The Charter 25 counties offer an early look at this national challenge. These are not identical counties. They represent different versions of transportation risk, including retirement-destination aging, rural distance, limited workforce, geographic isolation, modest local tax capacity, cross-county medical dependence, disaster vulnerability, and aging-in-place without realistic mobility options.
Pattern of Transportation Stressors from the Charter 25
Retirement counties can age into a second-stage crisis.
Stable aging-in-place counties may be more fragile than they look.
Frontier and rural counties face a distance penalty that standard planning often undercounts.
Some counties are running out of the people needed to operate the system.
Geography can become a direct aging-risk factor.
Administrative boundaries can strand people even when help exists nearby.
The central finding is clear: counties rarely face only one transportation risk. Most face layered risks. A county may be rural and aging, wealthy and unequal, scenic and isolated, stable and fragile, or well-served in some areas while deeply underserved in others.
For planners outside the Charter 25, the value of this report is not in asking, “Are we exactly like one of these counties?” The value is in asking: Which Charter 25 patterns are beginning to appear here?
A county may not have 40% of its population over age 65 today. But it may already have growing 75+ and 85+ populations, older adults living alone, long medical trips, no fixed-route transit, limited volunteer capacity, out-of-county care dependence, or neighborhoods where aging residents will eventually be unable to drive.
That is why transportation must be treated as core aging infrastructure.
If counties wait until the transportation crisis is visible, they will already be late. Warning signs are available now. The Charter 25 show where to look.
Patterns Revealed by the Charter 25 Counties
Category 1: Retirement Magnets and the Secondary-Move Crisis
These counties attract older adults while they are still mobile, independent, and driving. The transportation crisis appears later. A county can look successful for years, then begin to strain when large numbers of residents reach the point where they no longer drive, cannot manage long medical trips, or need door-through-door support.
Sumter County, Florida — 57.7%
Sumter is the extreme case. It is not simply “old.” It is structurally different from most American counties because aging is the dominant community condition, not a service subgroup.
Its transportation lesson is that senior density can create enough political and market pressure to build parallel systems: golf-cart networks, private shuttles, age-oriented development patterns, club-based support, and commercial services shaped around older residents. That does not mean Sumter is safe. It means Sumter has partially adapted because it had no choice.
The danger for other counties is misreading Sumter as proof that high aging density works on its own. It does not. Sumter works only where development, private systems, health access, local dollars, and senior-focused design are aligned. Counties with rising senior populations but ordinary suburban road systems should not assume they can age into Sumter’s model.
What planners should check locally:
Percent 65+, percent 75+, percent 85+, percent of older adults living in age-restricted or master-planned communities, transit availability inside senior-heavy developments, medical-trip destinations, and whether private mobility systems are available only to residents of certain developments.
Charlotte County, Florida — 40.5%
Charlotte should not be reduced to disaster risk. Disaster matters, but Charlotte’s deeper issue is the aging of a retirement destination after the first wave of retirees has moved from active independence into higher service need.
Many residents arrived as drivers. They bought homes in traditional subdivisions, coastal neighborhoods, canal communities, manufactured-home areas, or lower-density residential zones. Twenty years later, the same places can become transportation traps. A person may own a home, know the community, and appear stable on paper while losing the ability to reach oncology, cardiology, dialysis, grocery stores, pharmacies, or social supports.
Charlotte also has a layered transportation problem because older adults are not concentrated in one neatly served zone. The county includes coastal vulnerability, suburban sprawl, inland communities, storm recovery issues, and a growing 85+ population. The stress point is not one crisis. It is the combined effect of age, distance, medical need, and fragile infrastructure.
What planners should check locally:
ACS age bands, especially 75+ and 85+; vehicle availability among older households; disability status; distance from older neighborhoods to hospitals and specialists; hurricane evacuation zones; manufactured-home concentration; transit service areas; and post-disaster continuity plans for medical rides.
Sarasota County, Florida — 38.5%
Sarasota shows what happens when a high-aging county has more wealth, stronger nonprofit capacity, and greater local resources than many rural counties. It may have more options, but the options can hide need.
The transportation stress point is segmentation. Some older adults can buy rides, use private services, live near medical corridors, or access senior-focused nonprofit supports. Others live on fixed incomes, outside convenient service areas, or in housing that was affordable years ago but is now surrounded by rising costs. In a county like Sarasota, averages can deceive planners. Median income, philanthropy, and amenities can make the county appear better prepared than many seniors actually are.
