Yearly Traffic Safety Analysis

98 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Shelby County recorded 98 total traffic crashes, an increase from the 85 crashes reported in 2022, representing a 15.3% rise. While total crashes and the number of people injured increased, fatalities decreased from two in 2022 to one in 2023. The most notable year-over-year shift was the overall increase in crash volume.

98

▲ 15.3%was 85

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

33

▲ 17.9%was 28

Persons Injured

1

▼ -50.0%was 2

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, traffic crashes in Shelby County trended upward from 2022 to 2023. The total number of crashes increased by 15.3%, rising from 85 to 98. Similarly, the number of people injured in these incidents grew by 17.9% from 28 to 33, while total fatalities decreased from two to one.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

2

Pedestrians Injured

Prior: 0→%

31

Motorists Injured

Prior: 28↑10.7%

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 shifts between the two periods. While Friday remained the peak day for crashes in both 2022 (15 crashes) and 2023 (22 crashes), Wednesday saw a significant increase in incidents, rising from 8 to 20. The peak hour for crashes shifted from 4 p.m. in 2022 (7 crashes) to 3 p.m. in 2023, with a higher concentration of 12 crashes during that hour.

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 profile of crashes changed between the two periods. The fatal crash rate decreased from 2.35% in 2022 to 1.02% in 2023, with one fatal crash out of 98 total incidents. However, the proportion of crashes resulting in an injury of any kind (serious, minor, or possible) increased, accounting for 29.6% of all incidents in 2023 compared to 24.7% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
↓-50.0%prior 2
Serious Injury3serious injury crashes3.1%
↑200.0%prior 1
Minor Injury14minor injury crashes14.3%
↑27.3%prior 11
Possible Injury12possible injury crashes12.2%
↑33.3%prior 9
No Injury68no injury crashes69.4%
↑9.7%prior 62

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 shifted between 2022 and 2023. While collisions involving an 'Animal' remained a primary cause, the count of such incidents decreased from 23 to 19. In contrast, crashes attributed to 'Followed too close' increased significantly in count from 2 to 8, and incidents involving 'Lost Control' doubled from 4 to 8.

Officer-Reported Primary Contributing Cause

Animal19 (19.4%)↓-17.4%prior 23
Lost Control8 (8.2%)
Followed too close8 (8.2%)
Driving too fast for conditions7 (7.1%)
FTYROW: From stop sign5 (5.1%)↓-16.7%prior 6
Driver Distraction: Other interior distraction4 (4.1%)
Ran Stop Sign4 (4.1%)
Other (explain in narrative): Other4 (4.1%)↓-33.3%prior 6
Failed to keep in proper lane3 (3.1%)
FTYROW: Making left turn3 (3.1%)

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

Road & Environmental Conditions

In 2023, a larger proportion of crashes occurred under favorable conditions compared to the previous year. Crashes in 'Clear' weather constituted 69.4% of the total, up from a 56.5% share in 2022. Similarly, the share of incidents on 'Dry' road surfaces increased from 57.6% to 64.3%, and crashes during 'Daylight' hours rose from 51.8% to 60.2% of all crashes.

Weather

Clear68 (80.0%)
↑41.7%prior 48
Cloudy10 (11.8%)
↑100.0%prior 5
Rain3 (3.5%)
Snow2 (2.4%)
Freezing rain/drizzle1 (1.2%)
Other (explain in narrative)1 (1.2%)

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

Lighting

Daylight59 (69.4%)
↑34.1%prior 44
Dark - roadway not lighted12 (14.1%)
↑33.3%prior 9
Dark - roadway lighted6 (7.1%)
↑20.0%prior 5
Dawn4 (4.7%)
Dusk4 (4.7%)

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

Road Surface

Dry63 (75.0%)
↑28.6%prior 49
Wet8 (9.5%)
→0.0%prior 8
Ice/frost5 (6.0%)
Gravel4 (4.8%)
Snow3 (3.6%)
Mud, dirt1 (1.2%)

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 (33 vehicles) and Chevrolet (32 vehicles, combining 'CHEV' and 'CHEVROLET' entries) leading in 2023, similar to their top rankings in 2022. An analysis of persons involved in crashes shows a notable demographic shift; the 55-64 age group saw its involvement increase from 21 individuals in 2022 to 35 in 2023, becoming the most represented age group. In contrast, the number of persons involved from the 16-20 and 65+ age groups saw a slight decrease.

Top Vehicle Makes (147 vehicles)

1
FORD33 (22.4%)
↑22.2%prior 27
2
CHEV25 (17%)
↑13.6%prior 22
3
CHEVROLET7 (4.8%)
→0.0%prior 7
4
NISS7 (4.8%)
5
TOYT6 (4.1%)
↑20.0%prior 5
6
JEEP5 (3.4%)
↓-16.7%prior 6
7
GMC5 (3.4%)
8
HYUN5 (3.4%)
9
BUIC5 (3.4%)
10
KIA5 (3.4%)

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

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

Sex Distribution (138 persons with recorded sex)

Male78 (56.5%)
↑8.3%prior 72
Female60 (43.5%)
↑22.4%prior 49

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: 98
  • Total persons involved: 205
  • Total vehicles involved: 147

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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