A plain-language read on candidate policy problems for Stage 1 — my commentary on your four options and others worth considering. A more detailed briefing sits in the second tab.
Status Working draft for discussionPrepared 1 June 2026Scope Stage 1 proof-of-conceptHazard focus Heat & flood (best-evidenced)
A plain read on the options — no scoring, no ranking. My commentary on the four you flagged, then others worth considering, and a few I'd hold for later.
Your four options — my read
1 · Heat in poor-quality / thermally inefficient homes (renters, low-income)
The strongest of your four for a first pass. The vulnerability logic is clean — exposure comes from the building fabric, low capacity from not owning (or not affording to run) the home — so you're not leaning on a contested causal story. It also sits on a live lever: the minimum rental standards (efficient electric cooling in the main living area of all rentals by 2030). And the evidence is largely off-the-shelf — the Cooling & Greening Heat Vulnerability Index already combines heat exposure, sensitivity and adaptive capacity down to SA1. Watch-outs: the HVI is urban-only, so regional renters thin out, and "poor-quality housing" needs structural framing to avoid labelling places.
2 · Flood insurance affordability / availability
The most live in public debate (APRA's March 2026 insurance climate vulnerability assessment; the new Victorian flood hazard ratings) and a textbook market-failure story. The honest catch is data: hazard and social layers are public, but the granular insurance-affordability layer largely sits with insurers — the Actuaries Institute's affordability-and-equity work is the realistic public proxy, and its headline figures are national, so you'd derive a Victorian cut. Compelling, but a harder build than option 1, and the most caretaker-sensitive of the set. I'd confirm what affordability data you can actually obtain before committing.
Strong, and more buildable than it first looks: VCOSS's Ripple Effects (March 2026) ran a quantitative spatial-injustice analysis of the 2022 floods, so the method is demonstrated and you could do a retrospective proof-of-concept against a known flood footprint. The thing to be deliberate about is distinctiveness — because that study exists, you'd want a clear line on what DEECA adds beyond it (statewide, forward-looking, independent of an advocacy framing) rather than re-running it.
4 · Urban heat, low canopy and disadvantage
My honest view: the weakest of the four for Stage 1 — not because the problem isn't real, but because DEECA has largely already done it. The Cooling & Greening Map and the Open Space for Everyone Opportunities Framework already map this overlay. It only becomes distinctive if you flip the question from "where is heat vulnerability highest" (already answered) to "is greening investment actually flowing to the highest-need areas" — an allocation question. As framed, it risks re-mapping what exists.
Others worth considering
Beyond your four — new groups or hazards, with why each earns a look.
Extreme heat & older people living alone or in care
Heat is the state's deadliest hazard and the evidence is unusually unambiguous (the 2009 heatwave drove a ~62% jump in deaths, concentrated in over-75s), the data is almost entirely public, and the gap is sharp — whether heat-health alerts, welfare check-ins and cooling-centre placement actually map to where isolated older people live. The cleanest pure heat-health framing, and it complements the housing angle rather than overlapping it.
Energy hardship & heat — people who can't afford to run cooling
The demand-side twin of option 1: that option is about the building; this is about whether the household can afford to switch the cooling on. It sits squarely in the cost-of-living debate, and VCOSS has documented people rationing energy and food through heatwaves. Worth surfacing because option 1 alone misses households that have an air-conditioner but can't afford to use it.
Prolonged power outages & people who rely on power for health
Distinctive and very live — the 2024 storms cut power to ~530,000, and the ESC is mid-review of life-support protections (~35,800 Victorians on the register). The vulnerability is concrete: medical equipment, refrigerated medication, no heating or cooling. Fair caveat: storm wind is a weaker climate-attribution story than heat or flood, so it leans on an extreme-weather / grid-stress framing.
Bushfire smoke & air quality × respiratory and cardiovascular conditions
A different hazard from the heat/flood cluster, and one that reaches people nowhere near a fire — smoke travels hundreds of kilometres, and Black Summer blanketed Melbourne for weeks. The vulnerability is health-based (asthma, COPD, heart disease), plus infants, pregnant women and outdoor workers, and adaptive capacity splits on whether you can seal and filter indoor air — which renters and low-income households can't. Policy gap: clean-air shelters, warnings that reach at-risk groups, indoor-air provision. Evidence is workable — EPA AirWatch air-quality data, chronic-disease prevalence by area (PHIDU social health atlas), hospital admissions.
Drought × farming and rural community wellbeing
The only slow-onset hazard, reaching a group none of the others do: people in drying agricultural districts, where the harm is financial stress, isolation and mental health rather than a single acute event. Victoria's north and west are projected to keep drying. Policy gap: rural mental-health and financial-counselling services are thin and poorly targeted to where drought bites. Evidence: rainfall/drought projections, SEIFA, area-level distress indicators.
