Yearly Traffic Safety Analysis

226 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Mills County recorded 226 total crashes, a 3.2% increase from the 219 crashes reported in 2023. While overall crash volume saw a slight rise, the most significant change was in crash severity, with total fatalities increasing from one in the prior year to three in the current period.

226

▲ 3.2%was 219

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

83

▲ 9.2%was 76

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Mills County show a slight increase year-over-year. The total number of crashes rose from 219 in 2023 to 226 in 2024. This was accompanied by an increase in both injuries, which went from 76 to 83, and fatalities, which rose from one to three.

Vulnerable Road User Casualties

3

Motorists Killed

Prior: 1↑200.0%

83

Motorists Injured

Prior: 75↑10.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns show that Friday remained the peak day for crashes in both 2023 (38 crashes) and 2024 (65 crashes), with a substantial increase in volume on that day in the current period. The afternoon commute hours were prominent in both years; while 5 PM was a peak hour in both periods, 2024 also saw a significant peak at 3 PM with 22 crashes, compared to 14 in the prior year. Crashes on weekends (Saturday and Sunday) decreased from a combined 62 in 2023 to 43 in 2024.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2024, with fatal crashes increasing from one to three, raising the fatal crash rate from 0.46% to 1.33%. The proportion of serious injury crashes decreased from 5.9% (13 crashes) in 2023 to 2.7% (6 crashes) in 2024. Conversely, minor injury crashes saw an increase in their share, rising from 14.2% (31 crashes) to 17.3% (39 crashes). The percentage of crashes resulting in no injury remained relatively stable at approximately 70% for both periods.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.3%
↑200.0%prior 1
Serious Injury6serious injury crashes2.7%
↓-53.8%prior 13
Minor Injury39minor injury crashes17.3%
↑25.8%prior 31
Possible Injury19possible injury crashes8.4%
↓-13.6%prior 22
No Injury159no injury crashes70.4%
↑4.6%prior 152

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an 'Animal' remained a leading contributing factor in both periods, though the count decreased from 39 in 2023 to 33 in 2024. 'Ran off road - straight' incidents doubled in count, increasing from 10 to 20, making it the second-most cited factor in the current year. Conversely, crashes attributed to 'Lost Control' fell from 24 to 16, and those involving 'Failure to yield from a stop sign' decreased from 16 to 10. 'Driving too fast for conditions' saw a notable increase from 10 to 17 incidents year-over-year.

Officer-Reported Primary Contributing Cause

Animal33 (14.6%)↓-15.4%prior 39
Ran off road - straight20 (8.8%)↑100.0%prior 10
Driving too fast for conditions17 (7.5%)↑70.0%prior 10
Other (explain in narrative): Other17 (7.5%)↑88.9%prior 9
Lost Control16 (7.1%)↓-33.3%prior 24
Ran off road - left15 (6.6%)↑7.1%prior 14
FTYROW: From stop sign10 (4.4%)↓-37.5%prior 16
Ran Stop Sign7 (3.1%)
Driver Distraction: Other interior distraction7 (3.1%)→0.0%prior 7
Driver Distraction: Exterior distraction4 (1.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both 2024 and 2023 occurred in clear weather and on dry roads. However, there was a notable increase in crashes on adverse road surfaces, which rose from 34 incidents in 2023 to 50 in 2024, primarily driven by an increase in crashes on icy or frosty roads (from 3 to 21). Crashes during adverse weather conditions also increased from 22 to 30 year-over-year. The proportion of crashes occurring in daylight versus dark conditions remained relatively consistent across both periods.

Weather

Clear157 (77.7%)
↑6.8%prior 147
Freezing rain/drizzle12 (5.9%)
Cloudy10 (5.0%)
↓-41.2%prior 17
Rain7 (3.5%)
↑16.7%prior 6
Snow5 (2.5%)
↓-54.5%prior 11
Fog, smoke, smog4 (2.0%)
Blowing Snow3 (1.5%)
Other (explain in narrative)1 (0.5%)
Severe Winds1 (0.5%)
Sleet, hail1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight131 (63.3%)
↑5.6%prior 124
Dark - roadway not lighted41 (19.8%)
↑5.1%prior 39
Dark - roadway lighted13 (6.3%)
↓-7.1%prior 14
Dusk10 (4.8%)
Dark - unknown roadway lighting8 (3.9%)
Dawn4 (1.9%)
↓-33.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry146 (72.3%)
↑5.0%prior 139
Ice/frost21 (10.4%)
Wet15 (7.4%)
↓-11.8%prior 17
Snow12 (5.9%)
↑9.1%prior 11
Gravel6 (3.0%)
↓-53.8%prior 13
Slush2 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent year-over-year, with Ford (69 vehicles in 2024 vs. 67 in 2023) and Chevrolet (combined 45 vehicles in 2024 vs. 46 in 2023) being the most common. An analysis of persons involved shows a decrease in the number of individuals in the 16-20 age group, from 63 in 2023 to 50 in 2024. Similarly, the 35-44 age group saw a decrease from 75 persons involved to 59.

Top Vehicle Makes (344 vehicles)

1
FORD69 (20.1%)
↑3.0%prior 67
2
CHEV29 (8.4%)
↑16.0%prior 25
3
JEEP22 (6.4%)
↑15.8%prior 19
4
CHEVROLET16 (4.7%)
↓-23.8%prior 21
5
TOYT13 (3.8%)
↑30.0%prior 10
6
GMC12 (3.5%)
→0.0%prior 12
7
HOND11 (3.2%)
↑83.3%prior 6
8
KIA11 (3.2%)
↑83.3%prior 6
9
HONDA11 (3.2%)
↑57.1%prior 7
10
DODGE10 (2.9%)
↑66.7%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (209 persons with recorded sex)

Male117 (56.0%)
↓-40.0%prior 195
Female92 (44.0%)
↓-11.5%prior 104

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 226
  • Total persons involved: 361
  • Total vehicles involved: 344

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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