Monthly Traffic Safety Analysis

246 CRASHES IN
OHIO, OH
APRIL 2021

In April 2021, Allen County recorded 246 traffic crashes, resulting in 2 fatalities and 122 injuries. A significant portion of these incidents, 43.9%, were single-vehicle crashes not involving a collision with another vehicle in transport. The data also indicates that Thursday was the peak day for crashes, and the 4 p.m. hour saw the highest frequency of incidents.

246

Total Crash Events

2

Persons Killed

122

Persons Injured

16.7%

Hit-and-Run Rate

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 · 2021-04-01 to 2021-04-30 · Aggregate counts from crash, person, and vehicle records

41

Hit-and-Run Crashes — April 2021

Based on the initial determination of responding officers, 41 crashes in April 2021 were classified as hit-and-run incidents. This represents 16.7% of all crashes recorded in Allen County during this period.

Vulnerable Road User Casualties

During this period, there was one pedestrian fatality and three pedestrians injured in a total of four crashes involving pedestrians. Additionally, one motorist was killed and 119 were injured. No cyclists were reported killed or injured in the single bicycle-involved crash.

1

Pedestrians Killed

1

Motorists Killed

3

Pedestrians Injured

119

Motorists Injured

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash patterns in Allen County show a concentration during the latter part of the work week, with Thursday being the peak day with 49 incidents. The afternoon commute hour from 4 p.m. to 5 p.m. was the single busiest hour for crashes, recording 25 events. Overall, crashes were most frequent during daylight hours, which accounted for 184 of the 246 total incidents.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 246 crashes, the majority (67.9%) resulted in no injuries. Injury-related crashes, including serious, minor, and possible injuries, accounted for 77 incidents. There were 2 fatal crashes recorded, which resulted in a total of 2 fatalities.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.8%
Serious Injury10serious injury crashes4.1%
Minor Injury37minor injury crashes15%
Possible Injury30possible injury crashes12.2%
No Injury167no injury crashes67.9%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Most severe injury per crash record

Road & Environmental Conditions

The vast majority of crashes occurred in ideal driving conditions. Crashes in clear weather accounted for 68.3% of the total, while 82.9% happened on dry road surfaces. Similarly, 184 out of 246 crashes (74.8%) took place during daylight hours. Adverse conditions were less common, with 22 crashes reported during rain and 41 on wet roads.

Weather

Clear168 (68.3%)
Cloudy50 (20.3%)
Rain22 (8.9%)
Snow3 (1.2%)
Fog; Smog; Smoke2 (0.8%)
Other/Unknown1 (0.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Weather condition at time of crash

Lighting

Daylight184 (74.8%)
Dark - Roadway Not Lighted26 (10.6%)
Dark - Lighted Roadway25 (10.2%)
Dawn/Dusk7 (2.8%)
Dark - Unknown Roadway Lighting2 (0.8%)
Other/Unknown2 (0.8%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Lighting condition field

Road Surface

Dry204 (82.9%)
Wet41 (16.7%)
Other/Unknown1 (0.4%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows the 16-20 age group was the most represented, with 96 individuals. Among the 423 vehicles involved, Ford (75 vehicles) and Chevrolet (74 vehicles) were the most frequent makes recorded in crash reports. Dodge was the third most common make with 33 vehicles involved.

Top Vehicle Makes (423 vehicles)

1
FORD75 (17.7%)
2
CHEVROLET74 (17.5%)
3
DODGE33 (7.8%)
4
HONDA25 (5.9%)
5
NISSAN21 (5%)
6
TOYOTA18 (4.3%)
7
BUICK15 (3.5%)
8
CHRYSLER14 (3.3%)
9
KIA13 (3.1%)
10
HYUNDAI11 (2.6%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Vehicle unit records

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

Sex Distribution (530 persons with recorded sex)

Male274 (51.7%)
Female256 (48.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Person-level records linked to crash events

Crash Location (First Harmful Event)

The initial point of impact for most crashes (204 out of 246) occurred on the roadway itself. However, a notable number of incidents were run-off-road events, with a combined 30 crashes originating on the roadside, shoulder, or in the median. These run-off-road crashes represent 12.2% of all incidents.