People experiencing homelessness or insecure housing × extreme weather
A distinct group with near-zero adaptive capacity — and the only angle that also brings in cold (winter exposure), not just heat. Rough sleepers and people in crisis accommodation are acutely exposed to heat, cold and flash flooding, usually with poor health and no buffer. It sits squarely in the housing-crisis conversation. Soft spot: homelessness location data (AIHW, ABS estimates) is coarser than Census.
Culturally diverse and recently-arrived communities × emergency warnings
A different axis of vulnerability — not physical exposure but information and trust. People with low English proficiency, or unfamiliar with Australian bushfire/flood behaviour, are less likely to receive, understand or act on warnings, which turns an ordinary hazard into a far higher personal risk. Your reading notes flag exactly this. Evidence is unusually clean — proficiency in English, ancestry and language are Census variables down to small areas.
People with disability × inclusive evacuation and emergency response
Distinct from the power-dependence angle above: this is whether warnings, evacuation and relief are actually accessible (mobility, sensory, cognitive). Good public data via the Census "need for assistance" measure.
Extreme heat × maternal and perinatal health
Emerging evidence links heat to preterm birth and low birthweight, and the Government response names women specifically. The freshest framing of the set, but birth-outcome data by area is the hardest to obtain.
Considered, but I'd hold for later
First Nations communities (must be community-led, not a desktop exercise — better as Stage 2); outdoor workers (exposure is hard to map from where people live); and coastal inundation / managed retreat (slower-burn and very sensitive).
Where I'd steer
Of your four, 1 and 3 are the most buildable now; 4 I'd either reframe to the investment-targeting question or drop. Of the additions, older-people-and-heat is the strongest, and the bushfire-smoke and culturally-diverse-warnings angles open a hazard and a vulnerability axis your current list doesn't touch at all. A view to push against — not a ranking.
Research modeScores and recommendations are hidden so you can form your own view first. The options stay in assessed order.
Bottom line — read this first
Of seven candidate policy problems, three are the strongest Stage 1 bets: (A) extreme heat in poor-quality rentals, (C) repeated disasters deepening disadvantage, and (F) extreme heat and older people. All three rank highest because the evidence already sits in public datasets and each maps onto a live policy lever.
The scorecard's key signal: public profile and buildability pull in opposite directions. The most prominent problems in current debate — flood insurance (B) and power outages (D) — rank lower, because the data needed to prove them may not be public at a usable scale. For a proof-of-concept due by end-2026, buildable beats prominent.
Recommendation: take A, C and F into detailed analysis; hold B and D pending a data-access check.
01Purpose & scope
Stage 1 delivers a practical proof-of-concept: it takes one priority policy problem where a climate hazard intersects with vulnerable people, and tests whether hazard, exposure and vulnerability indicators can be combined to inform a real policy decision — built only from evidence we can access now, and delivered by the end of 2026.
The intersection
A climate hazard × vulnerable people (assets and infrastructure are out of scope) × a known policy gap or market failure.
The test
Can publicly available hazard and social-vulnerability data be combined into something that informs a defined policy problem?
The constraint
Deliverable by end-2026, within current resourcing, using evidence that is already accessible.
The timing
Sequence around the 28 November 2026 state election and caretaker period; frame findings carefully to avoid stigmatising places or groups.
Each option below is framed structurally — vulnerability reflects environmental, economic and policy conditions, not inherent characteristics of communities. The chosen problem is intended to inform the next round of Adaptation Action Plans (2027–31). Seven candidate options are presented in full; three lower-fit options are documented for completeness.
02Assessment criteria
These are the six criteria used to weigh the options, with the weighting that reflects Stage 1's binding constraints: we must be able to access the evidence and build it in time. They are provided so the reasoning is transparent and you can apply your own judgement. Sensitivity is tracked separately as a flag to manage, not a score to maximise.
Evidence availability · 25%
Is the hazard and vulnerability evidence publicly accessible at a usable spatial scale?
Feasibility by end-2026 · 20%
Can a credible first-pass overlay be built within time and resourcing?
Policy relevance & currency · 15%
Is it a current, active policy and public-interest issue the assessment could inform?
Vulnerability intersection · 15%
How clear and defensible is the hazard–people link?
Policy-gap / market-failure clarity · 15%
Is there a real, nameable gap or failure to act on?
Distinctiveness · 10%
Does it add value beyond work DEECA has already done?
03Options & scorecard
The candidate options, in the order assessed, with the sensitivity to manage for each. Scores and the weighted ranking are hidden — switch on Show my assessment at the top to reveal them once you've formed your own view.
