Yearly Traffic Safety Analysis

368 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Bremer County, total traffic crashes decreased by 5.2%, from 388 incidents in 2023 to 368 in 2024. This period also saw total injuries fall from 79 to 72. The most significant year-over-year change was the reduction in traffic fatalities from one in the prior period to zero in the current period.

368

▼ -5.2%was 388

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

72

▼ -8.9%was 79

Persons Injured

0

▼ -100.0%was 1

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Bremer County show a modest improvement year-over-year. The total number of crashes declined by 20 incidents, representing a 5.2% decrease from 2023 to 2024. This downward trend was also reflected in crash outcomes, with total injuries falling by 8.9% and fatalities dropping from one to zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

72

Motorists Injured

Prior: 76↓-5.3%

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

The temporal patterns of crashes showed a shift between the two periods. The peak day for collisions moved from Thursday (68 crashes) in 2023 to Friday (67 crashes) in 2024. More notably, the peak hour for crashes shifted significantly earlier, from the 9 p.m. hour in the prior period (31 crashes) to the 5 p.m. hour in the current period (34 crashes).

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 decreased notably from the prior year. Fatal crashes were eliminated, dropping from one incident in 2023 to zero in 2024. The count of serious injury crashes also fell by more than half, from 14 in the prior period to 6 in the current period. Consequently, the proportion of crashes resulting in no injuries increased from 83.8% to 85.9% year-over-year.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes1.6%
↓-57.1%prior 14
Minor Injury23minor injury crashes6.3%
↓-4.2%prior 24
Possible Injury23possible injury crashes6.3%
↓-4.2%prior 24
No Injury316no injury crashes85.9%
↓-2.8%prior 325

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 with animals remained the top contributing factor in both periods, with a slight decrease from 180 crashes in 2023 to 177 in 2024. 'Followed too close' was the second-ranked factor in both years with 20 incidents each. 'Driving too fast for conditions' saw a 26.7% increase in count, rising from 15 to 19 incidents, while crashes attributed to 'Failure to Yield Right of Way from a stop sign' decreased from 18 to 11.

Officer-Reported Primary Contributing Cause

Animal177 (48.1%)↓-1.7%prior 180
Followed too close20 (5.4%)→0.0%prior 20
Driving too fast for conditions19 (5.2%)↑26.7%prior 15
FTYROW: Making left turn18 (4.9%)↑80.0%prior 10
Other (explain in narrative): Other15 (4.1%)↑50.0%prior 10
Ran off road - left14 (3.8%)↓-17.6%prior 17
FTYROW: From stop sign11 (3%)↓-38.9%prior 18
Driver Distraction: Other interior distraction9 (2.4%)↓-25.0%prior 12
Driver Distraction: Inattentive/lost in thought8 (2.2%)↑60.0%prior 5
Ran Stop Sign8 (2.2%)↓-20.0%prior 10

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

Road & Environmental Conditions

Year-over-year data shows a reduction in crashes occurring under adverse conditions. Crashes on roads with ice or frost dropped from 22 incidents in 2023 to 9 in 2024. Similarly, collisions in dark, unlighted conditions were halved, decreasing from 48 to 24. Crashes in daylight and on dry roads remained the most common scenarios in both periods, though their counts also saw a slight decrease.

Weather

Clear144 (70.9%)
↓-7.7%prior 156
Cloudy33 (16.3%)
↓-19.5%prior 41
Snow11 (5.4%)
↓-21.4%prior 14
Rain6 (3.0%)
↓-14.3%prior 7
Blowing Snow3 (1.5%)
Fog, smoke, smog3 (1.5%)
↓-40.0%prior 5
Freezing rain/drizzle2 (1.0%)
↓-60.0%prior 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

Daylight156 (74.6%)
↑6.8%prior 146
Dark - roadway not lighted24 (11.5%)
↓-50.0%prior 48
Dark - roadway lighted14 (6.7%)
↓-39.1%prior 23
Dawn6 (2.9%)
Dusk5 (2.4%)
↓-28.6%prior 7
Dark - unknown roadway lighting4 (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

Dry148 (72.9%)
↓-11.4%prior 167
Wet15 (7.4%)
↓-11.8%prior 17
Snow13 (6.4%)
↑30.0%prior 10
Gravel13 (6.4%)
↑44.4%prior 9
Ice/frost9 (4.4%)
↓-59.1%prior 22
Slush5 (2.5%)

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

Vehicles & Demographics

Comparing vehicles involved, Chevrolet (102), Ford (87), and Toyota (52) were the top three makes in 2024, maintaining their rankings from the prior year despite a decrease in total crashes for Chevrolet (from 129) and Ford (from 89). The age distribution of persons involved in crashes also shifted; while the total number of people involved decreased from 776 to 535, the 35-44 age group became the most frequently involved group in 2024 with 85 individuals, replacing the 45-54 age group which led in 2023 with 124 individuals.

Top Vehicle Makes (517 vehicles)

1
FORD87 (16.8%)
↓-2.2%prior 89
2
CHEV80 (15.5%)
↓-26.6%prior 109
3
TOYT43 (8.3%)
↑38.7%prior 31
4
NISS25 (4.8%)
↑25.0%prior 20
5
DODG24 (4.6%)
↑20.0%prior 20
6
CHEVROLET22 (4.3%)
↑10.0%prior 20
7
JEEP20 (3.9%)
↑66.7%prior 12
8
CHRY20 (3.9%)
↑42.9%prior 14
9
BUIC19 (3.7%)
↑26.7%prior 15
10
GMC17 (3.3%)
↑13.3%prior 15

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

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

Sex Distribution (257 persons with recorded sex)

Male141 (54.9%)
↓-54.1%prior 307
Female116 (45.1%)
↓-42.3%prior 201

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: 368
  • Total persons involved: 535
  • Total vehicles involved: 517

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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