ZIP 17901 Property Distress & Foreclosure Data

DLRadar grades ZIP 17901 (Schuylkill County, Pennsylvania) at a low 20/100 for overall property distress. Structural exposure scores 44 and live distress 2 on the 0–100 scale. Property-level stress concentrates in structural risk (44/100), construction/permit lag (28/100), institutional ownership (14/100). On the quiet end sit institutional ownership (14/100) and mortgage stress (8/100). Environmental exposure also runs high (climate & FEMA risk (84/100)).

The expansion-phase market in 17901 posted values that rose 5.5% over the year, and 20% higher over three years, at 32/100 phase confidence. Rising prices can mask pockets of distress, where per-parcel scoring earns its keep.

There are about 11,278 housing units across 17901. 71% of housing is owner-occupied. The typical home is worth about $152,100 (2.1× income, relatively affordable). Vacancy runs 12.3%, above the national norm and a classic distress-and-opportunity signal. The demographic-stress sub-score lands at 27/100. At $61,632, median income runs below typical U.S. levels. Around 23% of adults hold a bachelor's degree or higher. Rent burden reaches 37% of tenant households. Population is roughly 22,557 with a median age of 45. The poverty rate is 14.3%.

On the whole, 17901 leans distressed, with opportunity clustered in specific stressed parcels. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

20/100
Composite stress
44/100
Structural risk
2/100
Distress activity

Distress signal breakdown — ZIP 17901

Foreclosure activity0
Mortgage stress8
Climate / FEMA risk84
+9 more distress dimensions scored for this ZIP

Tax delinquency, institutional ownership, insurance pressure, NFIP/flood, construction lag, price dislocation and auction velocity — plus the 0 individual distressed properties (owner, address, APN, per-property score and exit read) are in the full DLRadar report.

Nearby ZIPs in Schuylkill County

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Deterministic. Every signal traces to a public dataset · methodology