Weighted scores out of 5, ranked. The signal in this table: relevance and buildability pull in opposite directions. The most prominent problems in current debate — flood insurance (B) and power outages (D) — fall to the lower half once evidence access (25%) and feasibility are weighted, while the problems we can build now (A, C, F) rise to the top. For Stage 1, public profile is necessary but not sufficient.
Candidate options in assessed order. Weighted multi-criteria scores out of 5 (shown only in full-assessment mode), with a sensitivity flag per option.
Rank#
Option
Relevance15%
Vuln. link15%
Gap15%
Evidence25%
Feasibility20%
Distinct.10%
Weighted
Sensitivity
1
AHeat in poor-quality rental housing
5
5
5
5
5
4
4.90
Low–Med
2
CRepeated disasters deepening disadvantage
5
5
4
5
5
3.5
4.70
Medium
3
FExtreme heat & older people
4
5
4
4.5
5
4
4.48
Low–Med
4
BFlood-risk households & insurance affordability
5
4
5
3.5
3.5
5
4.18
Med–High
5
EEnergy hardship & heat
5
4
4
4
4
4
4.15
Low–Med
6
DPower outages & life-support reliance
4.5
5
4.5
3
3.5
5
4.05
Low–Med
7
GUrban heat & tree canopyDuplicates existing DEECA tools
3
4
3
5
5
2
3.95
Low
8
JCoastal inundation & low-income coastParked — lower fit
3
4
4
4
3
4
3.65
High
9
IOutdoor / low-paid workers & heatParked — lower fit
The top three (A, C, F) are carried into the recommended lead set below.
04Recommended lead set
Three options to take forward now, and four to hold pending a single check each.
Take three into detailed analysis
A — Heat in poor-quality rental housing is the clearest Stage 1 candidate: the data already exists (Heat Vulnerability Index), the market failure is well-understood (a landlord–renter split incentive), and it rides a live, dated reform — Victoria's minimum rental standards.
C — Repeated disasters deepening disadvantage now has both data and method available: VCOSS's March 2026 Ripple Effects report runs the analysis against the 2022 floods, so a retrospective proof-of-concept is fast to build. DEECA's value-add is an independent, statewide and forward-looking method — the VCOSS study (by an advocacy body) would be validated, not reproduced.
F — Extreme heat & older people is the strongest pure heat-health framing, with unambiguous mortality evidence and data that is almost entirely public.
Worth pursuing, with a specific watch-point each
B (flood insurance) & D (power / life-support): highest public profile, but both hinge on a data layer that may not be public at fine scale (insurer premiums; the life-support register). Confirm data access before committing.
E (energy hardship): strong, but overlaps A — treat as the demand-side of the same heat-and-housing problem.
G (urban heat / canopy): data-ready, but largely re-covers DEECA's own Cooling & Greening work unless reframed around investment targeting.
05Option profiles
Each profile carries the four working-document columns — problem statement, intersections with vulnerability, market failure / policy gaps, and evidence needed. Key figures are cited to the sources list.
Strongest MVP candidatesCandidate options
A
Extreme heat in poor-quality rental housing
Rank 1 · 4.90 Best data fit · live policy lever
Problem statement
Victorians renting thermally inefficient homes face rising exposure to extreme heat. Tenants — disproportionately people on low incomes, older renters, social-housing residents and those with chronic health conditions or disability — have limited capacity to cool, insulate or upgrade a home they do not own. The cost of improving the building sits with landlords, while the heat, health and energy-cost burden falls on renters.
Intersections with vulnerability
Heat exposure is shaped by both the physical home (insulation, glazing, fixed cooling, orientation) and household capacity to respond (afford energy, leave during heat, reach cooler spaces). Sensitivity concentrates in older people, young children, people with disability or chronic illness and pregnant people, for whom heat stress escalates fastest. Adaptive capacity is lowest for renters and low-income households — they cannot modify the dwelling, risk energy hardship if they run cooling, and are least able to relocate. Tenure is the structural hinge: renters bear the impact but do not control the asset.
VCOSS's Hot Divide analysis finds that in Melbourne the six most disadvantaged LGAs sit within the eight hottest; Greater Dandenong runs 1.8 °C hotter than Boroondara, and the lowest-income households live in areas 0.6 °C hotter on average.6
Market failure / policy gaps
Split incentive: landlords control investment in insulation and fixed cooling; renters bear the heat, health and energy costs — producing chronic under-investment in building quality.
Regulatory transition gap: minimum rental standards phase in to 2030, so the most-exposed homes may stay unimproved until then.
Targeting gap: standards and upgrade subsidies may not reach the most heat-exposed, least-able households first.
Information gap: renters rarely see a home's thermal performance before signing.
