Yearly Traffic Safety Analysis

262 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Meigs County, total traffic crashes decreased from 338 in 2024 to 262 in 2025, a reduction of 22.5%. Despite this overall decline in collisions, the number of fatalities increased from 4 to 5. The most significant year-over-year change was the 33.1% decrease in total injuries, which fell from 172 to 115.

262

-22.5%was 338

Total Crash Events

5

25.0%was 4

Persons Killed

115

-33.1%was 172

Persons Injured

18

-25.0%was 24

Hit-and-Run Crashes

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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Meigs County showed a notable improvement from 2024 to 2025, with total crashes falling by 22.5% from 338 to 262. This downward trend was also reflected in the number of people injured, which decreased by 33.1% from 172 to 115. However, the number of fatalities increased from 4 to 5 year-over-year.

18

Hit-and-Run Crashes — 2025

-25.0% vs prior (24)

Hit-and-run incidents decreased from 2024 to 2025, both in absolute numbers and as a percentage of total crashes. The number of hit-and-run crashes fell by 25%, from 24 to 18. The hit-and-run rate also saw a slight decline, moving from 7.1% of all crashes in the prior year to 6.9% in the current year.

Vulnerable Road User Casualties

5

Motorists Killed

Prior: 425.0%

115

Motorists Injured

Prior: 169-32.0%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes in Meigs County shifted between 2024 and 2025. The peak day for collisions moved from Monday and Friday (54 crashes each) in the prior year to Wednesday (46 crashes) in the current year. Similarly, the most frequent time for crashes changed from the 7 AM hour in 2024 (29 crashes) to the 5 PM hour in 2025 (26 crashes), indicating a shift from morning to evening commute times as the primary period of risk.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the absolute number of fatal crashes remained unchanged at 4 in both 2024 and 2025, the fatal crash rate increased from 1.18% to 1.53% due to the lower total number of crashes in the current year. The proportion of crashes resulting in any injury decreased, from 36.4% in 2024 to 30.2% in 2025. Notably, serious injury crashes fell from 30 to 17, while the share of crashes with no injuries increased from 62.4% to 68.3%.

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

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.5%
0.0%prior 4
Serious Injury17serious injury crashes6.5%
-43.3%prior 30
Minor Injury40minor injury crashes15.3%
-36.5%prior 63
Possible Injury22possible injury crashes8.4%
-26.7%prior 30
No Injury179no injury crashes68.3%
-15.2%prior 211

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and daylight. However, the proportion of crashes on dry road surfaces decreased from 84.0% in 2024 to 76.7% in 2025. Concurrently, the share of crashes occurring on snow-covered roads increased from 1.8% to 6.1%, and crashes on icy roads rose from 0.3% to 2.3% of the total.

Weather

Clear166 (63.4%)
-28.1%prior 231
Cloudy65 (24.8%)
0.0%prior 65
Rain16 (6.1%)
-36.0%prior 25
Snow13 (5.0%)
44.4%prior 9
Fog; Smog; Smoke1 (0.4%)
-87.5%prior 8
Other/Unknown1 (0.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight169 (64.5%)
-16.7%prior 203
Dark - Roadway Not Lighted70 (26.7%)
-22.2%prior 90
Dark - Lighted Roadway12 (4.6%)
-29.4%prior 17
Dawn/Dusk9 (3.4%)
-67.9%prior 28
Other/Unknown2 (0.8%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry201 (76.7%)
-29.2%prior 284
Wet34 (13.0%)
-27.7%prior 47
Snow16 (6.1%)
166.7%prior 6
Ice6 (2.3%)
Sand; Mud; Dirt; Oil; Gravel3 (1.1%)
Slush1 (0.4%)
Other/Unknown1 (0.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The ranking of vehicle makes involved in crashes shifted year-over-year. In 2025, Ford became the most frequent make with 79 vehicles, surpassing Chevrolet, which had 69 vehicles involved. In the prior year, Chevrolet was the top make with 88 vehicles, followed by Ford with 81. The age distribution of persons involved in crashes remained proportionally consistent between the two periods.

Top Vehicle Makes (369 vehicles)

1
FORD79 (21.4%)
-2.5%prior 81
2
CHEVROLET69 (18.7%)
-21.6%prior 88
3
TOYOTA29 (7.9%)
-6.5%prior 31
4
HONDA22 (6%)
-42.1%prior 38
5
DODGE20 (5.4%)
-20.0%prior 25
6
NISSAN20 (5.4%)
-23.1%prior 26
7
JEEP19 (5.1%)
-26.9%prior 26
8
GMC16 (4.3%)
23.1%prior 13
9
KIA14 (3.8%)
-6.7%prior 15
10
HYUNDAI13 (3.5%)
30.0%prior 10

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (472 persons with recorded sex)

Male284 (60.2%)
-16.2%prior 339
Female188 (39.8%)
-38.4%prior 305

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 262
  • Total persons involved: 483
  • Total vehicles involved: 369

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: 2025." Published July 6, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2025-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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Meigs County, OH Crash Report — 2025 | ThatCarHitMe.com