Yearly Traffic Safety Analysis

388 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Bremer County recorded 388 total crashes, an increase of 4.9% from the 370 crashes reported in 2022. While overall crashes increased, the number of fatalities decreased from three in the prior year to one in 2023. The most notable shift was a significant increase in the number of serious injury crashes, which rose from 5 in 2022 to 14 in 2023.

388

▲ 4.9%was 370

Total Crash Events

1

▼ -66.7%was 3

Persons Killed

79

▲ 9.7%was 72

Persons Injured

1

▼ -66.7%was 3

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Bremer County trended slightly upward, increasing by 18 incidents from 370 in 2022 to 388 in 2023, a 4.9% rise. The number of people injured also increased from 72 to 79. In contrast, the number of fatalities saw a notable decrease from three to one during the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

1

Pedestrians Injured

Prior: 1→0.0%

2

Cyclists Injured

Prior: 1↑100.0%

76

Motorists Injured

Prior: 70↑8.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent, with Thursday being the peak day for crashes in both 2023 (68 crashes) and 2022 (65 crashes). The peak hour for collisions shifted from 6 PM in 2022 (30 crashes) to a tie between 5 PM and 9 PM in 2023, with each hour recording 31 crashes. Weekdays continued to account for the majority of crash incidents in both periods.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes decreased from three in 2022 to one in 2023, with the fatal crash share dropping from 0.8% to 0.3% of all incidents. However, serious injury crashes increased significantly, rising from 5 incidents (a 1.4% share) in 2022 to 14 incidents (a 3.6% share) in 2023. Consequently, the proportion of crashes resulting in no injuries decreased slightly from 85.1% to 83.8% year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
↓-66.7%prior 3
Serious Injury14serious injury crashes3.6%
↑180.0%prior 5
Minor Injury24minor injury crashes6.2%
↓-20.0%prior 30
Possible Injury24possible injury crashes6.2%
↑41.2%prior 17
No Injury325no injury crashes83.8%
↑3.2%prior 315

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, with the count of such incidents increasing by 14.6% from 157 in 2022 to 180 in 2023. Crashes attributed to 'Driving too fast for conditions' decreased in count from 26 to 15. Conversely, incidents involving 'Failure to yield right of way from a stop sign' increased from 11 in 2022 to 18 in 2023.

Officer-Reported Primary Contributing Cause

Animal180 (46.4%)↑14.6%prior 157
Followed too close20 (5.2%)↓-13.0%prior 23
FTYROW: From stop sign18 (4.6%)↑63.6%prior 11
Ran off road - straight17 (4.4%)↑54.5%prior 11
Ran off road - left17 (4.4%)↑41.7%prior 12
Driving too fast for conditions15 (3.9%)↓-42.3%prior 26
Lost Control14 (3.6%)↓-17.6%prior 17
Driver Distraction: Other interior distraction12 (3.1%)↑140.0%prior 5
Other (explain in narrative): Other10 (2.6%)↑11.1%prior 9
FTYROW: Making left turn10 (2.6%)↓-9.1%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in 2023 occurred more frequently on dry roads (167 incidents) compared to 2022 (145 incidents), while crashes on snow-covered roads decreased from 26 to 10. Similarly, crashes during snowy weather conditions fell from 21 to 14 incidents. There was a notable increase in crashes occurring in dark, unlighted conditions, which rose from 32 incidents in 2022 to 48 in 2023.

Weather

Clear156 (68.4%)
↑8.3%prior 144
Cloudy41 (18.0%)
↑17.1%prior 35
Snow14 (6.1%)
↓-33.3%prior 21
Rain7 (3.1%)
↓-36.4%prior 11
Freezing rain/drizzle5 (2.2%)
Fog, smoke, smog5 (2.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight146 (62.4%)
↓-3.3%prior 151
Dark - roadway not lighted48 (20.5%)
↑50.0%prior 32
Dark - roadway lighted23 (9.8%)
↓-20.7%prior 29
Dusk7 (3.0%)
→0.0%prior 7
Dark - unknown roadway lighting6 (2.6%)
Dawn4 (1.7%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry167 (73.2%)
↑15.2%prior 145
Ice/frost22 (9.6%)
↓-8.3%prior 24
Wet17 (7.5%)
↓-19.0%prior 21
Snow10 (4.4%)
↓-61.5%prior 26
Gravel9 (3.9%)
Other (explain in narrative)2 (0.9%)
Slush1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Analysis of vehicles involved shows Chevrolet-branded vehicles (129 total) became the most frequent in 2023 crashes, surpassing Ford, which was the top make in 2022 (111 vehicles). Regarding the demographics of persons involved, the 45-54 age group saw the most significant change, with their involvement increasing from 92 individuals in 2022 to 124 in 2023. The number of individuals aged 16-20 involved in crashes also rose from 97 to 109.

Top Vehicle Makes (525 vehicles)

1
CHEV109 (20.8%)
↑17.2%prior 93
2
FORD89 (17%)
↓-19.8%prior 111
3
TOYT31 (5.9%)
↑14.8%prior 27
4
DODG20 (3.8%)
↓-37.5%prior 32
5
NISS20 (3.8%)
↑11.1%prior 18
6
CHEVROLET20 (3.8%)
↓-20.0%prior 25
7
HOND17 (3.2%)
↑21.4%prior 14
8
BUIC15 (2.9%)
↑15.4%prior 13
9
GMC15 (2.9%)
↓-25.0%prior 20
10
KIA14 (2.7%)
↑55.6%prior 9

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (508 persons with recorded sex)

Male307 (60.4%)
↑13.7%prior 270
Female201 (39.6%)
↓-7.8%prior 218

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 388
  • Total persons involved: 776
  • Total vehicles involved: 525

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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