Yearly Traffic Safety Analysis

978 CRASHES IN
OHIO, OH
2021

In 2021, Jefferson County recorded 978 total traffic crashes, resulting in 5 fatalities and 337 injuries. A majority of these incidents, 51.4%, were single-vehicle crashes not involving a collision with another vehicle in transport. The peak time for crashes was on Mondays during the 4 p.m. hour.

978

Total Crash Events

5

Persons Killed

337

Persons Injured

10.3%

Hit-and-Run Rate

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

101

Hit-and-Run Crashes — 2021

Based on initial officer determinations, 101 crashes in Jefferson County were classified as hit-and-run incidents. This represents 10.3% of all crashes recorded during the period.

Vulnerable Road User Casualties

In 2021, all 5 fatalities and 332 of the 337 total injuries involved motorists. There were no pedestrians or cyclists killed in crashes. However, 5 pedestrians sustained injuries in collisions during this period.

0

Pedestrians Killed

5

Motorists Killed

5

Pedestrians Injured

332

Motorists Injured

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes occurred most frequently on Mondays, with 169 incidents reported, while the single busiest hour for crashes was the 4 p.m. hour with 72 events. Overall, a majority of collisions, 575 crashes or 58.8%, happened during daylight hours.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 978 total crashes, 74.4% (728 incidents) resulted in no injuries, with the remainder involving a possible, minor, or serious injury. There were 4 fatal crashes recorded for the year. These 4 incidents resulted in a total of 5 fatalities.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.4%
Serious Injury29serious injury crashes3%
Minor Injury132minor injury crashes13.5%
Possible Injury85possible injury crashes8.7%
No Injury728no injury crashes74.4%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes occurred in favorable conditions, with 61.9% happening in clear weather and 75% on dry road surfaces. Daylight conditions were present for 58.8% of all incidents. Crashes in adverse weather included 100 in rain and 37 in snow.

Weather

Clear605 (61.9%)
Cloudy219 (22.4%)
Rain100 (10.2%)
Snow37 (3.8%)
Freezing Rain or Freezing Drizzle7 (0.7%)
Other/Unknown5 (0.5%)
Fog; Smog; Smoke4 (0.4%)
Sleet; Hail1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight575 (58.8%)
Dark - Roadway Not Lighted213 (21.8%)
Dark - Lighted Roadway124 (12.7%)
Dawn/Dusk54 (5.5%)
Dark - Unknown Roadway Lighting7 (0.7%)
Other/Unknown5 (0.5%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry733 (74.9%)
Wet190 (19.4%)
Snow28 (2.9%)
Ice19 (1.9%)
Slush4 (0.4%)
Sand; Mud; Dirt; Oil; Gravel2 (0.2%)
Other/Unknown2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

Among all persons involved in crashes, the 26-34 age group was the most represented, with 330 individuals. The vehicle makes most frequently involved in collisions were Ford with 238 vehicles, Chevrolet with 235, and Honda with 140.

Top Vehicle Makes (1,519 vehicles)

1
FORD238 (15.7%)
2
CHEVROLET235 (15.5%)
3
HONDA140 (9.2%)
4
TOYOTA98 (6.5%)
5
DODGE81 (5.3%)
6
JEEP76 (5%)
7
NISSAN61 (4%)
8
KIA53 (3.5%)
9
HYUNDAI45 (3%)
10
CHRYSLER44 (2.9%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

70 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (1,883 persons with recorded sex)

Male1,090 (57.9%)
Female793 (42.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Crash Location (First Harmful Event)

The first harmful event in most crashes, 641 incidents, occurred on the roadway itself. However, a significant portion, 314 crashes (32.1%), were run-off-road events, with the first impact happening on the roadside, shoulder, median, or outside the trafficway.

Crash Location (First Harmful Event)

"Other" combines 4 smaller categories (12 records): On ramp (5), Other/Unknown (3), On Gore (3), Shared-use paths or trails (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Traffic Control Device

Analysis of traffic controls at crash locations shows that a majority of involved vehicles (1,129 of 1,519) were in areas with no traffic control device present. Vehicles involved in crashes at signalized intersections accounted for 242 units, while 103 were at locations with a stop sign.

