Yearly Traffic Safety Analysis

738 CRASHES IN
OHIO, OH
2021

In 2021, Gallia County recorded 738 total traffic crashes, resulting in 7 fatalities and 253 injuries. A significant finding in the data is the high proportion of single-vehicle incidents; crashes not involving a collision with another vehicle in transport accounted for 56.5% of all crashes. The majority of collisions occurred during daylight hours on dry roads.

738

Total Crash Events

7

Persons Killed

253

Persons Injured

10.6%

Hit-and-Run Rate

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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

78

Hit-and-Run Crashes — 2021

During this period, 78 crashes were classified as hit-and-run incidents, accounting for 10.6% of all crashes in the county. This classification is based on the initial determination made by the responding law enforcement officer at the scene of the collision.

Vulnerable Road User Casualties

Motorists comprised the vast majority of individuals killed or injured in Gallia County crashes. In total, 7 motorists were killed and 251 were injured. During the same period, 2 pedestrians were injured, and no pedestrian or bicyclist fatalities were recorded.

0

Pedestrians Killed

7

Motorists Killed

2

Pedestrians Injured

251

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

Crash frequencies in Gallia County peaked on Fridays, which saw 138 incidents over the year. The single busiest hour for crashes was the 4 p.m. hour, with 63 recorded events. Overall, 60% of crashes (443) occurred during daylight hours, while 34% (254) happened in dark conditions.

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

The vast majority of crashes, 74.4% (549 incidents), resulted in no injuries. Injury-related crashes, including serious, minor, and possible injuries, constituted 24.8% of the total. In 2021, there were 6 fatal crashes, which resulted in a total of 7 fatalities, indicating at least one crash involved multiple deaths.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.8%
Serious Injury20serious injury crashes2.7%
Minor Injury109minor injury crashes14.8%
Possible Injury54possible injury crashes7.3%
No Injury549no 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

Most crashes in Gallia County occurred in ideal driving conditions. Specifically, 62.6% of crashes (462) happened in clear weather, 77.6% (573) on dry road surfaces, and 60% (443) during daylight hours. Crashes in adverse conditions included 68 in rain and 118 on wet roads.

Weather

Clear462 (62.6%)
Cloudy165 (22.4%)
Rain68 (9.2%)
Fog; Smog; Smoke18 (2.4%)
Snow12 (1.6%)
Sleet; Hail7 (0.9%)
Other/Unknown4 (0.5%)
Freezing Rain or Freezing Drizzle2 (0.3%)

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

Lighting

Daylight443 (60.0%)
Dark - Roadway Not Lighted206 (27.9%)
Dark - Lighted Roadway48 (6.5%)
Dawn/Dusk38 (5.1%)
Other/Unknown3 (0.4%)

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

Road Surface

Dry573 (77.6%)
Wet118 (16.0%)
Snow20 (2.7%)
Ice19 (2.6%)
Other/Unknown3 (0.4%)
Slush3 (0.4%)
Sand; Mud; Dirt; Oil; Gravel1 (0.1%)
Water (Standing; Moving)1 (0.1%)

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

Vehicles & Demographics

Among the 1,515 people involved in crashes, the most represented age groups were 26-34 years old (211 people) and 16-20 years old (208 people). Of the 1,116 vehicles involved, the most frequent makes were Chevrolet (223 vehicles), Ford (184), and Dodge (86). These were followed by Jeep (67) and Honda (58).

Top Vehicle Makes (1,116 vehicles)

1
CHEVROLET223 (20%)
2
FORD184 (16.5%)
3
DODGE86 (7.7%)
4
JEEP67 (6%)
5
HONDA58 (5.2%)
6
TOYOTA56 (5%)
7
NISSAN45 (4%)
8
GMC43 (3.9%)
9
KIA41 (3.7%)
10
CHRYSLER33 (3%)

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

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

Sex Distribution (1,468 persons with recorded sex)

Male789 (53.7%)
Female679 (46.3%)

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)

Analysis of the first harmful event's location shows that 465 crashes, or 63% of the total, occurred on the primary roadway. A significant portion, 230 crashes (31.2%), were classified as run-off-road events, with the first harmful event occurring on the roadside, shoulder, or in the median.