Sarasota’s national lesson is that transportation vulnerability can exist inside wealth. A county can have generous donors, cultural institutions, hospitals, and transit options while still leaving low-income, isolated, medically fragile, or non-driving older adults with limited practical access.
What planners should check locally:
Income by age group, older renters, older homeowners with high housing costs, paratransit eligibility and trip denials, low-income senior neighborhoods, distance to specialty medical care, nonprofit transportation capacity, and whether services reach beyond the most visible senior communities.
Citrus County, Florida — 36.5%
Citrus is a warning for middle-income aging counties. It has significant senior density without the same level of concentrated wealth or private infrastructure seen in stronger retirement markets.
Its transportation problem is the ordinary landscape: spread-out homes, limited density, lower incomes, older residents aging in place, and expensive demand-response transportation. This is the kind of county where planners may say, “We have transportation,” while residents experience it as too limited, too scheduled, too difficult to qualify for, or unavailable when they need it.
Citrus matters because many counties across the nation will look more like Citrus than Sumter or Sarasota. They will have rising senior density, modest local tax capacity, and a road network built around private vehicles. The lesson is that transportation failure does not begin when all service disappears. It begins when the available system cannot handle ordinary medical, food, pharmacy, and social-access needs.
What planners should check locally:
Median income for older adults, poverty 65+, disability 65+, no-vehicle households, demand-response service area, ride purpose restrictions, advance scheduling requirements, senior population growth, and local match capacity.
Category 2: Stability and Accumulation Counties
These counties did not necessarily become old through sudden retirement migration. Many became old because people stayed, younger residents left, or the community aged slowly over time. The transportation system often remained built for a younger, driving population long after the population changed.
Highlands County, Florida — 36.0%
Highlands represents the working-class aging county. It has a large older population, modest incomes, no fixed-route options, relies heavily on paratransit, and a spread-out development pattern.
The stress point is not only transportation supply. It is the mismatch between needs and geography. Seniors may live in older neighborhoods, mobile homes, rural pockets, lake communities, or areas outside easy service corridors. Many can remain technically “independent” only because they still drive, rely on someone else, or skip trips.
Highlands is important nationally because it shows how aging density becomes harder when local wealth is limited. The county’s transportation future cannot be solved only by adding a few vans. It requires looking at where older adults live, where essential services sit, how long trips take, and how many people have no realistic backup when driving ends.
What planners should check locally:
No-vehicle households, disability, poverty, senior housing locations, meal-site access, distance to grocery and medical care, transportation waitlists, unmet ride requests, and number of working-age adults available for paid or volunteer roles.
Jefferson County, Washington — 40.7%
Jefferson shows the challenge of an older county with rugged geography, coastal settlement patterns, and a strong identity of aging in place.
Its transportation stress is partly distance and partly terrain. Residents may live in small communities, rural roads, waterfront areas, or places where a simple trip becomes time-consuming because of road patterns and weather. Even when a regional transit system exists, the question is whether it can provide the kind of service older adults actually need: medical timing, door-to-door access, reliability, and practical connections to care.
Jefferson’s lesson is that having transit does not erase aging stress. A county can be more organized than many rural areas and still face a service ceiling because of geography, cost of labor, housing costs for workers, and the growing number of older residents needing more support.
What planners should check locally:
Transit route coverage, paratransit area, medical destination patterns, elevation and road constraints, ferry or bridge dependence where relevant, driver recruitment, senior disability, older adults living alone, and cost per rural trip.
San Juan County, Washington — 36.0%
San Juan is not just rural. It is island-based. That changes everything.
Transportation planning in San Juan must account for ferries, inter-island movement, mainland medical care, weather interruptions, scheduling complexity, and the physical difficulty of moving frail older adults through a multi-stage trip. A ride is not simply a ride. It may involve a vehicle, a ferry, another vehicle, waiting time, appointment timing, and return coordination.
San Juan’s national value is that it exposes reliability as a core aging issue. A county can have some transportation resources and still fail older residents if one link in the chain breaks. Ferry delays, medical appointment timing, wheelchair access, caregiver availability, and weather can turn a planned trip into an impossible trip.
What planners should check locally:
Ferry dependence, medical trips off-island, older adults living alone, emergency transport plans, paratransit coordination, volunteer-driver capacity, missed medical appointments due to transportation, and seasonal service disruption.
Towns County, Georgia — 36.9%
Towns County reflects the quiet danger of a beautiful retirement and aging-in-place community with a shrinking younger population.