Traffic Control Device

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Driver Contributing Factor

The most frequently cited contributing factors for drivers involved in crashes were driving off the road (214 units), following too closely (128 units), and failure to yield (113 units). Unsafe speed was also a significant factor, attributed to 109 vehicle operators.

Driver Contributing Factor

1
Drove off Road214 (24.2%)
2
Following too Close / ACDA128 (14.4%)
3
Failure to Yield113 (12.8%)
4
Unsafe Speed109 (12.3%)
5
Other Improper Action56 (6.3%)
6
Improper Lane Change45 (5.1%)
7
Left of Center43 (4.9%)
8
Not Discernible42 (4.7%)
9
Ran Red Light28 (3.2%)

Showing top 9 of 22 reported. 13 additional (108 total) not shown: Improper Backing, Operating Defective Equipment, Ran Stop Sign, Improper Passing, Swerving to Avoid, Improper Turn, Load shifting/Falling/Spilling, Stopped or Parked Illegally, Improper Start From a Parked Position, Wrong Way, Vision Obstruction, Opening Door into Roadway, Improper Crossing.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Commercial / Truck Involvement

A total of 97 commercial trucks were involved in crashes during this period. Of these, 66 were identified as semi-tractor trailers, while the remaining 31 were classified as other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

Crashes involved 29 individuals classified as vulnerable road users or motorcyclists. This included 23 motorcyclists, 5 pedestrians, and 1 bicyclist. Combined, there were 6 crashes involving pedestrians or bicyclists.

Animal-Involved Crashes

There were 74 crashes involving animals, accounting for approximately 7.6% of all incidents in the county. The vast majority of these, 69 crashes, were collisions with deer, while an additional 5 crashes involved other types of animals.

Impairment (Alcohol / Drugs)

Impairment was a factor in 114 crashes, representing 11.7% of the total for the year. Among these, alcohol was cited in 65 incidents, drugs in 37, and a combination of both in 12. These figures represent a minimum baseline, as impairment can be under-reported.

Driver Condition

Beyond 'Apparently Normal,' several adverse driver conditions were noted for the 1,438 drivers involved in crashes. The most common was being under the influence of medications, drugs, or alcohol, which was recorded for 103 drivers. An additional 18 drivers were noted as having fallen asleep, fainted, or been fatigued.

Driver Condition

1
Apparently Normal1,217 (86.1%)
2
Under the Influence of Medications / Drugs / Alcohol103 (7.3%)
3
Other/Unknown64 (4.5%)
4
Fell Asleep; Fainted; Fatigued; etc.18 (1.3%)
5
Illness4 (0.3%)
6
Physical Impairment4 (0.3%)
7
Emotional (E.G.; Depressed; Angry; Disturbed)3 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Driver Distraction

Among 1,438 drivers, 59 were identified as being distracted at the time of their crash. The most cited issues were other distractions inside the vehicle (25 drivers) and outside the vehicle (17 drivers). Electronic devices were a factor for 17 drivers, including 6 who were manually operating a device.

Driver Distraction

1
Not Distracted1,227 (87.5%)
2
Other/Unknown116 (8.3%)
3
Other distraction inside the vehicle25 (1.8%)
4
Other distraction outside the vehicle17 (1.2%)
5
Other activity with an electronic device8 (0.6%)
6
Manually operating an electronic communication device (texting; typing; dialing)6 (0.4%)
7
Talking on hand-held communication device3 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Road Alignment

Road geometry played a role in a substantial number of crashes. Nearly half of all incidents (48.3%) occurred on a grade, while 32.6% of crashes happened on a curve. Crashes on sections that were both curved and graded accounted for 214 of the total 978 incidents.

Road Alignment

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Top Cities

The geographic distribution of crashes was concentrated in a few key areas. The city of Steubenville accounted for the largest share with 322 crashes (33.0% of the total). Island Creek followed with 173 crashes (17.7%), and Wintersville recorded 84 crashes (8.6%).

