digital Services Act, Article 40 | Data from very large online platforms, including public content and engagement, for research on systemic risks | Access by application through digital services coordinators |
| OECD DAC Evaluation Resource Centre | Evaluation reports from development agencies | Free to read |
| Platform transparency reports | Reach, moderation and enforcement data published by platforms, including under the EU Digital Services Act | Free to read; reuse per platform terms |
How campaign evidence is modelled, measured and tested.
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.
System model
The couplings between the systems in campaign evidence: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Who decides, and what the evidence serves.
Campaigns prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Funders and foundations | Whether to continue, scale or stop funding a campaign | Outcome records by level; effect estimates with intervals; quality of the evaluation design |
| Public health and communication agencies | Which channels and formats to use in the next campaign | Comprehension and recall evidence; cost per person reached; context of each result |
| National audit offices and evaluation units | Whether public spending on campaigns met its stated aims | Logic models; pre-registration records; observed action measures |
| Platform research and transparency teams | Which data to make available to independent researchers | Documented researcher access needs; gaps in published transparency data |
Outputs this topic produces
- Campaign outcome records separating reach, understanding, intention and observed action
- Logic models stating what each measure can and cannot show
- Pre-registered evaluation plans, with null results published alongside positive ones
- Learning summaries recording the context each result came from
What experts ask.
- 01
What should change?
Knowledge, intended action, trusted sources or behaviour, chosen to match the campaign’s aim.
- 02
Compared with what?
The baseline and, where feasible, a comparison group, so change can be attributed with care.
- 03
How long does it last?
Whether effects persist after the campaign or fade within weeks.
- 04
Who was missed?
Which groups the campaign did not reach and why.
What drives the outcome.
Reach is easy to count and weakly linked to effect. Impressions and views say little about understanding. Evaluation research distinguishes outputs (what was delivered), outcomes (what changed for people) and impact (longer-term change attributable to the campaign).
Attribution is the hard part. Other messages, events and policies move the same measures. Without a baseline and some form of comparison, a campaign may claim credit for change it did not cause or miss effects it did have.
Publication bias distorts learning. If only successes are reported, the field learns little. Recording null and negative results is as valuable as recording successes, and it protects the next campaign team from repeating an approach that has already failed elsewhere.
Measures also shape behaviour. A team rewarded for reach will optimise for reach. Agreeing measures of understanding or action before launch keeps attention on the public purpose.
How evidence is gathered, and where it stops.
| Method | What it shows | Its limit |
|---|---|---|
| Baseline and follow-up surveys | Change in knowledge or intentions | Self-report and attrition |
| Comparison designs | Effect relative to a group not reached | Often hard to arrange ethically or practically |
| Administrative data | Behaviour such as service uptake | Many confounding influences |
| Qualitative follow-up | Why the campaign worked or did not | Not generalisable on its own |
How it is studied, and what the methods cannot say.
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why not just report reach?
What is a counterfactual?
Why publish null results?
Why do social media research data sources change?
Are disappointing results published?
Does every campaign need a control group?
Can I see the data behind a result?
Contribute evidence from this page.
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