Evidence needed
Victoria's Climate Science Report / Future Climate Tool — hot days & heatwave projections.12
Cooling & Greening Map / Heat Vulnerability Index — exposure, sensitivity, adaptive capacity to SA1, already integrating age, persons-needing-care and SEIFA.3
ABS Census & SEIFA — rental and social-housing tenure, age, need-for-assistance, household composition, income, dwelling structure.14
If accessible: Victorian Energy Upgrades / rental-standards compliance data.5Gap: HVI is urban-only — weaker for regional renters.
Live policy lever: Victoria's minimum rental standards phase in from 1 March 2027 — cooling required in the main living area at new leases, and efficient electric cooling in the main living area of all rentals by 1 July 2030 — backed by Victorian Energy Upgrades rebates.5
Stage 1 fit — Highest.
Best data readiness, a sharp and well-understood market failure, and it maps directly onto a reform government is mid-way through implementing.
Climate-driven disasters — particularly repeated flooding — are deepening existing poverty and disadvantage in affected Victorian communities. People on low incomes, in insecure housing, in poor health, or with limited savings, transport or service access face longer, harder recoveries — and less capacity to withstand the next event.
Intersections with vulnerability
Disasters deepen pre-existing disadvantage and erode future adaptive capacity — each event leaves the next one harder to survive. People experiencing poverty, insecure housing, unemployment, poor health or limited savings, transport and service access face longer recovery and greater cumulative harm. Compounding events (October 2022, then December 2023–January 2024) strike communities still mid-recovery, eroding resilience, social cohesion and trust in institutions. Renters and public-housing tenants face displacement with little control.
VCOSS's March 2026 Ripple Effects analysis found 63 of 79 LGAs affected by the 2022 floods; 59% of regional flood-affected areas had above-average poverty. The year after, disposable income was $22,818 lower for affected households than comparable households elsewhere, and 1 in 5 people in affected areas were living in poverty.8
Market failure / policy gaps
Recovery design & social protection: recovery funding, financial counselling, housing and service capacity may not be calibrated to those least able to recover.
Monitoring gap: long-term social impacts are under-measured, so support ends before vulnerable households have actually recovered.
Equity gap: uniform recovery mechanisms entrench inequality when they assume capacity (upfront costs, paperwork, digital access) that disadvantaged households lack.
Known flood footprints (Oct 2022; Dec 2023–Jan 2024) — enable a retrospective proof-of-concept overlaying disadvantage on actual disaster geography.
Emergency Recovery Victoria / IGEM reviews. Gap: granular recovery-trajectory data may be harder to access.
Stage 1 fit — High.
The most tractable retrospective proof-of-concept; the recent VCOSS report supplies data and a demonstrated method. Watch-point: VCOSS is an advocacy body and its analysis a single retrospective study — DEECA's value is an independent, statewide and forward-looking capability that validates rather than reproduces it.
F
Extreme heat and older people living alone or in care
Rank 3 · 4.48 Unambiguous evidence · public data
Problem statement
Extreme heat is Victoria's deadliest climate hazard and falls hardest on older people — particularly those living alone, in poor-quality housing, or reliant on home and community care — whose physiology, isolation and circumstances reduce their capacity to recognise heat stress and respond before it becomes a medical emergency.
Intersections with vulnerability
Older bodies thermoregulate poorly; heat illness escalates fast and is frequently fatal. Exposure is compounded by older or poor-quality housing, low canopy and urban heat-island effects. Adaptive capacity is reduced by living alone (no one to check in), limited mobility (can't reach cooling centres), cognitive decline (may not recognise the risk), energy hardship, and reliance on care services that may not scale during heat. Social isolation is the structural multiplier that turns exposure into preventable death.
Victoria's January 2009 heatwave caused 374 excess deaths — a 62% jump in all-cause mortality — with the largest increase (+64%) among people aged 75 and over; ambulance callouts rose up to 45%.13
Market failure / policy gaps
Service-targeting gap: heat-health alerts, welfare check-ins, cooling-centre placement and home-/aged-care heat preparedness may not map to where heat-exposed older people actually live.
Coordination gap: health, aged-care and emergency-management heat responses operate in silos, with no shared map of where vulnerable older people and high heat coincide.
Provision gap: cooling-centre access, and transport to it, may be missing in the highest-need areas.
Evidence needed
Heat Vulnerability Index (age and persons-needing-care already inputs) + Future Climate Tool.32
ABS Census — age (65+, 75+), lone-person households, need-for-assistance, dwelling quality.14
Department of Health / Ambulance Victoria heat-health surveillance (aggregate).13
My Aged Care provider locations (partially public).
Stage 1 fit — Strong.
Demographic and service-targeting framing with high data readiness; the heat-death evidence base is the most unambiguous of any option.