Top Cities

1
Steubenville322 (32.9%)
2
Island Creek173 (17.7%)
3
Wintersville84 (8.6%)
4
Warren46 (4.7%)
5
Knox43 (4.4%)
6
Wayne40 (4.1%)
7
Wells37 (3.8%)
8
Salem36 (3.7%)
9
Springfield33 (3.4%)

Showing top 9 of 29 reported. 20 additional (164 total) not shown: Cross Creek, Smithfield, Mingo Junction, Mount Pleasant, Richmond, Saline, Brush Creek, Adena, Dillonvale, Rayland, Tiltonsville, Ross, Amsterdam, Yorkville, New Alexandria, Stratton, Bloomingdale, Bergholz, Brilliant, Toronto.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Pre-Crash Driver Action

The most common pre-crash action for vehicles was driving straight ahead, which accounted for 739 of 1,519 vehicles involved. The next most frequent actions were negotiating a curve (224 vehicles) and slowing or stopping in traffic (140 vehicles).

Pre-Crash Driver Action

1
Straight Ahead739 (48.7%)
2
Negotiating a Curve224 (14.7%)
3
Slowing or Stopped In Traffic140 (9.2%)
4
Making Left Turn127 (8.4%)
5
Parked72 (4.7%)
6
Changing Lanes54 (3.6%)
7
Making Right Turn48 (3.2%)
8
Entering Traffic Lane37 (2.4%)
9
Backing33 (2.2%)

Showing top 9 of 16 reported. 7 additional (45 total) not shown: Other/Unknown, Overtaking/Passing, Leaving Traffic Lane, Driverless, Walking; Running; Jogging; Playing, Making U-Turn, Entering or Crossing Specified Location.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Manner of Collision

The dominant crash pattern was single-vehicle incidents, classified as 'Not Collision Between Two Vehicles in Transport,' which comprised 51.4% of all crashes (503 incidents). Among multi-vehicle collisions, angle crashes were the most frequent type, accounting for 184 incidents or 18.8% of the total.

Manner of Collision

"Other" combines 1 smaller categories (11 records): Other/Unknown (11).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 663 of the 1,519 total vehicles (43.7%). Sport Utility Vehicles (389) and Pick up trucks (234) were the next most frequent. Commercial vehicles, including semi-tractors and single-unit trucks, accounted for 101 of the vehicles involved.

Vehicle Type

"Other" combines 11 smaller categories (67 records): Cargo Van (18), Unknown or Hit/Skip (17), Other Vehicle (9), Bus (16+ Passengers) (8), Pedestrian/Skater (5), Van (9-15 Seats) (2), Farm Equipment (2), Heavy Equipment (2), All Terrain Vehicle (ATV/UTV) (2), Bicycle (1), Motorhome (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

Person Type

Of the 1,933 people involved in crashes, the vast majority were drivers (1,438 individuals, or 74.4%). Vehicle occupants, or passengers, accounted for another 490 people (25.3%). A small fraction, 5 individuals, were pedestrians.

Person Type

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Person Injury Severity

Among the 1,933 individuals involved in collisions, 1,547 (80.0%) sustained no injuries. A total of 337 people were injured, representing 17.4% of all persons involved. Fatal injuries were recorded for 5 individuals, accounting for 0.26% of the total.

Person Injury Severity

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Occupant Safety Equipment

Safety equipment usage was documented for occupants involved in crashes. While 1,547 individuals were recorded as using a shoulder and lap belt, 122 people were recorded as using no restraint system at all. This group accounts for 6.3% of all persons involved in crashes.

Occupant Safety Equipment

"Other" combines 3 smaller categories (28 records): Lap Belt Only Used (15), Helmet Used (12), Protective Pads Used (Elbow; knees; etc.) (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Vehicles Per Crash

The crashes were almost evenly split between single-vehicle and two-vehicle incidents. Single-vehicle crashes accounted for 473 events (48.4% of the total), while two-vehicle collisions numbered 474. An additional 31 crashes involved three or more vehicles.

Vehicles Per Crash

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Csv Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2021-01-01 through 2021-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 978
  • Total persons involved: 1,933
  • Total vehicles involved: 1,519

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "ohio, OH Crash Intelligence Report: 2021." Published July 5, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2021-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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Jefferson County, OH Crash Report — 2021 | ThatCarHitMe.com