Crash Location (First Harmful Event)

"Other" combines 2 smaller categories (2 records): In Median (1), Driveway/Alley access (1).

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

Traffic Control Device

The majority of vehicles involved in crashes were at locations with no traffic controls present, accounting for 903 of the 1,116 vehicles in the dataset. Vehicles at locations with traffic signals were involved in 145 instances, and those at stop signs were involved in 56 instances.

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

Among driver-related contributing factors cited, unsafe speed was the most common, noted for 133 vehicles. This was followed by following too closely, which was a factor for 125 vehicles, and driving off the road, cited for 114 vehicles. Failure to yield was the fourth-most common factor, attributed to 73 vehicles.

Driver Contributing Factor

1
Unsafe Speed133 (20.9%)
2
Following too Close / ACDA125 (19.7%)
3
Drove off Road114 (18%)
4
Failure to Yield73 (11.5%)
5
Left of Center61 (9.6%)
6
Other Improper Action26 (4.1%)
7
Not Discernible16 (2.5%)
8
Swerving to Avoid15 (2.4%)
9
Improper Backing14 (2.2%)

Showing top 9 of 21 reported. 12 additional (58 total) not shown: Operating Defective Equipment, Improper Passing, Ran Red Light, Improper Lane Change, Ran Stop Sign, Improper Turn, Wrong Way, Load shifting/Falling/Spilling, Improper Crossing, Improper Start From a Parked Position, Stopped or Parked Illegally, Opening Door into Roadway.

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 66 commercial vehicles were involved in crashes in 2021. Of these, 36 were identified as semi-tractor trailers and 30 were classified as other types of commercial vehicles.

Vulnerable Road Users & Motorcycles

Crashes involved 15 vulnerable road users and motorcyclists. This total includes 13 motorcyclists and 2 pedestrians. No crashes involving bicyclists were recorded in the dataset for this period.

Animal-Involved Crashes

Animal-related collisions accounted for 100 crashes, representing 13.5% of all incidents in the county. The vast majority of these, 91 crashes, involved deer, while the remaining 9 involved other types of animals.

Impairment (Alcohol / Drugs)

Impairment was a factor in 63 crashes, or 8.5% of the total. Among these, alcohol was suspected in 25 cases, drugs in 21 cases, and a combination of alcohol and drugs in 17 cases.

Driver Condition

Of the 1,064 drivers involved in crashes, 82 were noted as being in a non-normal physical or mental state. This includes 56 drivers suspected of being under the influence of alcohol or drugs and 18 drivers who reportedly fell asleep, fainted, or were fatigued.

Driver Condition

1
Apparently Normal921 (88.3%)
2
Under the Influence of Medications / Drugs / Alcohol56 (5.4%)
3
Other/Unknown40 (3.8%)
4
Fell Asleep; Fainted; Fatigued; etc.18 (1.7%)
5
Emotional (E.G.; Depressed; Angry; Disturbed)4 (0.4%)
6
Illness2 (0.2%)
7
Physical Impairment2 (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 1,064 drivers, 58 were identified as being distracted at the time of their crash. The most common cited issues were other distractions inside the vehicle (28 drivers) and distractions outside the vehicle (13 drivers). Manually operating an electronic communication device was noted for 8 drivers.

Driver Distraction

1
Not Distracted918 (88.4%)
2
Other/Unknown62 (6%)
3
Other distraction inside the vehicle28 (2.7%)
4
Other distraction outside the vehicle13 (1.3%)
5
Manually operating an electronic communication device (texting; typing; dialing)8 (0.8%)
6
Other activity with an electronic device5 (0.5%)
7
Passenger4 (0.4%)

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 notable share of crashes. Collisions on curved sections of road accounted for 201 incidents (27.2% of total), while crashes on grades (inclines or declines) accounted for 216 incidents (29.3% of total). Crashes on straight, level roads were the most frequent, with 445 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 Gallipolis recorded the highest number of incidents with 241 crashes, representing 32.7% of the county's total. The townships of Green and Springfield followed, with 107 (14.5%) and 93 (12.6%) crashes, respectively.