Crash Location (First Harmful Event)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash-level records

Traffic Control Device

Analysis of traffic controls present at crash locations shows that most vehicles involved (268 of 423) were at sites with no traffic control device. Vehicles involved in crashes at signalized intersections accounted for 97 instances. Crashes involving vehicles at locations with stop signs were recorded 41 times.

Traffic Control Device

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Vehicle unit records

Driver Contributing Factor

The most frequently cited contributing factor for drivers was 'Following too Close / ACDA,' attributed to 48 vehicles. 'Failure to Yield' was the second most common factor, noted for 36 vehicles involved in crashes. 'Drove off Road' was listed as a contributing circumstance for 29 vehicles.

Driver Contributing Factor

1
Following too Close / ACDA48 (21.7%)
2
Failure to Yield36 (16.3%)
3
Drove off Road29 (13.1%)
4
Other Improper Action19 (8.6%)
5
Not Discernible17 (7.7%)
6
Ran Red Light13 (5.9%)
7
Improper Backing10 (4.5%)
8
Unsafe Speed10 (4.5%)
9
Improper Turn9 (4.1%)

Showing top 9 of 19 reported. 10 additional (30 total) not shown: Ran Stop Sign, Operating Defective Equipment, Improper Lane Change, Left of Center, Load shifting/Falling/Spilling, Swerving to Avoid, Wrong Way, Improper Crossing, Improper Passing, Lying in Roadway.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Vehicle unit records

Commercial / Truck Involvement

Crashes involving commercial trucks were recorded in 12 instances, accounting for approximately 4.9% of all crashes in this period. Of these, 9 involved a semi-tractor trailer, while 3 involved other types of commercial vehicles.

Animal-Involved Crashes

Collisions with animals accounted for 19 crashes, or 7.7% of the total incidents in April. The vast majority of these, 17 crashes, involved collisions with deer. An additional 2 crashes were recorded as involving other types of animals.

Impairment (Alcohol / Drugs)

Impairment was a factor in 21 crashes, representing 8.5% of all incidents. Among these, alcohol was suspected in 14 cases, drugs in 5 cases, and a combination of alcohol and drugs in 2 cases. These figures represent a minimum, as impairment may be under-reported in official crash data.

Driver Condition

While most drivers (336) were listed as 'Apparently Normal,' 31 drivers were recorded with a specific adverse condition. This includes 14 drivers noted as being under the influence of medications, drugs, or alcohol. Additionally, 7 drivers had a physical impairment, and 6 were noted as being in an emotional state such as anger or distress.

Driver Condition

1
Apparently Normal336 (87%)
2
Other/Unknown19 (4.9%)
3
Under the Influence of Medications / Drugs / Alcohol14 (3.6%)
4
Physical Impairment7 (1.8%)
5
Emotional (E.G.; Depressed; Angry; Disturbed)6 (1.6%)
6
Fell Asleep; Fainted; Fatigued; etc.3 (0.8%)
7
Illness1 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Person-level records linked to crash events

Driver Distraction

Among the 393 drivers involved in crashes, 19 were noted as being distracted. The most common specified distraction was 'Other distraction inside the vehicle,' with 7 instances. Manually operating an electronic device like a phone was cited for 3 drivers, while another 2 were distracted by passengers.

Driver Distraction

1
Not Distracted348 (90.4%)
2
Other/Unknown18 (4.7%)
3
Other distraction inside the vehicle7 (1.8%)
4
Other distraction outside the vehicle5 (1.3%)
5
Manually operating an electronic communication device (texting; typing; dialing)3 (0.8%)
6
Other activity with an electronic device2 (0.5%)
7
Passenger2 (0.5%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Person-level records linked to crash events

Road Alignment

The majority of crashes (212) occurred on straight, level sections of roadway. However, road geometry played a role in some incidents, with 19 crashes (7.7%) occurring on curves. An identical number of crashes, 19, also occurred on graded sections of road, both straight and curved.

Road Alignment

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash-level records

Top Cities

The geographic distribution of crashes within Allen County was concentrated in a few key areas. The City of Lima saw the highest volume, with 112 crashes, accounting for 45.5% of the county's total. The townships of American and Bath followed, with 30 and 28 crashes respectively.

