Yearly Traffic Safety Analysis

675 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Gallia County recorded 675 traffic crashes, a decrease of 8.5% from the 738 crashes reported in 2021. Despite the overall decline in collisions, the number of people injured increased from 253 to 263. The number of fatal crashes also increased from 6 to 7, and crashes resulting in serious injuries rose from 20 to 25 over the same period.

675

-8.5%was 738

Total Crash Events

7

Persons Killed

263

4.0%was 253

Persons Injured

76

-2.6%was 78

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Gallia County saw a downward trend, decreasing by 8.5% from 738 in 2021 to 675 in 2022. However, the number of people injured in these incidents increased by 4.0% year-over-year, rising from 253 to 263. The total number of fatalities remained unchanged at 7 for both years.

76

Hit-and-Run Crashes — 2022

-2.6% vs prior (78)

The absolute number of hit-and-run incidents decreased slightly from 78 in 2021 to 76 in 2022. However, because the total number of crashes fell at a faster pace, the hit-and-run rate as a percentage of all crashes increased. The rate rose from 10.6% in the prior year to 11.3% in the current year, indicating that hit-and-runs constituted a larger proportion of total crashes in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

7

Motorists Killed

Prior: 70.0%

1

Pedestrians Injured

Prior: 2-50.0%

262

Motorists Injured

Prior: 2514.4%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between 2021 and 2022. The peak day for collisions moved from Friday (138 crashes) in 2021 to Thursday (125 crashes) in 2022. The afternoon commute remained the most frequent time for incidents, with the peak hour shifting slightly from 4 p.m. in the prior year to 3 p.m. in the current year.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of outcomes worsened in some categories. The number of fatal crashes increased from 6 in 2021 to 7 in 2022, and the fatal crash rate rose from 0.81 to 1.04 per 100 crashes. Crashes resulting in serious injuries also saw a notable increase of 25%, rising from 20 to 25 incidents year-over-year, while crashes involving minor injuries decreased from 109 to 86.

Outcome by Severity (Crash Events)

Fatal7fatal crashes1%
16.7%prior 6
Serious Injury25serious injury crashes3.7%
25.0%prior 20
Minor Injury86minor injury crashes12.7%
-21.1%prior 109
Possible Injury70possible injury crashes10.4%
29.6%prior 54
No Injury487no injury crashes72.1%
-11.3%prior 549

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely consistent year-over-year. In both 2022 and 2021, the majority of incidents occurred during daylight hours (61.0% and 60.0%, respectively) and on dry road surfaces (78.5% and 77.6%, respectively). Similarly, clear weather was reported in over 62% of crashes in both periods, indicating no significant shift in the role of adverse conditions.

Weather

Clear428 (63.4%)
-7.4%prior 462
Cloudy148 (21.9%)
-10.3%prior 165
Rain65 (9.6%)
-4.4%prior 68
Snow16 (2.4%)
33.3%prior 12
Fog; Smog; Smoke12 (1.8%)
-33.3%prior 18
Other/Unknown4 (0.6%)
Freezing Rain or Freezing Drizzle1 (0.1%)
Sleet; Hail1 (0.1%)
-85.7%prior 7

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight412 (61.0%)
-7.0%prior 443
Dark - Roadway Not Lighted171 (25.3%)
-17.0%prior 206
Dark - Lighted Roadway52 (7.7%)
8.3%prior 48
Dawn/Dusk36 (5.3%)
-5.3%prior 38
Other/Unknown3 (0.4%)
Dark - Unknown Roadway Lighting1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry530 (78.5%)
-7.5%prior 573
Wet108 (16.0%)
-8.5%prior 118
Snow25 (3.7%)
25.0%prior 20
Ice8 (1.2%)
-57.9%prior 19
Sand; Mud; Dirt; Oil; Gravel2 (0.3%)
Slush1 (0.1%)
Other/Unknown1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The composition of vehicles involved in crashes remained stable, with Passenger Cars, Sport Utility Vehicles, and Pick-ups being the three most common types in both years. Chevrolet and Ford were the top two makes involved in collisions in both periods, though Chevrolet's involvement decreased from 223 vehicles in 2021 to 188 in 2022. Analysis of persons involved shows a shift in the most represented age demographic, moving from the 26-34 age group in 2021 to the 35-44 age group in 2022.

Top Vehicle Makes (1,041 vehicles)

1
CHEVROLET188 (18.1%)
-15.7%prior 223
2
FORD188 (18.1%)
2.2%prior 184
3
DODGE76 (7.3%)
-11.6%prior 86
4
TOYOTA61 (5.9%)
8.9%prior 56
5
JEEP52 (5%)
-22.4%prior 67
6
HONDA45 (4.3%)
-22.4%prior 58
7
NISSAN40 (3.8%)
-11.1%prior 45
8
CHRYSLER39 (3.7%)
18.2%prior 33
9
GMC37 (3.6%)
-14.0%prior 43
10
KIA32 (3.1%)
-22.0%prior 41

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (1,305 persons with recorded sex)

Male762 (58.4%)
-3.4%prior 789
Female543 (41.6%)
-20.0%prior 679

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

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: 2022-01-01 through 2022-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 675
  • Total persons involved: 1,358
  • Total vehicles involved: 1,041

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: 2022." Published July 5, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2022-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 — 2022 | ThatCarHitMe.com