Yearly Traffic Safety Analysis

261 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In Hardin County, total traffic crashes decreased from 310 in 2019 to 261 in 2020, a 15.8% reduction. Despite the drop in overall incidents, the number of fatalities increased from 5 to 6. The most significant change was a 33.9% decrease in total injuries, which fell from 109 in the prior year to 72 in the current period.

261

▼ -15.8%was 310

Total Crash Events

6

▲ 20.0%was 5

Persons Killed

72

▼ -33.9%was 109

Persons Injured

4

Fatal Crash Events

Note: "Persons Killed" (6) 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: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Hardin County showed a notable improvement in 2020 compared to the previous year. The total number of crashes fell by 15.8%, from 310 to 261. This decline was accompanied by a significant 33.9% reduction in injuries, although fatalities saw a slight increase from 5 to 6.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

6

Motorists Killed

Prior: 5↑20.0%

1

Cyclists Injured

Prior: 2↓-50.0%

71

Motorists Injured

Prior: 105↓-32.4%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Hardin County showed some shifts between 2019 and 2020. While Friday remained the peak day for crashes in both years, the count on Fridays decreased from 58 to 44. The peak hour for collisions moved from the 7 a.m. morning commute in 2019, which saw 27 crashes, to the 3 p.m. afternoon hour in 2020 with 17 crashes, indicating a change in daily traffic risk patterns.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes remained constant at 4 in both 2019 and 2020, the fatal crash rate increased from 1.29% to 1.53% due to the lower overall crash volume. The proportion of crashes resulting in possible injuries saw a marked decrease, falling from 15.2% of all crashes in 2019 to 10.0% in 2020. Consequently, the share of non-injury crashes rose from 71.3% to 75.9% of the total.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 6 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes1.5%
→0.0%prior 4
Serious Injury10serious injury crashes3.8%
→0.0%prior 10
Minor Injury23minor injury crashes8.8%
↓-17.9%prior 28
Possible Injury26possible injury crashes10%
↓-44.7%prior 47
No Injury198no injury crashes75.9%
↓-10.4%prior 221

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving animals remained the leading contributing factor in both periods, though the count decreased from 93 in 2019 to 87 in 2020. A significant reduction was observed in crashes attributed to 'Ran Stop Sign,' which plummeted from a count of 11 incidents in 2019 to just 1 in 2020. Conversely, crashes involving 'Driver Distraction: Other interior distraction' doubled in count from 7 to 14 year-over-year.

Officer-Reported Primary Contributing Cause

Animal87 (33.3%)↓-6.5%prior 93
Lost Control26 (10%)↓-7.1%prior 28
Driving too fast for conditions16 (6.1%)↓-11.1%prior 18
Driver Distraction: Other interior distraction14 (5.4%)↑100.0%prior 7
Ran off road - straight11 (4.2%)↓-26.7%prior 15
Ran off road - left11 (4.2%)↓-26.7%prior 15
Driver Distraction: Inattentive/lost in thought10 (3.8%)↑100.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner10 (3.8%)↓-33.3%prior 15
Followed too close9 (3.4%)↓-30.8%prior 13
Other (explain in narrative): Other8 (3.1%)↓-42.9%prior 14

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring on dry road surfaces increased from 42.6% in 2019 to 51.3% in 2020. Correspondingly, crashes on roads with snow or ice accounted for a smaller share of the total, dropping from 18.7% to 11.1% year-over-year. While the share of crashes in daylight decreased, incidents in dark, unlighted conditions rose from 15.5% to 19.5% of all crashes.

Weather

Clear121 (64.4%)
↓-10.4%prior 135
Cloudy37 (19.7%)
↓-22.9%prior 48
Snow12 (6.4%)
↓-29.4%prior 17
Freezing rain/drizzle6 (3.2%)
↑20.0%prior 5
Rain5 (2.7%)
↓-37.5%prior 8
Fog, smoke, smog4 (2.1%)
Blowing Snow3 (1.6%)
↓-70.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight112 (59.3%)
↓-24.8%prior 149
Dark - roadway not lighted51 (27.0%)
↑6.3%prior 48
Dark - roadway lighted17 (9.0%)
↓-15.0%prior 20
Dawn6 (3.2%)
↑20.0%prior 5
Dark - unknown roadway lighting2 (1.1%)
Dusk1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry134 (71.3%)
↑1.5%prior 132
Ice/frost18 (9.6%)
↓-28.0%prior 25
Wet15 (8.0%)
↓-31.8%prior 22
Snow11 (5.9%)
↓-66.7%prior 33
Gravel8 (4.3%)
↓-20.0%prior 10
Mud, dirt2 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

The demographic makeup of persons involved in crashes shifted, with the 26-34 age group's representation increasing from 15.2% to 18.4% of the total. In contrast, the share of persons in the 16-20 and 65+ age groups both decreased. Regarding vehicle makes, Chevrolet (80 vehicles, combining 'CHEV' and 'CHEVROLET') surpassed Ford (51 vehicles) as the most frequently involved make in 2020, reversing the ranking from 2019 when Ford led with 97 vehicles to Chevrolet's 87.

Top Vehicle Makes (330 vehicles)

1
CHEV56 (17%)
↓-9.7%prior 62
2
FORD51 (15.5%)
↓-47.4%prior 97
3
CHEVROLET24 (7.3%)
↓-4.0%prior 25
4
DODG13 (3.9%)
↓-45.8%prior 24
5
JEEP13 (3.9%)
↓-13.3%prior 15
6
DODGE11 (3.3%)
↑83.3%prior 6
7
TOYT11 (3.3%)
↓-35.3%prior 17
8
GMC10 (3%)
↓-37.5%prior 16
9
FREIGHTLINER10 (3%)
↑42.9%prior 7
10
HOND8 (2.4%)
↓-20.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

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

Sex Distribution (315 persons with recorded sex)

Male195 (61.9%)
↓-20.1%prior 244
Female120 (38.1%)
↓-27.3%prior 165

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 261
  • Total persons involved: 501
  • Total vehicles involved: 330

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-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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