Strong, with a watch-point
B
Flood-risk households and home-insurance affordability
Rank 4 · 4.18 Highest public profile · data-access watch-point
Problem statement
Households in flood-prone parts of Victoria face rising home-insurance costs and, in the highest-risk areas, reduced availability — leaving some underinsured or uninsured. This increases financial insecurity and reduces capacity to recover from future floods, with lower-income, highly-mortgaged and tenure-insecure households least able to afford premiums, retrofit, absorb losses or relocate.
Intersections with vulnerability
Vulnerability intersects through location, income, housing security and tenure, mortgage exposure, financial stress, health and recovery capacity. Lower-income households in high-risk areas are least able to afford rising premiums, least able to retrofit, and slowest to recover — the same households face both higher exposure and lower capacity. Underinsurance turns a physical hazard into a lasting financial and housing-security shock.
Nationally, 1.61 million households (15%) are now in home-insurance affordability stress (up from 1.24m), spending on average 9.6 weeks of income on cover. For 171,000 households, riverine flood risk makes up more than half the premium — about $8,800 a year each (national).9 APRA's March 2026 Insurance Climate Vulnerability Assessment stress-tests this protection gap.10
Market failure / policy gaps
Risk-reflective pricing vs capacity to act: premiums increasingly price flood risk, but households lack information, resources or feasible alternatives to reduce it or relocate.
Information asymmetry: insurers hold risk data households don't, and availability in the highest-risk areas can narrow.
Underinsurance: the protection gap widens and government becomes de facto last resort after disasters.
Legacy planning: past decisions placed housing in flood-exposed areas; new hazard ratings risk stranding existing owners.
Evidence needed
Future Climate Tool / Victorian flood mapping + the new state flood hazard rating system.2
Actuaries Institute Home Insurance Affordability & Socioeconomic Equity — a public dataset mapping affordability to disadvantage.9
Stage 1 fit — High profile, medium feasibility.
The public affordability-equity dataset makes this buildable, but the headline figures are national and would need a Victorian cut; granular insurer premiums stay private. Manage the caretaker-period sensitivity of characterising insurance availability in named locations — attribute such claims to the public APRA and Actuaries Institute sources rather than asserting them in DEECA's voice.
E
Heat exposure where households can't afford to stay cool
Rank 5 · 4.15 Cost-of-living core · overlaps A
Problem statement
Rising extreme heat is colliding with energy-bill stress, so households experiencing energy hardship ration cooling — staying in dangerously hot homes, or cutting spending on food and medication to pay power bills. This concentrates heat-health risk among the people least able to afford to adapt, even where they have cooling available.
Intersections with vulnerability
Here adaptive capacity is financial, not physical: a home may have an air-conditioner the household can't afford to run. It concentrates in low-income households, income-support recipients, energy-hardship customers and those with high health-related energy needs. Sensitivity overlaps the heat-vulnerable groups, so affordability and physiology compound, and the coping behaviours themselves cause harm.
VCOSS documents Victorians during heatwaves "avoiding using any energy-consuming equipment at home or rationing food" — not choices but responses to rising costs — against the backdrop of 2024 being Australia's second-hottest year on record.7
Market failure / policy gaps
Targeting gap: energy concessions and hardship programs may not align spatially with heat-health risk.
Affordability externality: efficiency and electrification benefits may not reach hardship households first because the barrier is upfront cost.
Tariff structure: peak pricing during heat events penalises cooling exactly when it is most life-protecting.
VCOSS Adaptation for All / Feeling the Heat / Hot Divide.76
Stage 1 fit — Strong.
Squarely inside the cost-of-living debate. Best treated as the demand-side companion to option A (which is the supply-side / building view of the same heat-and-housing problem).
D
Prolonged power outages and people who depend on power for health
Rank 6 · 4.05 Distinctive · live ESC reform
Problem statement
More frequent and severe storms and extreme-weather events are causing prolonged power outages across Victoria, placing people who depend on electricity for medical equipment, refrigerated medication, mobility or temperature regulation at acute risk. These households — often older people, people with disability or chronic illness, and those living alone or in isolated areas — frequently have the least capacity to prepare for, withstand or recover from extended outages.
Intersections with vulnerability
Exposure clusters in storm-prone and end-of-line network areas. Sensitivity is driven by life-support equipment (oxygen, dialysis, CPAP), refrigerated medication, powered mobility, and the inability to heat or cool without power — any of which can turn an outage into a medical emergency. Adaptive capacity is low for those who can't afford backup power, live alone, or rely on others for care. Outages during heatwaves or cold snaps multiply the risk.
About 35,800 Victorians are on the electricity life-support register.11 The February 2024 storms left 530,000 customers without power, prompting a Prolonged Power Outage Payment of $1,920/week.12
Market failure / policy gaps
Resilience-investment gap: network reliability investment follows asset economics, not health need, so may not track where medical vulnerability concentrates.