Its transportation stress is not only distance. It is the absence of backup. When the under-65 population shrinks, the informal ride system weakens. Family members are farther away. Volunteers age. Paid drivers become harder to recruit. Churches, neighbors, and civic groups may still help, but they cannot replace a transportation system.
Towns is a national warning for mountain and lake counties that attract or retain older residents while losing younger workers. The county may look peaceful and stable, but the service structure underneath can become fragile.
What planners should check locally:
Old-age dependency ratio, percent under 18, percent 18–64, volunteer-driver availability, distance to hospitals and specialists, road conditions, seasonal population shifts, and senior poverty.
Category 3: Frontier Distance and Medical-Desert Pressure
These counties are defined by distance, low population density, sparse services, and long trips for basic care. Traditional per-person transportation funding often fails here because the cost is driven by miles, time, terrain, and driver availability.
Catron County, New Mexico — 47.6%
Catron is one of the clearest examples of the rural distance penalty. With nearly half the population age 65+ and a very large land area, transportation cannot be understood through headcount alone.
A single medical trip may consume hours. A driver may spend most of a day serving one person. Weather, road conditions, fuel costs, and vehicle wear become central service issues. The county’s senior transportation problem is not simply “lack of transit.” It is that ordinary transit formulas are not built for places where distance is the main cost.
Catron’s lesson is essential for national planners: when aging density and frontier geography combine, service need should be weighted by miles, not just population.
What planners should check locally:
Population density, land area, average medical trip distance, HRSA shortage designations, distance to pharmacy, distance to hospital, percent 65+, percent 75+, no-vehicle households, road conditions, and fuel/driver cost per completed trip.
Prairie County, Montana — 42.2%
Prairie County shows the small-population version of the same problem. The county may not have many people, but a large share of those people are older.
Small numbers can fool planners. A state or federal formula may see a tiny county and allocate limited resources. But for the people living there, the need is not tiny. A few frail older adults can require long, expensive, high-stakes trips. When the population base is small, losing one driver, one volunteer, or one vehicle can collapse the system.
Prairie matters because it shows why “low volume” does not mean “low need.” It means each need is harder and more expensive to meet.
What planners should check locally:
Total 65+ population, percent 65+, land area, population density, number of available drivers, vehicle inventory, distance to nearest hospital, distance to pharmacy, and emergency medical transport capacity.
La Paz County, Arizona — 43.1%
La Paz represents the high-desert medical-distance problem. Older adults may be separated from specialty care by long drives, heat, limited local medical infrastructure, and sparse public transportation.
Its stress point is layered. The county has aging density, rural distance, high summer heat, and likely out-of-county medical dependence. For older adults, especially those with cardiac disease, kidney disease, cancer, vision loss, or mobility limitations, transportation is not optional. It is the condition for treatment.
La Paz’s national lesson is that desert counties need to treat medical transportation, heat safety, and emergency planning as one connected system.
What planners should check locally:
Out-of-county medical trips, distance to Yuma/Phoenix/other specialty hubs, heat-risk days, older adults living alone, poverty, disability, no-vehicle households, dialysis access, VA access, and emergency cooling-center transportation.
Sierra County, New Mexico — 38.8%
Sierra County shares the high-desert challenge but should not be treated as interchangeable with La Paz. Its value is in showing how a smaller service base changes the transportation problem.
A county like Sierra may have older residents spread across small communities, with limited local providers and long trips for higher-level care. Transportation stress can appear in the gap between basic local access and specialty access. Residents may manage routine needs nearby but face serious barriers when care becomes complex.
Sierra’s lesson is that rural aging counties need to map levels of care separately. A clinic in the county does not mean access to oncology, cardiology, dialysis, surgery, or rehabilitation.
What planners should check locally:
Primary care locations, specialty-care destinations, medically underserved designations, senior disability, older adults living alone, no-vehicle households, trip distance by care type, and availability of non-emergency medical transportation.
Wheeler County, Oregon — 38.5%
Wheeler represents the ultra-rural service-thin county. Its challenge is not only distance but extremely low density.
Transportation systems depend on enough riders, enough workers, and enough local infrastructure to function. Wheeler shows what happens when all three are limited. Even if need is high by percentage, the county may struggle to justify or sustain traditional service models because riders are scattered and trips are long.
Wheeler’s national lesson is that rural transportation cannot rely only on bus or van models. Counties like this need hybrid systems: medical-trip coordination, supply delivery, volunteer support, telehealth, mobile clinics, and regional service agreements.
