1.6 - Development, governance and resilience
Explain how unequal access to resources, decisions by governments and the geography of settlements shape tectonic disaster impacts, using careful comparisons rather than a simple rich–poor rule.
Unequal capacity to cope
People exposed to the same hazard can have very different chances of surviving and recovering because their resources and opportunities differ.
Vulnerability and resilience
Vulnerability is susceptibility to harm under a hazard. Resilience is the capacity to resist, absorb, adapt to and recover from its effects while sustaining essential functions.
Housing is a direct link between inequality and injury. A household unable to afford safe construction may occupy an unreinforced building or a steep, unstable site. Shaking then becomes collapse or a landslide, rather than merely an inconvenience. Tenure insecurity can discourage investment and make displaced renters less able to access reconstruction support.
Education affects whether people understand warnings and know evacuation routes, but years of schooling are an imperfect measure of hazard knowledge. Locally trusted advice, accessible language and repeated drills can support people with different levels of formal education. A technically accurate message fails if it cannot be heard, understood or acted on.
Healthcare influences survival after injury and continuity of treatment. A damaged hospital, an unaffordable journey or interrupted medicine can turn an initially survivable event into prolonged illness. Income opportunities influence savings, insurance access and the ability to rebuild a livelihood. Daily-paid workers may lose income immediately when transport or workplaces close; a household with savings can absorb a longer interruption.
These mechanisms interact. A safer evacuation shelter may exist, but a person with limited mobility needs assistance to reach it; a fishing household may hesitate to leave equipment that sustains its income. Age, disability, gender, legal status and social networks can therefore create differences within the same income group. Strong community organisation can improve resilience even where money is scarce.
Governance and settlement geography
Governance changes who is protected before a hazard and how effectively resources reach people afterwards.
Governance concerns how decisions are made, implemented and held accountable. National governments can fund monitoring, set building standards and coordinate large emergencies. Local governments translate those policies into inspections, land-use decisions, route planning and shelter provision. A strong written code achieves little if construction is not inspected, informal settlements are excluded or corruption undermines enforcement. Equally, effective local teams cannot repair a destroyed national transport network without wider support.
Population density can increase the number of people and assets exposed within the strong-shaking zone. Dense streets and building collapse can impede evacuation and rescue. Yet density can also support nearby hospitals, skilled responders and efficient communication. The relevant question is how density combines with construction, services and the hazard footprint.
Urbanisation can concentrate growth faster than safe housing and infrastructure are supplied. Unplanned expansion onto unstable slopes or low coastal land creates exposure. However, a well-managed city can have redundant water networks, reinforced buildings and fast rescue. Urban and rural are not automatic synonyms for unsafe and safe.
Isolation reduces accessibility: damaged bridges, mountain roads or communications may delay information, supplies and medical evacuation. A remote village may have few people exposed, yet lose its only access route. A connected city may receive aid faster but suffer much greater total disruption because more systems are interdependent. Accessibility can change during the event, so maps of normal travel times need a scenario for damaged routes.
Development provides resources; governance determines how they are used and shared; geographical context affects both exposure and access. None works as a complete explanation alone.
Contrasting event contexts
Historical event comparisons are strongest when they connect a specific physical setting to identifiable human mechanisms.
| Context at the time | Event and physical setting | Human factors and observed implications |
|---|---|---|
| Developing, lower-income context | Nepal, April–May 2015: main shock , followed by ; mountain terrain and landslides | Vulnerable masonry housing and disrupted mountain access compounded losses. The World Bank's 2021 account reports 8,970 deaths for the sequence. The 2015 assessment separated USD5.2 billion physical damage from USD1.9 billion economic loss. |
| Emerging-economy context | Philippines, Pinatubo 1991: VEI 6 eruption coinciding with Yunya's rain | PHIVOLCS–USGS monitoring and evacuation reduced pyroclastic-flow exposure. Wet ash still collapsed vulnerable roofs; later rainfall remobilised deposits into lahars. Preparedness success and serious residual vulnerability existed together. |
| Developed, high-income context | New Zealand, Kaikōura 14 November 2016: , complex fault rupture, landslides and local tsunami | MCDEM's May 2017 report records two fatalities, but damaged transport isolated communities and infrastructure losses extended to Wellington. National support capacity did not remove the consequences of a vulnerable coastal transport corridor. |
Sources: World Bank Nepal country brief, Nepal recovery account, 2021, USGS roof survey of Pinatubo, GeoNet event account and MCDEM post-event report, pp5–7.
Nepal and Kaikōura have the same main-shock magnitude, yet profoundly different mortality totals. This is evidence that magnitude alone is insufficient. It does not prove that national income explains the entire difference: Nepal's figure covers a sequence, exposure and construction differ, and shaking is not identical everywhere at a given magnitude. Pinatubo adds a different hazard type, so its raw fatalities are not a controlled earthquake comparison. Its value is showing that scientists, planners and communities can reduce losses in an emerging economy while an interacting storm changes the residual hazard.
Avoid describing all residents of a country as equally resilient. Compare who had safe housing, whose services were restored and who remained displaced. National averages can conceal a successful city response alongside neglected rural or marginalised communities.
Making comparisons comparable
Statistics help compare impacts only when the event boundaries, denominators and monetary definitions are consistent.
Matching magnitudes controls one factor, not depth, distance, duration or secondary hazards. Record the counting period and whether deaths are direct, indirect or missing people presumed dead. For damage, use the same definition, currency and price year. Absolute losses indicate the scale of destroyed assets; loss as a percentage of GDP indicates a burden relative to the national economy. GDP is annual economic output, not a stock of property, so this percentage is a comparison of burden rather than a literal fraction of all wealth destroyed.
For illustration, suppose two original hypothetical magnitude 7.0 events use identical reporting rules:
| Measure | District A | District B |
|---|---|---|
| Population exposed to severe shaking | 200,000 | 50,000 |
| Direct deaths | 400 | 150 |
| Direct damage, constant-price USD | 2 billion | 0.5 billion |
| National annual GDP, same price year | 100 billion | 10 billion |
Use equivalent exposure thresholds and the same counting period. The units in each monetary ratio must match.
A has deaths per 100,000 exposed; B has 300. A's absolute death toll is larger, but B's mortality rate among those exposed is higher. A's damage is 2% of GDP; B's is 5%. B therefore faces a greater relative economic burden despite its smaller monetary loss. These results suggest questions about construction and capacity; they do not identify the cause on their own.
In a real comparison, verify how exposure was estimated, whether informal homes and livelihoods were valued, and whether missing damage entries mean unreported rather than zero. Use ranges if estimates disagree. Combining physical records, statistical rates and local accounts gives a more defensible explanation than a league table of national development labels.