Social impacts
Codes SO1 to SO10. The largest group in POESE, and the one that answers who bears the cost.
Ten metrics cover four distinct concerns: distributional equity, accessibility, health and safety.
The metrics
| Code | Metric | Applies to |
|---|---|---|
| SO1 | Percentage of individuals experiencing delayed journeys by demographic group (%) | Short and long-term |
| SO2 | Percentage of individuals experiencing cancelled journeys by demographic group (%) | Short and long-term |
| SO3 | Geographical distribution of individuals experiencing delayed journeys by demographic group | Short and long-term |
| SO4 | Geographical distribution of individuals experiencing cancelled journeys by demographic group | Short and long-term |
| SO5 | Decrease in the number or percentage of a population group able to access a type of destination from home within a given proximity by a specified transport mode | Long-term only |
| SO6 | Geospatial distribution of increased air pollutant emission across demographic groups (μg/m³) | Long-term only |
| SO7 | Increased burden of disease | Long-term only |
| SO8 | Number of slightly injured individuals | Short and long-term |
| SO9 | Number of seriously injured individuals | Short and long-term |
| SO10 | Number of fatalities | Short and long-term |
Distributional equity: SO1 to SO4
Whether in the form of journey delay or cancellation, operational performance loss affects users' access to employment, education, healthcare and other essential services.
These impacts could be unevenly distributed, with vulnerable groups experiencing a greater burden.
Assessing the disproportionate delay and cancellation effects across population groups, and identifying their geographical distributions, is therefore essential for incorporating equity into resilience assessment. It enables adaptation strategies to explicitly target vulnerable populations.
Why both percentage and geography are measured
SO1 and SO2 answer which groups are affected. SO3 and SO4 answer where they are.
The pair matters because an intervention has to be built somewhere. Knowing that a particular demographic group is disproportionately affected does not tell you where to put the flood defence or the alternative bus route. The geographical distribution does.
Accessibility: SO5
Decreases in accessibility for different population groups are particularly relevant for long-term disruption, because sustained limitations could exacerbate social inequity.
SO5 measures the decrease in the number or percentage of a population group able to reach a type of destination from home, within a given proximity, by a specified transport mode.
Accessibility is a different loss from delay
Delay means a journey took longer. Accessibility loss means the destination is no longer reachable at all within a tolerable range.
The first is an inconvenience that compounds; the second removes an option from someone's life. Over a long recovery period, that is how disruption turns into inequity.
SO6: Spatial distribution of pollution
Increased air pollutant emissions may concentrate in specific spatial areas, disproportionately affecting residents in those locations.
This metric takes the emissions computed in environmental impacts and asks where they land, and on whom.
Rerouting moves harm as well as traffic
Traffic diverted from a flooded main road does not vanish. It travels through other streets, and the people living on those streets absorb the resulting air quality change.
They are typically not the people the diversion was arranged for.
SO7: Increased burden of disease
The rise in air pollutants during long-term disruptions could be substantial, and lead to a greater burden of disease such as lung cancer, asthma and stroke.
This metric reflects the induced health issue of disruptions, which is a measure of social impact.
Safety: SO8 to SO10
Severe weather conditions could increase traffic accident risk for two separate reasons:
| Cause | Mechanism |
|---|---|
| Conditions | Reductions in visibility and vehicle control |
| Rerouting | Traffic moving from safer major roads onto less suitable minor residential streets |
Both may induce additional safety issues, usually measured by the number of casualties and fatalities.
| Code | Severity |
|---|---|
| SO8 | Slightly injured individuals |
| SO9 | Seriously injured individuals |
| SO10 | Fatalities |
The rerouting mechanism is easy to miss
The first cause is intuitive: bad weather makes driving harder.
The second is a consequence of the model rather than the storm. When a major road closes, traffic redistributes onto residential streets that were never designed to carry it, near pedestrians and cyclists who did not expect it. The risk is created by the diversion, not the rain.
Required input data
The social metrics split into two groups with very different data requirements.
| Metrics | Source |
|---|---|
| SO1 to SO6 | Obtained directly from agent-based model outputs, for example comparing agents' daily trips with a baseline |
| SO7 to SO10 | Can only be estimated based on external datasets and/or assumptions |
SO7 to SO10 are not model outputs
Disease burden, injuries and fatalities cannot be read off a transport simulation. They require external epidemiological and casualty data, plus assumptions linking exposure or traffic conditions to outcomes.
Any figure reported against these four codes should carry its assumptions with it, and be presented with appropriately wider uncertainty than the directly simulated metrics.
A numbering overlap in the source
The handbook's input section describes "SO1 to SO6" as model-derived and "S7-10" as externally estimated, while its metric descriptions group SO1 to SO4, then SO5, SO6 and SO7 individually, and SO8 to SO10 together.
SO7 therefore appears in both groupings. It is listed above as externally estimated, consistent with the input requirements, since disease burden cannot come from the transport model.
Where this leads
Several social impacts carry a monetary valuation in economic impacts: injuries and fatalities become EC9, and social inequity itself becomes EC10.