Yearly Traffic Safety Analysis

209 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Mills County, total traffic crashes increased from 196 in 2020 to 209 in 2021, a rise of 6.6%. Despite this increase in overall collisions, the most significant year-over-year change was a drop in traffic fatalities, which fell from 5 in the prior period to 0 in the current period. The total number of injuries, however, rose from 62 to 78.

209

▲ 6.6%was 196

Total Crash Events

0

▼ -100.0%was 5

Persons Killed

78

▲ 25.8%was 62

Persons Injured

0

▼ -100.0%was 3

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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

Traffic crashes in Mills County showed a slight upward trend, increasing by 6.6% from 196 in 2020 to 209 in 2021. While total crashes rose, fatal crashes were eliminated, dropping from 3 in the prior year to 0. Conversely, the number of people injured in these incidents increased from 62 to 78.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 5↓-100.0%

1

Cyclists Injured

Prior: 2↓-50.0%

77

Motorists Injured

Prior: 59↑30.5%

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 peak day for crashes shifted from Friday (38 crashes) in 2020 to Saturday (41 crashes) in 2021. The peak hour also moved later in the day, from 12 p.m. in the prior period (14 crashes) to a tie between 1 p.m. and 2 p.m. in the current period (17 crashes each). Crashes on Saturdays saw a notable increase, rising from 24 in 2020 to 41 in 2021.

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

Crash severity saw a positive shift, with fatal crashes decreasing from 3 in 2020 to 0 in 2021, and total fatalities dropping from 5 to 0. The number of serious injury crashes increased slightly from 8 to 10, while minor injury crashes rose from 28 to 32. The proportion of crashes resulting in no injuries increased from 69.4% in 2020 to 71.8% in 2021.

Outcome by Severity (Crash Events)

Serious Injury10serious injury crashes4.8%
↑25.0%prior 8
Minor Injury32minor injury crashes15.3%
↑14.3%prior 28
Possible Injury17possible injury crashes8.1%
↓-19.0%prior 21
No Injury150no injury crashes71.8%
↑10.3%prior 136

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

The top three contributing factors remained consistent in ranking across both periods: collisions with an animal, losing control, and running off a straight road. Crashes involving an animal, the leading factor, increased in count from 39 in 2020 to 45 in 2021. The count for crashes attributed to 'Driving too fast for conditions' also saw a notable increase, rising from 11 to 17. Conversely, crashes due to 'Lost Control' saw a slight decrease from 27 to 26.

Officer-Reported Primary Contributing Cause

Animal45 (21.5%)↑15.4%prior 39
Lost Control26 (12.4%)↓-3.7%prior 27
Ran off road - straight19 (9.1%)↑26.7%prior 15
Driving too fast for conditions17 (8.1%)↑54.5%prior 11
FTYROW: From stop sign12 (5.7%)↑20.0%prior 10
Other (explain in narrative): Other11 (5.3%)↑10.0%prior 10
Followed too close8 (3.8%)→0.0%prior 8
Operating vehicle in an reckless, erratic, careless, negligent manner6 (2.9%)
Driver Distraction: Other interior distraction5 (2.4%)
FTYROW: From yield sign5 (2.4%)

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

Road & Environmental Conditions

Year-over-year, crash conditions remained broadly similar. Crashes on dry road surfaces were the most common in both periods, increasing slightly from 139 to 141. However, crashes on icy or frosty roads more than doubled, increasing from 5 incidents in 2020 to 13 in 2021. The proportion of crashes occurring in daylight was stable, accounting for 56.1% in 2020 and 56.0% in 2021.

Weather

Clear124 (68.5%)
↓-4.6%prior 130
Cloudy26 (14.4%)
↑18.2%prior 22
Rain9 (5.0%)
↓-10.0%prior 10
Snow8 (4.4%)
↓-38.5%prior 13
Freezing rain/drizzle5 (2.8%)
Fog, smoke, smog3 (1.7%)
Blowing Snow3 (1.7%)
Severe Winds2 (1.1%)
Other (explain in narrative)1 (0.6%)

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

Lighting

Daylight117 (63.9%)
↑6.4%prior 110
Dark - roadway not lighted41 (22.4%)
↓-2.4%prior 42
Dark - roadway lighted11 (6.0%)
→0.0%prior 11
Dusk8 (4.4%)
↑60.0%prior 5
Dawn6 (3.3%)
↓-40.0%prior 10

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

Road Surface

Dry141 (76.6%)
↑1.4%prior 139
Ice/frost13 (7.1%)
↑160.0%prior 5
Snow12 (6.5%)
↓-20.0%prior 15
Wet12 (6.5%)
↑9.1%prior 11
Gravel5 (2.7%)
↓-37.5%prior 8
Slush1 (0.5%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved makes in crashes during both periods, though Ford's involvement decreased from 48 vehicles in 2020 to 42 in 2021. Among persons involved in crashes, the 16-20 age group saw a notable increase in representation, growing from 44 individuals in 2020 to 61 in 2021. The total number of persons involved in crashes decreased from 421 to 379.

Top Vehicle Makes (294 vehicles)

1
FORD42 (14.3%)
↓-12.5%prior 48
2
CHEVROLET26 (8.8%)
↑62.5%prior 16
3
CHEV22 (7.5%)
↓-18.5%prior 27
4
DODGE14 (4.8%)
↑40.0%prior 10
5
JEEP11 (3.7%)
→0.0%prior 11
6
DODG10 (3.4%)
↑11.1%prior 9
7
TOYOTA10 (3.4%)
↓-37.5%prior 16
8
NISSAN8 (2.7%)
→0.0%prior 8
9
CHRYSLER8 (2.7%)
10
TOYT7 (2.4%)

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

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

Sex Distribution (234 persons with recorded sex)

Male153 (65.4%)
↓-2.5%prior 157
Female81 (34.6%)
↓-14.7%prior 95

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: 209
  • Total persons involved: 379
  • Total vehicles involved: 294

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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