Yearly Traffic Safety Analysis

282 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Hardin County recorded 282 total crashes, an 8.1% increase from the 261 crashes reported in 2020. Despite the rise in total incidents, the number of fatalities saw a substantial decrease, falling from 6 in the prior year to 1 in the current period. Crashes involving suspected DUI also dropped significantly, from 15 in 2020 to 4 in 2021.

282

▲ 8.0%was 261

Total Crash Events

1

▼ -83.3%was 6

Persons Killed

74

▲ 2.8%was 72

Persons Injured

1

▼ -75.0%was 4

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Hardin County showed a moderate increase year-over-year, with total crashes rising by 8.1% from 261 in 2020 to 282 in 2021. While the overall volume of crashes grew, the number of resulting injuries remained nearly stable, increasing slightly from 72 to 74. In contrast, fatalities experienced a significant decline, dropping from 6 in 2020 to 1 in 2021.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 6↓-83.3%

1

Cyclists Injured

Prior: 1→0.0%

73

Motorists Injured

Prior: 71↑2.8%

Source: Iowa Crash Data · ArcGIS 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

The temporal patterns of crashes showed a notable shift in the peak time of day between the two periods. While Friday remained the busiest day for crashes in both 2021 (47 crashes) and 2020 (44 crashes), the peak hour moved from the 3 p.m. hour in 2020 (17 crashes) to the 9 p.m. hour in 2021 (22 crashes). This reflects a change from an afternoon peak in the prior year to a late-evening peak in the current year.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased significantly in 2021 compared to the prior year. The number of fatal crashes fell from 4 in 2020 to 1 in 2021, causing the fatal crash rate to drop from 1.53% to 0.35%. While the proportion of serious injury crashes also saw a slight decline from 3.8% to 3.2%, crashes resulting in minor injuries increased in both count (from 23 to 28) and share (from 8.8% to 9.9% of total crashes).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-75.0%prior 4
Serious Injury9serious injury crashes3.2%
↓-10.0%prior 10
Minor Injury28minor injury crashes9.9%
↑21.7%prior 23
Possible Injury28possible injury crashes9.9%
↑7.7%prior 26
No Injury216no injury crashes76.6%
↑9.1%prior 198

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both periods, with the count of such incidents increasing from 87 in 2020 to 99 in 2021. 'Lost Control' also held its position as the second most common factor, rising slightly from 26 to 28 crashes. Notably, crashes attributed to 'Followed too close' saw a significant increase in count, rising from 9 to 14 incidents. Conversely, crashes involving 'Driving too fast for conditions' decreased from 16 to 14.

Officer-Reported Primary Contributing Cause

Animal99 (35.1%)↑13.8%prior 87
Lost Control28 (9.9%)↑7.7%prior 26
Other (explain in narrative): Other19 (6.7%)↑137.5%prior 8
Followed too close14 (5%)↑55.6%prior 9
Ran off road - straight14 (5%)↑27.3%prior 11
Driving too fast for conditions14 (5%)↓-12.5%prior 16
Driver Distraction: Other interior distraction11 (3.9%)↓-21.4%prior 14
FTYROW: From stop sign10 (3.5%)
Ran off road - left7 (2.5%)↓-36.4%prior 11
Improper Backing6 (2.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across environmental conditions remained broadly similar year-over-year, with most incidents in both periods occurring in clear weather and during daylight hours on dry roads. However, there was a decrease in the number of crashes occurring in adverse weather, with incidents in snow falling from 12 to 7 and on icy roads from 18 to 15. Crashes in dark, unlighted conditions also decreased from 51 in 2020 to 41 in 2021.

Weather

Clear140 (72.9%)
↑15.7%prior 121
Cloudy26 (13.5%)
↓-29.7%prior 37
Snow7 (3.6%)
↓-41.7%prior 12
Rain6 (3.1%)
↑20.0%prior 5
Freezing rain/drizzle6 (3.1%)
→0.0%prior 6
Severe Winds2 (1.0%)
Fog, smoke, smog2 (1.0%)
Other (explain in narrative)1 (0.5%)
Blowing Snow1 (0.5%)
Sleet, hail1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight120 (62.8%)
↑7.1%prior 112
Dark - roadway not lighted41 (21.5%)
↓-19.6%prior 51
Dark - roadway lighted16 (8.4%)
↓-5.9%prior 17
Dawn5 (2.6%)
↓-16.7%prior 6
Dusk5 (2.6%)
Dark - unknown roadway lighting4 (2.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry137 (71.7%)
↑2.2%prior 134
Wet19 (9.9%)
↑26.7%prior 15
Ice/frost15 (7.9%)
↓-16.7%prior 18
Snow11 (5.8%)
→0.0%prior 11
Gravel7 (3.7%)
↓-12.5%prior 8
Slush1 (0.5%)
Mud, dirt1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes were consistent year-over-year, with Chevrolet (80 vehicles) and Ford (70 vehicles) being the most common in 2021, similar to the prior year where Chevrolet also had 80 and Ford had 51. An analysis of persons involved shows that the 26-34 age group was the most represented in both years, though their count decreased from 92 to 83. Conversely, involvement of the 16-20 age group increased from 58 to 73 persons, and the 65+ age group grew from 43 to 58 persons.

Top Vehicle Makes (377 vehicles)

1
FORD70 (18.6%)
↑37.3%prior 51
2
CHEV60 (15.9%)
↑7.1%prior 56
3
CHEVROLET20 (5.3%)
↓-16.7%prior 24
4
DODG19 (5%)
↑46.2%prior 13
5
HOND15 (4%)
↑87.5%prior 8
6
TOYT15 (4%)
↑36.4%prior 11
7
GMC12 (3.2%)
↑20.0%prior 10
8
DODGE11 (2.9%)
→0.0%prior 11
9
BUIC11 (2.9%)
↑57.1%prior 7
10
CHRY9 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (298 persons with recorded sex)

Male185 (62.1%)
↓-5.1%prior 195
Female113 (37.9%)
↓-5.8%prior 120

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS 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: ArcGIS 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: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 282
  • Total persons involved: 514
  • Total vehicles involved: 377

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). "iowa, IA Crash Intelligence Report: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/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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