What planners should check locally:
Population density, senior density, medical-trip distance, provider locations, road mileage, volunteer capacity, broadband access, pharmacy access, and regional transportation agreements.
Custer County, Idaho — 36.6%
Custer’s transportation issue is distance intensified by mountains, winter, and road conditions.
A 25-mile trip in a mountain county is not the same as a 25-mile trip in a flat suburban county. Snow, elevation, road closures, limited cell service, and seasonal access all matter. For older adults, this affects medical care, food access, caregiver response, emergency evacuation, and the ability to remain at home.
Custer’s national lesson is that transportation formulas need a terrain adjustment. Mileage alone undercounts the burden when the miles are mountainous, seasonal, or dangerous.
What planners should check locally:
Elevation, winter road closures, average medical-trip distance, emergency response time, older adults living alone, disability, no-vehicle households, broadband, and seasonal access to food/pharmacy/medical care.
Ouray County, Colorado — 35.8%
Ouray is a high-terrain county with tourism wealth, scenic identity, and aging density. That combination creates a different stress pattern.
Tourism can bring money, roads, services, and attention. It can also raise housing costs, strain the workforce, and orient transportation around visitors rather than frail older residents. A county may have shuttle activity, seasonal transportation, or visitor infrastructure while still lacking dependable aging-focused access.
Ouray’s lesson is that tourism infrastructure is not the same as senior infrastructure. A county can move visitors and still fail residents who need medical, grocery, pharmacy, and caregiver-connected transportation.
What planners should check locally:
Seasonal transit patterns, year-round service availability, senior income, older renters, workforce housing, medical-trip distance, road closures, emergency access, and whether transportation funding is visitor-oriented or resident-oriented.
Category 4: Labor Vacuum Counties
These counties show the human-capital side of transportation. The problem is not only vehicles or money. It is the shrinking pool of people available to drive, dispatch, maintain vehicles, volunteer, coordinate trips, or help older adults safely complete the trip.
Ontonagon County, Michigan — 38.2%
Ontonagon reflects the older industrial/rural county where younger workers have left and the remaining population is heavily aged.
Its transportation stress is workforce collapse. Even if funding exists, the county may not have enough drivers, substitute drivers, dispatchers, mechanics, or volunteers. Informal support also weakens when adult children move away and neighbors are older themselves.
Ontonagon’s national lesson is that aging counties must measure labor capacity as seriously as they measure vehicles. A van without a driver is not a transportation system.
What planners should check locally:
Old-age dependency ratio, working-age population, labor-force participation, driver vacancy rates, volunteer age, distance to medical care, winter road conditions, and number of licensed transportation providers.
Alcona County, Michigan — 37.0%
Alcona should stand on its own as a rural aging-in-place county with lake/coastal settlement patterns, limited density, and workforce pressure.
Its transportation problem is likely less about one dramatic barrier and more about accumulated small barriers: distance, winter, limited local medical options, older residents living alone, and a thin workforce. These counties often survive on informal arrangements until the need becomes too large for informal help to carry.
Alcona’s lesson is that low-density aging counties can reach a point where neighbor-help systems become overused, invisible, and unreliable.
What planners should check locally:
Older adults living alone, no-vehicle households, disability, working-age population, volunteer-driver programs, seasonal road conditions, distance to hospitals, and demand-response service limits.
Keweenaw County, Michigan — 36.5%
Keweenaw is a special case because of geography, winter, and small population size.
The issue is not only that many residents are older. It is that the county’s physical location and winter conditions can turn transportation into a safety and continuity problem. Small population counties also have very little redundancy. One unavailable driver, one vehicle repair, or one weather event can disrupt access.
Keweenaw’s national lesson is that small aging counties need backup systems before they need them. Redundancy is not waste. In places like this, redundancy is survival.
What planners should check locally:
Winter access, road closures, emergency transport time, number of vehicles, driver backup capacity, older adults living alone, medical-trip distance, and mutual-aid agreements with nearby counties.
Quitman County, Georgia — 37.2%
Quitman represents the Deep South labor-vacuum problem in a small, high-poverty, high-aging county.
Its transportation stress includes poverty, limited workforce, rural distance, and likely out-of-county medical dependence. The county may not only struggle to fund transportation; it may struggle to staff it. In very small counties, formal systems can be thin, and informal systems can be overburdened.