Top Cities

1
Gallipolis241 (32.7%)
2
Green107 (14.5%)
3
Springfield93 (12.6%)
4
Addison62 (8.4%)
5
Raccoon47 (6.4%)
6
Clay35 (4.7%)
7
Huntington26 (3.5%)
8
Harrison25 (3.4%)
9
Cheshire21 (2.8%)

Showing top 9 of 18 reported. 9 additional (81 total) not shown: Morgan, Walnut, Ohio, Perry, Guyan, Greenfield, Rio Grande, Vinton, Crown City.

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 action for vehicles immediately prior to a crash was driving straight ahead, which accounted for 600 of the 1,116 vehicles involved (53.8%). The next most frequent pre-crash actions were negotiating a curve (171 vehicles, 15.3%) and slowing or stopping in traffic (128 vehicles, 11.5%).

Pre-Crash Driver Action

1
Straight Ahead600 (53.8%)
2
Negotiating a Curve171 (15.3%)
3
Slowing or Stopped In Traffic128 (11.5%)
4
Making Left Turn67 (6%)
5
Parked47 (4.2%)
6
Making Right Turn30 (2.7%)
7
Backing20 (1.8%)
8
Entering Traffic Lane19 (1.7%)
9
Overtaking/Passing9 (0.8%)

Showing top 9 of 16 reported. 7 additional (25 total) not shown: Leaving Traffic Lane, Changing Lanes, Other/Unknown, Driverless, Walking; Running; Jogging; Playing, Standing, Making U-Turn.

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

Manner of Collision

Single-vehicle crashes were the most common type of incident, with 417 crashes (56.5%) classified as 'Not Collision Between Two Vehicles in Transport'. Among multi-vehicle collisions, rear-end crashes were the most frequent, accounting for 122 incidents (16.5%), followed closely by angle collisions with 118 incidents (16.0%).

Manner of Collision

"Other" combines 1 smaller categories (7 records): Other/Unknown (7).

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 455 of the 1,116 vehicles (40.8%). Sport Utility Vehicles (270 vehicles) and Pick-up trucks (226 vehicles) were the next most frequent types. Commercial vehicles, including semi-tractors and single-unit trucks, were involved in 61 instances.

Vehicle Type

"Other" combines 11 smaller categories (45 records): Unknown or Hit/Skip (12), Cargo Van (9), Other Vehicle (6), Van (9-15 Seats) (4), All Terrain Vehicle (ATV/UTV) (4), Motorhome (2), Farm Equipment (2), Animal with Rider or Animal Drawn Vehicle (2), Pedestrian/Skater (2), Motorcycle 3 Wheeled (1), Heavy Equipment (1).

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

Person Type

The dataset includes 1,515 individuals involved in crashes. The majority of these were drivers, who accounted for 1,064 people (70.2% of the total). Vehicle occupants (passengers) represented another 449 people (29.6%), and 2 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

Of the 1,515 people involved in crashes, 253 sustained some level of injury, representing 16.7% of all individuals. An additional 7 individuals, or 0.46% of the total, suffered fatal injuries. The majority of people involved, 1,230 individuals, were not injured.

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

Among 1,515 vehicle occupants and other participants, 1,234 were reported as using a shoulder and lap belt. A total of 84 individuals, or 5.5% of all persons involved, were recorded as using no safety equipment at the time of the crash.

Occupant Safety Equipment

"Other" combines 2 smaller categories (13 records): Lap Belt Only Used (8), Helmet Used (5).

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 data shows a near-even split between single-vehicle and two-vehicle crashes. Single-vehicle crashes accounted for 50.7% of all incidents (374 crashes), while two-vehicle crashes made up 47.7% (352 crashes). Multi-vehicle incidents involving three or more vehicles were less common, with only 12 such crashes recorded.

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: 738
  • Total persons involved: 1,515
  • Total vehicles involved: 1,116

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