Backup-power / public-good gap: backup generation is a private cost most vulnerable households can't bear; provision is ad hoc.
Register & coordination gap: life-support registers may be incomplete or not linked to prioritised restoration and welfare checks — exactly what the ESC is reviewing now.
Evidence needed
Victoria's Climate Science Report — extreme-weather context. Attribution caveat: storm-wind attribution to climate change is weaker than heat/flood; strengthen via heatwave-driven grid stress and compounding.1
ABS Census — need-for-assistance, disability, age, lone-person households, transport access.14
ACSVI — health & disability, transport, access-to-services themes.4
ESC life-support review + distributor outage data — access TBC; the main evidence gap.11
Stage 1 fit — Distinctive and very current.
A live ESC reform gives a strong policy hook, but feasibility hinges on access to the register / outage data, and the hazard-attribution framing needs care.
Include only with a caveat
G
Urban heat, low tree canopy and disadvantage
Rank 7 · 3.95 Data-ready, but duplicative
Problem statement
People in urban areas combining high heat exposure, low tree canopy and socioeconomic disadvantage face disproportionate heat-health and wellbeing risk, yet cooling and greening investment may not be reaching the communities with the highest exposure and lowest capacity to adapt.
Intersections with vulnerability
Vulnerability arises where heat exposure overlaps with age, health and disability, disadvantage, poor housing, limited private green space, low canopy, high impervious surface and limited ability to reach cooler places. Urban form intensifies local heat exactly where disadvantage concentrates.6
Market failure / policy gaps
Distribution of a public good: greening delivers public benefits but investment may not flow to highest-exposure, lowest-capacity communities.
Planning gap: greening may follow amenity or development value rather than vulnerability.
ABS / SEIFA + Census — social indicators, age, disability, density, tenure.14
New layer: greening / open-space investment data (state + council) — needed to test the targeting gap.
Stage 1 fit — Lower.
Duplicates DEECA's existing Cooling & Greening Map and Open Space Opportunities Framework unless reframed around the investment-allocation question — does greening spend go where vulnerability is highest?
Also considered — parked (lower MVP fit)Also considered
J
Coastal inundation and low-income coastal communities
Rank 8 · 3.65 Slower-burn · high sensitivity
Problem statement
Sea-level rise and coastal flooding/erosion threaten low-income and tenure-insecure households in exposed Victorian coastal settlements, who are least able to retrofit, insure (against "actions of the sea" exclusions) or relocate.
Why parked
A real market failure ("actions of the sea" insurance exclusions) and good hazard data, but slower-burn in current debate, and the policy and funding pathways for adaptation or relocation in receding-coast settlements are still developing — a highly sensitive area (property values, relocation) better suited to later, engagement-led work.
I
Outdoor and low-paid workers exposed to extreme heat
Rank 9 · 3.05 Exposure-location mismatch
Problem statement
Outdoor and physically-exposed workers (construction, agriculture, warehousing, delivery) face rising occupational heat exposure, with insecure and low-paid workers least able to stop work, lose income or secure protective conditions.
Why parked
Exposure is tied to the workplace, not residence, so spatial people-vulnerability mapping from Census residence data is much harder. A real issue (occupational heat standards, productivity), but a weaker fit for a place-based MVP.
H
First Nations communities and climate vulnerability
Rank 10 · 2.90 Engagement-led · Stage 2
Problem statement
Aboriginal and Torres Strait Islander communities in Victoria experience unique and disproportionate climate impacts — to health, Country, culture and self-determination — yet mainstream vulnerability data and methods, developed without community governance, are not the appropriate vehicle for assessing them.
Why parked
Cannot be a desktop exercise: it requires community-led engagement and Indigenous Data Sovereignty, and standard socioeconomic indicators don't capture connection to Country. Named explicitly in the Government response, so likely a Stage 2 priority; ADAPT Loddon Mallee is the closest model. This must be progressed through self-determination, not desktop mapping.
06Evidence & sources
All figures are drawn from publicly available sources, listed below. Where statistics are national, this is noted in the relevant profile and a Victorian cut would be derived for the assessment.
Ripple Effects: Spatial injustice and the 2022 Victorian floods (March 2026) — VCOSS. vcoss.org.au
Home Insurance Affordability — Home Loans at Risk (2024); Funding for Flood Costs; & Socioeconomic Equity dataset — Actuaries Institute. home loans at risk · equity report & data
January 2009 Heatwave in Victoria — assessment of health impacts (excess deaths) — Victorian Dept of Health / Chief Health Officer. health.vic.gov.au
Census & SEIFA — Australian Bureau of Statistics. abs.gov.au
07Method & caveats
This document opens in Research mode: the options, their evidence and the criteria are shown, but the scoring and recommendation are hidden so a reader can form an independent view first. Use Show my assessment at the top to reveal the weighted scorecard and recommended lead set.