Quitman’s national lesson is that counties with high aging density and high poverty need transportation treated as basic infrastructure, not an optional supportive service.
What planners should check locally:
Poverty 65+, disability 65+, working-age population, no-vehicle households, medical underservice, distance to hospital and pharmacy, driver availability, and whether residents cross county or state lines for care.
Category 5: Geography of Isolation
These counties show that physical barriers shape aging access. Water, mountains, peninsulas, coastlines, forests, and single-road corridors can all make transportation harder than mileage alone suggests.
Lancaster County, Virginia — 39.9%
Lancaster’s transportation issue is shaped by peninsula geography and the Northern Neck settlement pattern.
A county may look close to services on a regional map but function much farther away on the road. Water, bridges, limited routes, and rural roads can turn medical access into long, indirect travel. Older adults may live in waterfront or rural homes that were manageable while they drove but isolating after driving stops.
Lancaster’s lesson is that planners must calculate real travel time, not straight-line distance.
What planners should check locally:
Driving distance to hospitals and specialists, bridge dependence, road-network circuity, older adults living alone, no-vehicle households, disability, emergency response time, and transit service area.
Northumberland County, Virginia — 38.0%
Northumberland shares the Northern Neck geography but needs its own analysis. Its stress point is the combination of rural aging, waterfront/peninsula development, and limited direct access to regional medical systems.
For older residents, living near water can mean living far from care. A short visual distance across water may require a long road trip. As residents age, this affects routine care, emergency response, caregiver access, and storm evacuation.
Northumberland’s national lesson is that scenic rural retirement areas can carry hidden access penalties.
What planners should check locally:
Out-of-county medical trips, road miles to care, emergency evacuation routes, flood/coastal risk, no-vehicle households, disability, and older adults living alone.
Curry County, Oregon — 36.7%
Curry is a coastal corridor county. Its transportation vulnerability is tied to the limited road network between mountains and the Pacific.
When service depends heavily on one corridor, there is little redundancy. Fog, landslides, storms, road work, or vehicle limitations can interrupt access. Older adults may be distributed along a long coastal strip, making service expensive and fragile.
Curry’s national lesson is that coastal aging counties need continuity planning. Transportation cannot depend on one road, one provider, or one weather-sensitive corridor.
What planners should check locally:
Highway dependence, road closure history, medical-trip distance, older adults living alone, disability, no-vehicle households, emergency evacuation routes, and backup transportation agreements.
Category 6: Jurisdictional, Fiscal, and Administrative Walls
These counties show that transportation barriers are not always physical. Sometimes the barrier is a county line, funding rule, tax base limitation, eligibility rule, or lack of interlocal agreement.
McCormick County, South Carolina — 39.5%
McCormick’s transportation stress is fiscal and structural. It is a small county with high aging density and limited local capacity.
A key issue to examine is whether land ownership, tax base limits, lake/federal/recreation land patterns, or small population size restrict the county’s ability to raise local match. Even when the need is clear, the county may not have the fiscal base to unlock or sustain service.
McCormick’s national lesson is that high-aging counties with small tax bases need funding formulas that recognize capacity, not just population.
What planners should check locally:
Taxable property base, federal/state/non-taxable land share, poverty 65+, no-vehicle households, disability, transit funding sources, local match requirements, and out-of-county medical destinations.
Real County, Texas — 37.9%
Real County represents the rural border-and-distance problem in a rugged, low-density setting.
The transportation stress is likely a combination of distance, terrain, county-line dependence, and limited formal systems. Older adults may need services outside the county, but transportation funding and operations may be organized locally. In a place like Real, crossing a boundary may be essential, not exceptional.
Real’s national lesson is that rural counties need regional mobility agreements before individual crises occur.
What planners should check locally:
Out-of-county medical care, interlocal transit agreements, road conditions, terrain, distance to hospital and pharmacy, no-vehicle households, disability, and old-age dependency ratio.
Llano County, Texas — 37.0%
Llano has a different version of the same broad problem. It is rural, aging, and connected to regional medical and service economies beyond its borders.
Its transportation issue may involve older adults living in dispersed communities, lake-area development, rural roads, and medical trips that do not respect county lines. A county-based transportation system can become too small for the actual life pattern of residents.
Llano’s national lesson is that county boundaries are often poor maps of senior need. Older adults live regionally even when services are funded locally.
What planners should check locally:
Medical destination leakage, county-line trip restrictions, senior population by census tract, no-vehicle households, disability, demand-response rules, and regional service agreements.