Yearly Traffic Safety Analysis

1,958 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Black Hawk County recorded 1,958 total crashes, a slight decrease of approximately 1.0% from the 1,977 crashes in 2022. While the overall crash volume remained stable, the number of fatalities increased significantly, rising from 7 in 2022 to 13 in 2023. This represents an 85.7% increase in traffic-related deaths year-over-year.

1,958

▼ -1.0%was 1,977

Total Crash Events

13

▲ 85.7%was 7

Persons Killed

715

▲ 6.7%was 670

Persons Injured

12

▲ 140.0%was 5

Fatal Crash Events

Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) 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 traffic crashes in Black Hawk County remained relatively stable, decreasing by just 1.0% from 1,977 in 2022 to 1,958 in 2023. However, the severity of these crashes worsened, with total injuries rising by 6.7% from 670 to 715 and total fatalities increasing by 85.7% from 7 to 13.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 0→%

1

Cyclists Killed

Prior: 0→%

10

Motorists Killed

Prior: 7↑42.9%

0

Other Killed

Prior: 0→0.0%

18

Pedestrians Injured

Prior: 19↓-5.3%

11

Cyclists Injured

Prior: 14↓-21.4%

685

Motorists Injured

Prior: 635↑7.9%

1

Other Injured

Prior: 2↓-50.0%

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 in Black Hawk County showed consistency year-over-year. Friday remained the peak day for crashes in both 2023 (337 crashes) and 2022 (351 crashes). Similarly, the 3 PM hour was the peak hour in both periods, with 166 crashes in 2023 and 192 in 2022. The overall daily and hourly distributions of crashes did not experience a significant shift between the two years.

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

Crash severity worsened in 2023 compared to 2022, driven by a sharp rise in fatal incidents. The number of fatal crashes increased from 5 to 12, and the fatality rate per 100 crashes rose from 0.25 to 0.61. While fatal crashes increased, serious injury crashes decreased from 49 to 38. The proportion of crashes resulting in minor or possible injury remained stable, accounting for 26.9% of crashes in 2023 versus 26.7% in 2022.

Severity is per crash event (most severe injury). 12 fatal crash events resulted in 13 persons killed.

Outcome by Severity (Crash Events)

Fatal12fatal crashes0.6%
↑140.0%prior 5
Serious Injury38serious injury crashes1.9%
↓-22.4%prior 49
Minor Injury192minor injury crashes9.8%
↑3.8%prior 185
Possible Injury335possible injury crashes17.1%
↓-2.3%prior 343
No Injury1,381no injury crashes70.5%
↓-1.0%prior 1,395

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 became the leading contributing factor in 2023, with the count increasing by 22.2% from 171 to 209 incidents. Failure to yield from a stop sign also saw a significant increase, rising 25.2% in count from 115 to 144 crashes. Crashes attributed to running a traffic signal grew by 30.6% from 85 to 111. Conversely, crashes where a driver ran a stop sign decreased in count by 30.5% from 131 to 91.

Officer-Reported Primary Contributing Cause

Animal209 (10.7%)↑22.2%prior 171
Other (explain in narrative): Other172 (8.8%)↓-23.2%prior 224
FTYROW: From stop sign144 (7.4%)↑25.2%prior 115
Followed too close141 (7.2%)↓-0.7%prior 142
Ran Traffic Signal111 (5.7%)↑30.6%prior 85
Ran off road - left96 (4.9%)→0.0%prior 96
Ran Stop Sign91 (4.6%)↓-30.5%prior 131
Driver Distraction: Other interior distraction90 (4.6%)↑8.4%prior 83
FTYROW: Making left turn85 (4.3%)↓-21.3%prior 108
Driving too fast for conditions73 (3.7%)↓-23.2%prior 95

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

Road & Environmental Conditions

The proportion of crashes occurring in adverse conditions decreased in 2023. Crashes on wet, snowy, icy, or slushy roads dropped from 23.5% of all crashes in 2022 to 16.7% in 2023. Similarly, crashes in non-clear weather conditions declined from 34.8% to 30.8% of the total. There was a slight proportional increase in crashes occurring in dark conditions, which accounted for 26.2% of incidents in 2023 compared to 23.9% in 2022.

Weather

Clear1,355 (75.9%)
↑5.1%prior 1,289
Cloudy227 (12.7%)
↓-8.1%prior 247
Snow85 (4.8%)
↓-30.3%prior 122
Rain77 (4.3%)
↓-23.8%prior 101
Freezing rain/drizzle19 (1.1%)
↓-9.5%prior 21
Fog, smoke, smog11 (0.6%)
Blowing Snow8 (0.4%)
↓-74.2%prior 31
Other (explain in narrative)3 (0.2%)
↓-40.0%prior 5
Sleet, hail1 (0.1%)

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

Lighting

Daylight1,193 (66.8%)
↓-6.6%prior 1,277
Dark - roadway lighted339 (19.0%)
↑5.3%prior 322
Dark - roadway not lighted158 (8.9%)
↑16.2%prior 136
Dusk42 (2.4%)
↓-16.0%prior 50
Dawn37 (2.1%)
↑12.1%prior 33
Dark - unknown roadway lighting16 (0.9%)
↑6.7%prior 15

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

Road Surface

Dry1,443 (80.8%)
↑6.7%prior 1,352
Wet163 (9.1%)
↓-18.9%prior 201
Snow84 (4.7%)
↓-40.4%prior 141
Ice/frost68 (3.8%)
↓-39.8%prior 113
Gravel15 (0.8%)
↓-6.3%prior 16
Slush12 (0.7%)
↑20.0%prior 10
Sand1 (0.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes showed little change, with Ford, Chevrolet, and Toyota remaining the top three most common makes in both periods. However, the age distribution of persons involved in crashes shifted. The number of individuals aged 21-25 involved in crashes increased by 21.0%, from 458 to 554. The 65 and older age group also saw a 6.7% increase in involvement, while the 26-34 age group saw a 5.8% decrease.

Top Vehicle Makes (3,502 vehicles)

1
FORD588 (16.8%)
↑1.7%prior 578
2
CHEV513 (14.6%)
↓-1.5%prior 521
3
TOYT224 (6.4%)
↑3.2%prior 217
4
CHEVROLET162 (4.6%)
↑4.5%prior 155
5
JEEP122 (3.5%)
↑2.5%prior 119
6
DODG121 (3.5%)
↓-13.6%prior 140
7
HOND120 (3.4%)
↓-13.0%prior 138
8
NISS117 (3.3%)
↓-7.9%prior 127
9
GMC112 (3.2%)
↑47.4%prior 76
10
KIA99 (2.8%)
↑2.1%prior 97

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

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

Sex Distribution (3,149 persons with recorded sex)

Male1,707 (54.2%)
↓-1.6%prior 1,734
Female1,442 (45.8%)
↑2.1%prior 1,412

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: 1,958
  • Total persons involved: 4,628
  • Total vehicles involved: 3,502

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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