See suffering more clearly - and act where it may matter most

WSI can help public-health agencies, humanitarian organizations, researchers, and funders compare the scale and concentration of documented suffering within a well-defined topic.

It can support prioritization, track changes over time, highlight severe or under-recognized burdens, improve public communication, and reveal where better data are needed. WSI is designed to inform judgment - not replace it.

WSI is the applied research project: it produces harmonized comparative burden series for specific diseases, humanitarian conditions, and events.

USU is the underlying measurement framework: it combines modeled intensity, duration, and the number of people affected on a common calibrated scale.

Renal colic is intense, time-bounded, commonly assessed on clinical pain scales, and supported by published pain and treatment-response data. A specified, stylized renal-colic trajectory is defined as 1.0 USU.

This is a calibration convention, not a claim that kidney-stone pain is the most important form of suffering. Because the calibration is explicit, alternative anchors can be tested and results can be rescaled.

Physical pain is only one form of suffering. Severe negative experience can also involve breathlessness, nausea, fatigue, panic, fear, grief, humiliation, or disruption of basic life conditions.

USU therefore targets experienced suffering more broadly. Pain provides the initial calibration anchor, but each non-pain state requires its own clear definition, evidence, and uncertainty.

Case counts show how many episodes were reported, but not how intense or prolonged they were. Death counts are essential and remain separate. DALYs and QALYs are established health measures with different purposes.

WSI adds an experiential burden perspective and is intended to be used alongside - not instead of - those measures.

A focused series can hold the source, definitions, time period, and burden model constant across all eligible locations. That makes the comparison much cleaner than adding a different mixture of available harms for every country.

Over time, many focused series can form a useful global evidence library and support country dashboards without forcing them prematurely into one total score.

A completed series will report the source universe, reporting period, inclusion criteria, affected population or episode counts, total modeled burden, burden per 100,000, severity composition, uncertainty intervals, mortality indicators separately, and sensitivity analyses.

It will also document the source coverage, definitions, assumptions, methods, and release version.

Total burden shows where the largest aggregate amount of documented suffering occurred. Per-capita burden shows where that burden was most concentrated relative to population size.

Both are useful, and they can produce different rankings. WSI will present them separately rather than blend them into one weighted score.

Each state is defined as precisely as possible and linked to published evidence, clinical or humanitarian descriptions, validated measures, and clearly documented assumptions.

Intensity and duration are represented as ranges or probability distributions when uncertainty is meaningful. Observed source data remain separate from the modeled USU mapping.

WSI will primarily use official public-health surveillance, humanitarian and disaster datasets, demographic sources, and peer-reviewed research.

Each comparative series will use a common source or harmonized source family and will identify the exact data snapshot and reporting cutoff used.

Absence does not mean absence of suffering. A location may fall outside the source coverage, use an incompatible reporting definition, or lack enough data for the specified period.

Every series will state its eligible universe and explain exclusions.

WSI will use probability distributions and Monte Carlo simulation where appropriate, reporting median estimates and uncertainty intervals rather than a single precise-looking number.

Shared assumptions - such as the duration of a disease state - will be sampled jointly across locations, while location-specific data uncertainty will be handled separately. When rankings are unstable, WSI can show rank probabilities or broad tiers.

Psychological suffering can be included when the state is clearly defined and supported by credible evidence or validated measures. Physical and psychological suffering are not assumed to be identical; they are compared through the narrower question of how negatively the state is experienced over time.

Any mapping for anxiety, depression, grief, trauma, or fear will be treated as context-specific and will require explicit uncertainty and validation.

WSI will not simply add separate series into a country total when the same people and time periods may overlap. Within analyses where co-occurring states matter, the overlap rule will be explicit and sensitivity-tested.

This allows multiple harms to be acknowledged without automatically counting the same experienced distress more than once.

Any attempt to quantify experienced suffering involves judgment. WSI's goal is not to pretend otherwise, but to make the important choices visible: the anchor, state definition, intensity range, duration, overlap rule, and uncertainty.

Because the major assumptions and methods will be documented, researchers can examine how alternative choices might affect the conclusions.

WSI estimates experienced suffering associated with the specific states included in each series. It does not measure a person's worth, dignity, rights, productivity, or overall value of life.

Deaths and other mortality measures remain visible as companion outcomes rather than being automatically converted into experienced-suffering units.

DALYs and QALYs summarize health loss or health-adjusted time. HDI summarizes dimensions of human development. Other indices may combine economic, political, or security indicators.

WSI addresses a different question: how much modeled adverse experience is associated with a clearly defined condition or event across the locations included in one series. These measures can be used together because each reveals a different aspect of reality.

Possibly, but only after a sufficiently broad set of condition-specific series has comparable coverage and the effects of overlap and missing domains can be evaluated responsibly.

The condition-specific series are the immediate foundation. As coverage grows, WSI can test whether a broader country-level view becomes sufficiently comparable, stable, and useful.

The intensity-over-time structure may be relevant to animal-welfare research, but the present USU calibration and WSI programme are human-centered.

Any non-human application would require species-specific behavioral and physiological evidence, animal-welfare expertise, and separate validation. Human and non-human estimates would not be combined by default.

WSI welcomes collaboration on data sourcing, domain expertise, state mapping, uncertainty modeling, software, replication, visualization, and independent review.

Researchers can also apply USU to their own data, propose alternative mappings, scrutinize future WSI methods, and publish critiques or extensions.