Yearly Traffic Safety Analysis

1,923 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Dubuque County, total traffic crashes decreased by 1.8% from 1,959 in 2022 to 1,923 in 2023. While the overall crash volume remained relatively stable, the most significant year-over-year change was a 66.7% reduction in fatalities, which fell from 12 in the prior period to 4 in the current period. Conversely, the total number of injuries saw a slight increase of 3.3%, rising from 552 to 570.

1,923

▼ -1.8%was 1,959

Total Crash Events

4

▼ -66.7%was 12

Persons Killed

570

▲ 3.3%was 552

Persons Injured

4

▼ -55.6%was 9

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

The overall trend in traffic crashes shows a slight decline year-over-year, with 36 fewer incidents in 2023 compared to 2022. This represents a 1.8% decrease in total crash volume. Despite the drop in total crashes, the number of people injured increased slightly from 552 to 570, while fatalities decreased substantially from 12 to 4.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 11↓-72.7%

0

Other Killed

Prior: 0→0.0%

13

Pedestrians Injured

Prior: 20↓-35.0%

13

Cyclists Injured

Prior: 11↑18.2%

542

Motorists Injured

Prior: 520↑4.2%

2

Other Injured

Prior: 1↑100.0%

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 showed a shift in the peak day of the week, moving from Friday (358 crashes) in 2022 to Thursday (318 crashes) in 2023. The peak hour for collisions remained consistent at 3 p.m. in both periods, though the number of crashes during this hour increased from 160 to 174. Crash volumes during the morning commute, specifically the 7 a.m. hour, saw a notable decrease from 124 incidents in 2022 to 88 in 2023.

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 severity of crashes shifted year-over-year, with a notable decrease in fatal incidents from 9 in 2022 to 4 in 2023, reducing their share of total crashes from 0.5% to 0.2%. The count of serious injury crashes remained unchanged at 24 for both periods. There was a slight decrease in minor injury crashes (from 164 to 155), while possible injury crashes increased from 286 to 291. The proportion of crashes resulting in no injury remained stable at approximately 75% for both years.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.2%
↓-55.6%prior 9
Serious Injury24serious injury crashes1.2%
→0.0%prior 24
Minor Injury155minor injury crashes8.1%
↓-5.5%prior 164
Possible Injury291possible injury crashes15.1%
↑1.7%prior 286
No Injury1,449no injury crashes75.4%
↓-1.8%prior 1,476

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

The leading contributing factor in both periods was a vehicle running off the road to the left, though the count of these incidents decreased from 461 in 2022 to 392 in 2023. Collisions involving animals became more frequent, increasing from 218 to 265 incidents and moving from the second to the second-ranked factor. Crashes attributed to running a stop sign increased from 93 to 122, entering the top three factors in 2023. Conversely, incidents involving failure to yield the right-of-way from a stop sign decreased from 99 to 61.

Officer-Reported Primary Contributing Cause

Ran off road - left392 (20.4%)↓-15.0%prior 461
Animal265 (13.8%)↑21.6%prior 218
Ran Stop Sign122 (6.3%)↑31.2%prior 93
Ran Traffic Signal110 (5.7%)↓-7.6%prior 119
Lost Control100 (5.2%)↑9.9%prior 91
Followed too close74 (3.8%)↓-22.9%prior 96
Other (explain in narrative): No improper action69 (3.6%)↑27.8%prior 54
FTYROW: Making left turn64 (3.3%)↓-17.9%prior 78
FTYROW: From stop sign61 (3.2%)↓-38.4%prior 99
Driver Distraction: Other interior distraction61 (3.2%)↑38.6%prior 44

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 occurred under similar conditions year-over-year, with dry roads and clear weather being the most common circumstances in both periods. However, there was a notable decrease in crashes occurring in rainy conditions, which fell from 118 incidents in 2022 to 71 in 2023. Correspondingly, crashes on wet road surfaces declined from 213 to 174. Incidents in snowy weather saw a slight increase from 102 to 117.

Weather

Clear1,089 (64.9%)
↓-6.8%prior 1,168
Cloudy346 (20.6%)
↑4.8%prior 330
Snow117 (7.0%)
↑14.7%prior 102
Rain71 (4.2%)
↓-39.8%prior 118
Fog, smoke, smog19 (1.1%)
Freezing rain/drizzle17 (1.0%)
↓-39.3%prior 28
Blowing Snow14 (0.8%)
↑27.3%prior 11
Sleet, hail2 (0.1%)
Other (explain in narrative)2 (0.1%)
Severe Winds1 (0.1%)
↓-87.5%prior 8

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

Lighting

Daylight1,200 (71.1%)
↓-3.5%prior 1,243
Dark - roadway lighted277 (16.4%)
↓-17.1%prior 334
Dark - roadway not lighted140 (8.3%)
↑5.3%prior 133
Dusk40 (2.4%)
↓-11.1%prior 45
Dawn19 (1.1%)
↑46.2%prior 13
Dark - unknown roadway lighting11 (0.7%)

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

Road Surface

Dry1,331 (79.3%)
↓-1.8%prior 1,356
Wet174 (10.4%)
↓-18.3%prior 213
Snow114 (6.8%)
↓-5.0%prior 120
Ice/frost41 (2.4%)
↓-26.8%prior 56
Slush8 (0.5%)
↓-57.9%prior 19
Gravel7 (0.4%)
→0.0%prior 7
Other (explain in narrative)2 (0.1%)
Mud, dirt1 (0.1%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, including Chevrolet and Ford, remained consistent across both years, with most seeing a slight decrease in counts that mirrors the overall trend. Analysis of persons involved shows a demographic shift, with fewer individuals in the 16-34 age groups involved in crashes in 2023 compared to 2022. Conversely, the number of people in the 65+ age group involved in crashes increased from 558 to 608, and the 45-54 age group saw an increase from 434 to 480.

Top Vehicle Makes (3,331 vehicles)

1
CHEV457 (13.7%)
↓-8.0%prior 497
2
FORD453 (13.6%)
↓-6.0%prior 482
3
TOYT201 (6%)
↑11.7%prior 180
4
CHEVROLET194 (5.8%)
↓-17.4%prior 235
5
JEEP175 (5.3%)
↓-3.3%prior 181
6
HOND164 (4.9%)
↑7.9%prior 152
7
GMC122 (3.7%)
↓-10.3%prior 136
8
NISS115 (3.5%)
↑55.4%prior 74
9
DODG103 (3.1%)
↓-15.6%prior 122
10
KIA103 (3.1%)
↓-25.4%prior 138

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

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

Sex Distribution (2,997 persons with recorded sex)

Male1,668 (55.7%)
↓-5.2%prior 1,759
Female1,329 (44.3%)
↓-1.7%prior 1,352

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: 1,923
  • Total persons involved: 4,400
  • Total vehicles involved: 3,331

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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