Monthly Traffic Safety Analysis

20,169 CRASHES IN
OHIO, OH
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, there were 20,169 total crashes, a 4.0% decrease from the 20,999 crashes recorded in April 2021. Despite the overall reduction in crashes and a corresponding 8.8% drop in injuries, the most notable year-over-year change was an 11.5% increase in total fatalities, which rose from 104 to 116.

20,169

-4.0%was 20,999

Total Crash Events

116

11.5%was 104

Persons Killed

7,497

-8.8%was 8,218

Persons Injured

3,688

-7.5%was 3,989

Hit-and-Run Crashes

Note: "Persons Killed" (116) counts individual fatalities across all crash events. "Fatal" in the severity table below (106) 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 · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash volume decreased in April 2022 compared to the same month in the prior year. Total crashes fell by 4.0%, from 20,999 to 20,169. However, this downward trend did not extend to the most severe outcomes, as total fatalities increased from 104 to 116.

3,688

Hit-and-Run Crashes — April 2022

-7.5% vs prior (3,989)

Hit-and-run incidents decreased both in absolute numbers and as a percentage of total crashes. In April 2022, there were 3,688 hit-and-run crashes, down from 3,989 in the same month of the previous year. The hit-and-run rate also declined, falling from 19.0% of all crashes in April 2021 to 18.3% in April 2022.

Vulnerable Road User Casualties

11

Pedestrians Killed

Prior: 16-31.3%

105

Motorists Killed

Prior: 8819.3%

169

Pedestrians Injured

Prior: 14318.2%

7,328

Motorists Injured

Prior: 8,075-9.3%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained broadly consistent year-over-year, with Friday being the peak day and 4 p.m. being the peak hour in both periods. In April 2022, Friday saw 3,923 crashes, compared to 3,994 in April 2021. The peak 4 p.m. hour recorded 1,752 crashes in the current period, down from 1,817 in the prior year.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of outcomes worsened year-over-year. The number of fatal crashes rose from 96 to 106, and the fatal crash rate increased from 0.46% to 0.53% of all crashes. The proportion of crashes resulting in minor injuries decreased from 14.0% to 12.9%, while the share of no-injury crashes increased from 72.4% to 73.8%.

Severity is per crash event (most severe injury). 106 fatal crash events resulted in 116 persons killed.

Outcome by Severity (Crash Events)

Fatal106fatal crashes0.5%
10.4%prior 96
Serious Injury507serious injury crashes2.5%
-1.7%prior 516
Minor Injury2,600minor injury crashes12.9%
-11.6%prior 2,942
Possible Injury2,063possible injury crashes10.2%
-8.4%prior 2,252
No Injury14,893no injury crashes73.8%
-2.0%prior 15,193

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Road & Environmental Conditions

The proportion of crashes occurring in adverse conditions increased in April 2022 compared to the prior year. Crashes on wet roads accounted for 22.0% of the total, up from 17.4% in April 2021, and the share of crashes during rain increased from 10.5% to 12.7%. In contrast, the distribution of crashes by lighting conditions remained stable, with approximately 71% of incidents in both periods occurring during daylight.

Weather

Clear11,219 (55.6%)
-15.0%prior 13,193
Cloudy5,507 (27.3%)
16.2%prior 4,739
Rain2,564 (12.7%)
16.3%prior 2,204
Snow440 (2.2%)
-20.1%prior 551
Other/Unknown229 (1.1%)
3.2%prior 222
Fog; Smog; Smoke112 (0.6%)
143.5%prior 46
Sleet; Hail71 (0.4%)
317.6%prior 17
Freezing Rain or Freezing Drizzle23 (0.1%)
27.8%prior 18
Severe Crosswinds3 (0.0%)
-40.0%prior 5
Blowing Sand; Soil; Dirt; Snow1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight14,408 (71.4%)
-3.7%prior 14,966
Dark - Lighted Roadway2,630 (13.0%)
-7.6%prior 2,847
Dark - Roadway Not Lighted1,941 (9.6%)
2.2%prior 1,900
Dawn/Dusk928 (4.6%)
-8.9%prior 1,019
Other/Unknown174 (0.9%)
-5.4%prior 184
Dark - Unknown Roadway Lighting88 (0.4%)
6.0%prior 83

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry15,246 (75.6%)
-8.6%prior 16,677
Wet4,443 (22.0%)
21.3%prior 3,664
Snow211 (1.0%)
-26.0%prior 285
Other/Unknown181 (0.9%)
37.1%prior 132
Slush38 (0.2%)
31.0%prior 29
Ice32 (0.2%)
-82.4%prior 182
Sand; Mud; Dirt; Oil; Gravel10 (0.0%)
-44.4%prior 18
Water (Standing; Moving)8 (0.0%)
-33.3%prior 12

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent year-over-year: Chevrolet, Ford, and Honda, although the number of crashes involving Chevrolet and Ford vehicles decreased. The age demographics of persons involved in crashes also showed a similar pattern between the two periods. The 26-34 age group represented the largest cohort of individuals in both April 2022 (7,230 persons) and April 2021 (7,790 persons), with no significant shifts in proportional representation among age groups.

Top Vehicle Makes (36,696 vehicles)

1
CHEVROLET5,204 (14.2%)
-11.4%prior 5,871
2
FORD5,065 (13.8%)
-9.0%prior 5,566
3
HONDA3,231 (8.8%)
-0.4%prior 3,244
4
TOYOTA2,792 (7.6%)
1.0%prior 2,763
5
DODGE1,844 (5%)
-11.9%prior 2,093
6
NISSAN1,685 (4.6%)
-6.5%prior 1,802
7
JEEP1,529 (4.2%)
6.5%prior 1,436
8
KIA1,415 (3.9%)
-0.6%prior 1,423
9
HYUNDAI1,392 (3.8%)
-4.4%prior 1,456
10
OTHER/UNKNOWN977 (2.7%)
5.5%prior 926

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

3,451 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (42,950 persons with recorded sex)

Male23,349 (54.4%)
-4.9%prior 24,563
Female19,601 (45.6%)
-3.8%prior 20,384

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 20,169
  • Total persons involved: 45,593
  • Total vehicles involved: 36,696

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: April 2022." Published July 5, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/april-2022-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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Ohio (Statewide) Crash Report — April 2022 | ThatCarHitMe.com