Welcome to the Health Vulnerability and Adaptation Toolkit (HVAT)

Built by Principal Economics for the Ministry of Health, HVAT is your gateway to understanding how climate change affects health and well-being across Aotearoa New Zealand. We model real-world impacts—from extreme heat stressing urban communities to regional rivalry scenarios (SSP3-7.0) doubling emissions and driving 3.6°C warming by 2100—so everyday New Zealanders, whānau, and policymakers can prepare and adapt.

Why HVAT?

Climate change isn’t abstract—it’s hotter summers in Auckland, wetter winters in the South Island, and greater risks to vulnerable groups like tamariki and kaumatua. Our toolkit draws on Ministry data to:

  • Explore Environmental Indicators: Track extreme heat, cold, rain, wind, fire, dry, and wet events at local levels (e.g., ECI metrics for your region).
  • Project Future Scenarios: Dive into four SSP pathways, from sustainable SSP1-2.6 (below 2°C warming, net-zero CO2 by 2050) to fossil-fuelled SSP5-8.5 (over 4°C by 2100), showing temperature, precipitation, and wind changes.
  • Assess Health Vulnerabilities: Link data to hospital admissions, drinking water risks (campylobacteriosis, cryptosporidiosis, giardiasis), heating fuel reliance, and vehicle fleet resilience.
  • Empower Adaptation: Spot patterns to inform local action, like cooling centers in high-heat zones or resilient infrastructure under middle-of-the-road SSP2-4.5 (2.7°C by 2100).

Key Climate Scenarios

Scenario Description Warming by 2100 Key Insight for NZ Health
Sustainability (SSP1-2.6) Assumes the world shifts gradually toward a more sustainable path, emphasising more inclusive development that respects environmental boundaries. Warming stays below 2°C, with net zero CO2 emissions reached by 2050. Below 2°C Optimistic path: Manageable heat/cold extremes with proactive adaptation.
Middle of the Road (SSP2-4.5) Assumes the world follows a path in which social, economic, and technological trends do not shift markedly from historical patterns. Warming reaches 2.7°C by 2100. 2.7°C Balanced risks: Increased rain/wind events straining emergency services.
Regional Rivalry (SSP3-7.0) Assumes the world becomes more focused on national and regional security issues, and there is no additional climate policy. CO2 emissions approximately double from current levels by 2100 and warming reaches 3.6°C by 2100. 3.6°C High vulnerability: Amplified fire/dry risks in rural areas.
Fossil-Fuelled Development (SSP5-8.5) Represents the high end of the range of future scenarios. Assumes the world places increasing faith in competitive markets, innovation, and participatory societies to produce rapid technological progress and development of human capital as the path to sustainable development, with warming of more than 4°C by 2100. >4°C Worst-case: Severe heat waves overwhelming hospitals and water systems.

Get Started

Head to Data Explorer to filter by location (e.g., Auckland or Southland), season, and metric. Explore hospital risk curves or vehicle fleet stats to see how climate hits home.

HVAT is a collaborative tool—your feedback shapes future updates. Questions? Contact Principal Economics at [email protected].

Kia ora from the team—let’s build a resilient Aotearoa together.

Policy Explorer Placeholder

Future content for policy scenarios, e.g., SSP overlays on vulnerability indices.

Climate Glossary – HVAT

This glossary explains the key indicators and concepts shown in the dashboard.
All definitions are taken directly from the August 2025 Principal Economics report for the Ministry of Health.

Extreme Climate Index (ECI) Indicators

(ECI Indicators tab)

  • Extreme Heat (eci_heat)
    Composite measure of days above 25 °C plus consecutive hot-day spells (3, 5, or 10 days). Tracks heatwave frequency and duration. Strong predictor of heat-related hospital admissions.

  • Extreme Cold (eci_cold)
    Composite of frost mornings (<0 °C), cold nights (<5 °C), ice days (<0 °C max) and cold days (<10 °C max). Linked to winter illness and energy demand.

  • Extreme Dry (eci_dry)
    Six metrics of dry spells: single dry days (<1 mm rain) and consecutive dry periods (3–20 days). Proxy for drought, fire risk and pollen seasons.

  • Extreme Rain (eci_rain)
    Seven daily rainfall intensity thresholds (≥10 mm up to ≥150 mm). Tracks heavy rainfall events associated with flooding and waterborne disease.

  • Extreme Wet (eci_wet)
    Wet days (≥1 mm) plus consecutive wet spells (3–15 days). Indicator of prolonged damp conditions linked to mould and respiratory illness.

  • Extreme Wind (eci_wind)
    Days with average wind speed exceeding 5, 7.5, 10, 15 or 20 m/s. Linked to power outages, infrastructure damage and transport disruption.

  • Extreme Fire (eci_fire)
    Seasonal Fire Weather Index (FWI) based on temperature, humidity, wind and rainfall. Pilot indicator of wildfire danger.

Climate Model Projections

(Climate Model Projections tab)

  • Sustainability (SSP1-2.6)
    Low-emissions pathway with strong global cooperation. Net-zero CO₂ by 2050, warming stays below 2 °C.

  • Middle of the road (SSP2-4.5) (default)
    Continuation of current social, economic and technological trends. Warming reaches ~2.7 °C by 2100.

  • Regional rivalry (SSP3-7.0)
    Fragmented world focused on national security, limited climate policy. Warming reaches ~3.6 °C by 2100.

Drinking Water Indicators

(Drinking Water tab)

  • Campylobacteriosis
    Most common bacterial gastrointestinal illness in New Zealand. Often linked to untreated drinking water after heavy rainfall (5-year moving average rate per 100,000).

  • Cryptosporidiosis
    Protozoan parasite commonly associated with contaminated surface water following heavy rain or flooding.

  • Giardiasis
    Protozoan waterborne illness; notifications frequently spike after flooding events.

Heating Fuel

(Heating Fuel tab)

  • Household Heating Fuel Types (air_heating)
    Proportion of dwellings using wood, coal, electricity, gas, etc. (Census 2013, 2018, 2023). Solid-fuel burning is the main source of winter PM₂.₅ in many towns.

Vehicle Fleet Statistics

(Vehicle Fleet Stats tab)

  • Vehicle Age Profile (air_fleetage)
    Average age and age-band distribution of the light vehicle fleet by Territorial Authority (2025 snapshot). Older fleets emit more PM₂.₅ and NO₂.

  • Number of Motor Vehicles by Type (air_fleettype)
    Count of light vehicles, heavy vehicles, motorcycles, etc., by Territorial Authority. Proxy for transport-related air pollution hazard.

Hospital Admissions

(Hospital Admissions tab)

  • Temperature-Related Hospital Admission Risk Curves
    Relative risk (RR) of hospital admission by temperature percentile for different demographic groups. Shows how risk changes with heat and cold extremes.

Source
Principal Economics (August 2025 draft), Vulnerability and Adaptation Assessment – Technical documentation: Indicators, prepared for the Ministry of Health.