Yearly Traffic Safety Analysis

759 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Des Moines County recorded 759 total traffic crashes, a 7.7% decrease from the 822 crashes in 2022. This period also saw a significant reduction in traffic fatalities, which fell from four in 2022 to one in 2023. While overall crashes and fatalities declined, the distribution of crash severity and contributing factors saw notable shifts.

759

▼ -7.7%was 822

Total Crash Events

1

▼ -75.0%was 4

Persons Killed

167

▼ -12.1%was 190

Persons Injured

1

▼ -75.0%was 4

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

The overall trend in traffic safety for Des Moines County showed improvement year-over-year. Total crashes fell by 7.7% from 822 to 759. Similarly, the number of people injured decreased by 12.1% from 190 to 167, and fatalities saw a substantial 75% drop from four to one.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 3↓-66.7%

5

Pedestrians Injured

Prior: 4↑25.0%

3

Cyclists Injured

Prior: 4↓-25.0%

159

Motorists Injured

Prior: 180↓-11.7%

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 some year-over-year shifts. While Friday remained the peak day for crashes in both 2023 (131 crashes) and 2022 (138 crashes), the peak hour shifted from 3 PM in 2022 (73 crashes) to 5 PM in 2023 (69 crashes). Overall, crashes decreased on all days of the week except for Tuesday, which saw an increase from 103 to 114 incidents.

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 distribution changed between the two periods. The number of fatal crashes dropped from four in 2022 to one in 2023. However, crashes resulting in serious injuries increased from 10 to 16, and minor injury crashes rose from 56 to 62. Conversely, crashes involving possible injuries saw a significant decline from 129 in 2022 to 87 in 2023.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.1%
↓-75.0%prior 4
Serious Injury16serious injury crashes2.1%
↑60.0%prior 10
Minor Injury62minor injury crashes8.2%
↑10.7%prior 56
Possible Injury87possible injury crashes11.5%
↓-32.6%prior 129
No Injury593no injury crashes78.1%
↓-4.8%prior 623

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 factors for crashes showed some changes year-over-year. Collisions involving animals remained the top factor, increasing from 143 incidents in 2022 to 152 in 2023. Crashes attributed to 'Followed too close' decreased from 61 to 46, while 'Driver Distraction: Other interior distraction' increased from 54 to 61. 'FTYROW: From stop sign' was a factor in exactly 40 crashes in both years.

Officer-Reported Primary Contributing Cause

Animal152 (20%)↑6.3%prior 143
Driver Distraction: Other interior distraction61 (8%)↑13.0%prior 54
Other (explain in narrative): Other52 (6.9%)↓-40.9%prior 88
Followed too close46 (6.1%)↓-24.6%prior 61
FTYROW: From stop sign40 (5.3%)→0.0%prior 40
Ran off road - left33 (4.3%)↓-25.0%prior 44
FTYROW: Making left turn24 (3.2%)↓-11.1%prior 27
Ran Stop Sign22 (2.9%)↓-15.4%prior 26
Driving too fast for conditions21 (2.8%)↓-27.6%prior 29
Lost Control21 (2.8%)↓-40.0%prior 35

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

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. The proportion of crashes on dry road surfaces increased from 60.9% (501 of 822 crashes) in 2022 to 68.6% (521 of 759 crashes) in 2023. This corresponds with a sharp decrease in crashes happening in adverse winter weather, with incidents on snowy roads dropping from 53 to 15 and on icy roads from 29 to 15.

Weather

Clear484 (77.6%)
↓-2.6%prior 497
Cloudy71 (11.4%)
↓-14.5%prior 83
Rain31 (5.0%)
↓-29.5%prior 44
Snow19 (3.0%)
↓-52.5%prior 40
Freezing rain/drizzle9 (1.4%)
↓-35.7%prior 14
Sleet, hail3 (0.5%)
Fog, smoke, smog3 (0.5%)
Blowing Snow2 (0.3%)
Severe Winds1 (0.2%)
Other (explain in narrative)1 (0.2%)

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

Lighting

Daylight450 (71.9%)
↓-5.7%prior 477
Dark - roadway lighted107 (17.1%)
↓-18.3%prior 131
Dark - roadway not lighted45 (7.2%)
↓-2.2%prior 46
Dusk17 (2.7%)
↓-29.2%prior 24
Dawn6 (1.0%)
↑20.0%prior 5
Dark - unknown roadway lighting1 (0.2%)
↓-85.7%prior 7

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

Road Surface

Dry521 (83.2%)
↑4.0%prior 501
Wet55 (8.8%)
↓-29.5%prior 78
Ice/frost15 (2.4%)
↓-48.3%prior 29
Snow15 (2.4%)
↓-71.7%prior 53
Gravel13 (2.1%)
↓-18.8%prior 16
Slush6 (1.0%)
↓-25.0%prior 8
Other (explain in narrative)1 (0.2%)

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 remained consistent, with Ford (212) and Chevrolet (173 as 'Chev') leading in 2023, similar to 2022 (234 and 158, respectively). Analysis of person demographics shows a shift in age group involvement; the share of persons aged 55-64 involved in crashes increased from 9.6% of the total in 2022 (181 of 1894 persons) to 12.8% in 2023 (220 of 1721 persons).

Top Vehicle Makes (1,261 vehicles)

1
FORD212 (16.8%)
↓-9.4%prior 234
2
CHEV173 (13.7%)
↑9.5%prior 158
3
DODG71 (5.6%)
↓-15.5%prior 84
4
KIA63 (5%)
↓-17.1%prior 76
5
NR57 (4.5%)
↓-1.7%prior 58
6
CHEVROLET53 (4.2%)
↓-31.2%prior 77
7
HOND45 (3.6%)
↑18.4%prior 38
8
JEEP42 (3.3%)
↓-25.0%prior 56
9
TOYO42 (3.3%)
↓-30.0%prior 60
10
NISS41 (3.3%)
↑20.6%prior 34

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

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

Sex Distribution (1,051 persons with recorded sex)

Male589 (56.0%)
↓-3.1%prior 608
Female462 (44.0%)
↓-14.9%prior 543

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: 759
  • Total persons involved: 1,721
  • Total vehicles involved: 1,261

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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