Scores (when shown) reflect indicative expert judgement against the six weighted criteria, intended to seed a formal multi-criteria analysis — not to pre-empt it. Re-weighting is expected.
The weighting deliberately privileges evidence availability (25%) and feasibility (20%), because Stage 1's defining constraint is building something credible, now, from accessible data.
Alignment to the next Adaptation Action Plans (2027–31): A and E sit with the Built Environment and Health & Human Services systems; C with Emergency Management; F with Health & Human Services — so a chosen problem feeds the next AAP cycle.
Several headline insurance figures (option B) are national; a Victorian subset would be derived. Options B and D carry a genuine data-access risk on their policy-specific layer (insurer premiums; the life-support register) that should be confirmed before selection.
All language is structural by design: vulnerability reflects environmental, economic and policy conditions, not inherent characteristics of people or places.
Next step: confirm the lead set, then deepen the evidence scan and indicator identification for the chosen problem(s) ahead of MVP development.
08Further work available on request
Optional analysis and tools that could be produced to support Stage 1, mapped to the project's roadmap. Flagged here so you can indicate what would be useful — nothing is started yet.
Build
MVP spatial overlay prototype
An interactive Victorian map (SA1/SA2) overlaying a climate hazard with vulnerability indicators — e.g. heat exposure with the Heat Vulnerability Index, SEIFA and Census — to show where hazard and vulnerability concentrate. Built entirely from public data.
Serves: proof-of-concept / MVP
Interactive scoring workbook
An Excel workbook where you set your own criteria weights and scores and watch the option ranking recalculate live — so the assessment is yours to drive, not pre-judged.
Serves: policy-problem analysis
Executive brief & short deck
A one-page summary and a short slide deck to socialise the chosen direction with executive and stakeholders.
Serves: project direction / sign-off
Framing & language guide
A concise reference consolidating the IPCC / VCOSS non-stigmatising language norms, to keep wording consistent and structural across the project.
Serves: sensitivity / consistency
Research
Data-access feasibility check (B & D)
Confirm whether the gated data layers — granular insurance affordability; the ESC life-support register — are actually obtainable, before either option is selected.
Serves: de-risking selection
Evidence & indicator scan (lead set)
For the chosen problem: candidate vulnerability indicators mapped to exposure / sensitivity / adaptive capacity, each with source, spatial scale, access method and limitations.
Serves: evidence scan + indicator identification
Cross-jurisdiction method scan
How NSW, Queensland, the UK, New Zealand and the US (CDC Social Vulnerability Index) have tied vulnerability mapping to a specific policy problem — to sharpen the MVP method and pre-empt "why this approach?"
Serves: method design
Policy-lever & agency map
Which agencies own each relevant lever (DFFH, DH, DEECA, ESC, local government) for the shortlisted problems — input to the engagement plan.
Serves: engagement planning
Keep current
Standing watch on 2026 developments
Ongoing monitoring of developments that affect the evidence base — the ESC life-support final decision (mid-2026), the next Dropping off the Edge (2027), APRA / insurance follow-ups, and Adaptation Action Plan 2027–31 milestones.
A plain read on the options — no scoring, no ranking. My commentary on the four you flagged, then others worth considering, and a few I'd hold for later.
Your four options — my read
1 · Heat in poor-quality / thermally inefficient homes (renters, low-income)
The strongest of your four for a first pass. The vulnerability logic is clean — exposure comes from the building fabric, low capacity from not owning (or not affording to run) the home — so you're not leaning on a contested causal story. It also sits on a live lever: the minimum rental standards (efficient electric cooling in the main living area of all rentals by 2030). And the evidence is largely off-the-shelf — the Cooling & Greening Heat Vulnerability Index already combines heat exposure, sensitivity and adaptive capacity down to SA1. Watch-outs: the HVI is urban-only, so regional renters thin out, and "poor-quality housing" needs structural framing to avoid labelling places.
2 · Flood insurance affordability / availability
The most live in public debate (APRA's March 2026 insurance climate vulnerability assessment; the new Victorian flood hazard ratings) and a textbook market-failure story. The honest catch is data: hazard and social layers are public, but the granular insurance-affordability layer largely sits with insurers — the Actuaries Institute's affordability-and-equity work is the realistic public proxy, and its headline figures are national, so you'd derive a Victorian cut. Compelling, but a harder build than option 1, and the most caretaker-sensitive of the set. I'd confirm what affordability data you can actually obtain before committing.
3 · Climate disasters deepening existing disadvantage
Strong, and more buildable than it first looks: VCOSS's Ripple Effects (March 2026) ran a quantitative spatial-injustice analysis of the 2022 floods, so the method is demonstrated and you could do a retrospective proof-of-concept against a known flood footprint. The thing to be deliberate about is distinctiveness — because that study exists, you'd want a clear line on what DEECA adds beyond it (statewide, forward-looking, independent of an advocacy framing) rather than re-running it.