Top Cities

1
Lima112 (45.5%)
2
American30 (12.2%)
3
Bath28 (11.4%)
4
Shawnee20 (8.1%)
5
Perry15 (6.1%)
6
Richland8 (3.3%)
7
Monroe6 (2.4%)
8
Marion5 (2%)
9
Auglaize4 (1.6%)

Showing top 9 of 16 reported. 7 additional (18 total) not shown: Sugar Creek, Bluffton, Delphos, Jackson, Fort Shawnee, Elida, Amanda.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash-level records

Pre-Crash Driver Action

Prior to impact, the most common action for vehicles involved was 'Straight Ahead,' which accounted for 251 of the 423 units. A significant number of vehicles, 49, were either slowing or stopped in traffic at the time of the crash. Making a left turn was the third most frequent pre-crash action, recorded for 28 vehicles.

Pre-Crash Driver Action

1
Straight Ahead251 (59.3%)
2
Slowing or Stopped In Traffic49 (11.6%)
3
Making Left Turn28 (6.6%)
4
Parked26 (6.1%)
5
Negotiating a Curve16 (3.8%)
6
Other/Unknown13 (3.1%)
7
Backing13 (3.1%)
8
Making Right Turn13 (3.1%)
9
Entering Traffic Lane5 (1.2%)

Showing top 9 of 15 reported. 6 additional (9 total) not shown: Changing Lanes, Other Non-Motorist, Overtaking/Passing, Leaving Traffic Lane, Standing, Making U-Turn.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Vehicle unit records

Manner of Collision

The most common type of crash was a single-vehicle incident, categorized as 'Not Collision Between Two Vehicles in Transport,' which accounted for 108 crashes or 43.9% of the total. Among multi-vehicle crashes, angle collisions were the most frequent, with 54 incidents (22.0%), followed closely by rear-end collisions, which occurred 47 times (19.1%).

Manner of Collision

"Other" combines 2 smaller categories (5 records): Head-on (4), Rear-to-rear (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 208 of the 423 vehicles. Sport Utility Vehicles (100) and Pick-up trucks (54) were also frequently involved. Commercial vehicles, including 11 semi-tractors and 6 single-unit trucks, were present in these incidents as well.

Vehicle Type

"Other" combines 8 smaller categories (20 records): Motorcycle 2 Wheeled (5), Cargo Van (5), Pedestrian/Skater (4), Other Vehicle (2), Van (9-15 Seats) (1), Bicycle (1), Moped or Motorized Bicycle (1), All Terrain Vehicle (ATV/UTV) (1).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Vehicle unit records

Person Type

Of the 556 individuals involved in crashes, the majority were drivers, accounting for 393 people or 70.7% of the total. Vehicle occupants (passengers) made up the next largest group with 159 individuals. Four pedestrians were also involved in crashes during this period.

Person Type

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash-level records

Person Injury Severity

Across all 556 people involved in crashes, 122 individuals sustained some level of injury, representing 21.9% of all participants. This included 13 serious injuries, 47 minor injuries, and 62 possible injuries. Two individuals suffered fatal injuries, while the majority, 427 people, were not injured.

Person Injury Severity

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Crash-level records

Occupant Safety Equipment

Safety equipment usage was reported for 552 participants, with 439 individuals (79.5%) recorded as using both a shoulder and lap belt. A total of 20 individuals involved in crashes were documented as not using any safety equipment. Additionally, various child restraint systems were in use, including 13 forward-facing seats and 7 rear-facing seats.

Occupant Safety Equipment

"Other" combines 2 smaller categories (4 records): Helmet Used (2), Shoulder Belt Only Used (2).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · Person-level records linked to crash events

Vehicles Per Crash

The majority of incidents, 157 out of 246, were two-vehicle collisions, making up 63.8% of the total. Single-vehicle crashes were also common, accounting for 80 incidents or 32.5% of all crashes. Crashes involving three or more vehicles were less frequent, with a total of 9 such events recorded.

Vehicles Per Crash

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2021-04-01 to 2021-04-30 · 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: 2021-04-01 through 2021-04-30
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2021-04-01 through 2021-04-30 (30 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 246
  • Total persons involved: 556
  • Total vehicles involved: 423

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 2021." Published July 6, 2026. Reporting period: 2021-04-01 to 2021-04-30. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/april-2021-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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Allen County, OH Crash Report — April 2021 | ThatCarHitMe.com