4 · Urban heat, low canopy and disadvantage
My honest view: the weakest of the four for Stage 1 — not because the problem isn't real, but because DEECA has largely already done it. The Cooling & Greening Map and the Open Space for Everyone Opportunities Framework already map this overlay. It only becomes distinctive if you flip the question from "where is heat vulnerability highest" (already answered) to "is greening investment actually flowing to the highest-need areas" — an allocation question. As framed, it risks re-mapping what exists.
Others worth considering
Beyond your four — new groups or hazards, with why each earns a look.
Extreme heat & older people living alone or in care
Heat is the state's deadliest hazard and the evidence is unusually unambiguous (the 2009 heatwave drove a ~62% jump in deaths, concentrated in over-75s), the data is almost entirely public, and the gap is sharp — whether heat-health alerts, welfare check-ins and cooling-centre placement actually map to where isolated older people live. The cleanest pure heat-health framing, and it complements the housing angle rather than overlapping it.
Energy hardship & heat — people who can't afford to run cooling
The demand-side twin of option 1: that option is about the building; this is about whether the household can afford to switch the cooling on. It sits squarely in the cost-of-living debate, and VCOSS has documented people rationing energy and food through heatwaves. Worth surfacing because option 1 alone misses households that have an air-conditioner but can't afford to use it.
Prolonged power outages & people who rely on power for health
Distinctive and very live — the 2024 storms cut power to ~530,000, and the ESC is mid-review of life-support protections (~35,800 Victorians on the register). The vulnerability is concrete: medical equipment, refrigerated medication, no heating or cooling. Fair caveat: storm wind is a weaker climate-attribution story than heat or flood, so it leans on an extreme-weather / grid-stress framing.
Bushfire smoke & air quality × respiratory and cardiovascular conditions
A different hazard from the heat/flood cluster, and one that reaches people nowhere near a fire — smoke travels hundreds of kilometres, and Black Summer blanketed Melbourne for weeks. The vulnerability is health-based (asthma, COPD, heart disease), plus infants, pregnant women and outdoor workers, and adaptive capacity splits on whether you can seal and filter indoor air — which renters and low-income households can't. Policy gap: clean-air shelters, warnings that reach at-risk groups, indoor-air provision. Evidence is workable — EPA AirWatch air-quality data, chronic-disease prevalence by area (PHIDU social health atlas), hospital admissions.
Drought × farming and rural community wellbeing
The only slow-onset hazard, reaching a group none of the others do: people in drying agricultural districts, where the harm is financial stress, isolation and mental health rather than a single acute event. Victoria's north and west are projected to keep drying. Policy gap: rural mental-health and financial-counselling services are thin and poorly targeted to where drought bites. Evidence: rainfall/drought projections, SEIFA, area-level distress indicators.
People experiencing homelessness or insecure housing × extreme weather
A distinct group with near-zero adaptive capacity — and the only angle that also brings in cold (winter exposure), not just heat. Rough sleepers and people in crisis accommodation are acutely exposed to heat, cold and flash flooding, usually with poor health and no buffer. It sits squarely in the housing-crisis conversation. Soft spot: homelessness location data (AIHW, ABS estimates) is coarser than Census.
Culturally diverse and recently-arrived communities × emergency warnings
A different axis of vulnerability — not physical exposure but information and trust. People with low English proficiency, or unfamiliar with Australian bushfire/flood behaviour, are less likely to receive, understand or act on warnings, which turns an ordinary hazard into a far higher personal risk. Your reading notes flag exactly this. Evidence is unusually clean — proficiency in English, ancestry and language are Census variables down to small areas.
People with disability × inclusive evacuation and emergency response
Distinct from the power-dependence angle above: this is whether warnings, evacuation and relief are actually accessible (mobility, sensory, cognitive). Good public data via the Census "need for assistance" measure.
Extreme heat × maternal and perinatal health
Emerging evidence links heat to preterm birth and low birthweight, and the Government response names women specifically. The freshest framing of the set, but birth-outcome data by area is the hardest to obtain.
Considered, but I'd hold for later
First Nations communities (must be community-led, not a desktop exercise — better as Stage 2); outdoor workers (exposure is hard to map from where people live); and coastal inundation / managed retreat (slower-burn and very sensitive).
Where I'd steer
Of your four, 1 and 3 are the most buildable now; 4 I'd either reframe to the investment-targeting question or drop. Of the additions, older-people-and-heat is the strongest, and the bushfire-smoke and culturally-diverse-warnings angles open a hazard and a vulnerability axis your current list doesn't touch at all. A view to push against — not a ranking.