Yearly Traffic Safety Analysis

98 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, IDA County recorded 98 total crashes, a decrease from 111 crashes in 2022, representing an 11.7% year-over-year decline. This downturn was accompanied by a reduction in both fatalities, from 3 to 2, and total injuries, from 29 to 27. One of the most notable shifts was a sharp decrease in crashes attributed to 'Driving too fast for conditions,' which fell from 8 incidents in 2022 to 2 in 2023.

98

▼ -11.7%was 111

Total Crash Events

2

▼ -33.3%was 3

Persons Killed

27

▼ -6.9%was 29

Persons Injured

2

▼ -33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 safety metrics in IDA County showed improvement in 2023 compared to the prior year. Total crashes fell by 11.7%, from 111 to 98. This downward trend extended to severe outcomes, with total fatalities decreasing from 3 to 2 and the number of people injured declining from 29 to 27.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 3↓-33.3%

27

Motorists Injured

Prior: 29↓-6.9%

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 shifted slightly year-over-year. The peak day for collisions moved from Thursday in 2022 (23 crashes) to Wednesday in 2023 (22 crashes). The peak hour also changed, shifting from 1 p.m. in the prior year (9 crashes) to the 4 p.m. hour in the current year (10 crashes).

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 outcomes improved in 2023. The fatal crash rate declined from 2.7% of all crashes in 2022 to 2.0% in 2023. The proportion of crashes resulting in any injury also decreased, with serious injury crashes falling from 4 to 2 and minor injury crashes falling from 6 to 2. Consequently, the share of crashes with no reported injuries rose from 73.0% to 79.6%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes2%
↓-33.3%prior 3
Serious Injury2serious injury crashes2%
↓-50.0%prior 4
Minor Injury2minor injury crashes2%
↓-66.7%prior 6
Possible Injury14possible injury crashes14.3%
↓-17.6%prior 17
No Injury78no injury crashes79.6%
↓-3.7%prior 81

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 top contributing factor in both periods, though the count decreased from 32 crashes in 2022 to 29 in 2023. The second-ranked factor changed from 'Failure to yield from a stop sign' (9 crashes) in 2022 to a tie between 'Lost Control' and 'Failure to yield while making a left turn' (7 crashes each) in 2023. Notably, crashes from 'Failure to yield while making a left turn' increased from 2 to 7, while incidents of 'Driving too fast for conditions' dropped from 8 to 2.

Officer-Reported Primary Contributing Cause

Animal29 (29.6%)↓-9.4%prior 32
FTYROW: Making left turn7 (7.1%)
Lost Control7 (7.1%)↓-12.5%prior 8
FTYROW: From stop sign6 (6.1%)↓-33.3%prior 9
FTYROW: From driveway4 (4.1%)
Other (explain in narrative): Other4 (4.1%)↓-42.9%prior 7
Followed too close3 (3.1%)
Driver Distraction: Reaching for object(s)/fallen object(s)3 (3.1%)
Improper Backing3 (3.1%)
Driver Distraction: Exterior distraction2 (2%)

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 both 2023 and 2022, the vast majority of crashes occurred in clear weather on dry roads during daylight. However, there was a significant year-over-year reduction in crashes occurring in adverse lighting conditions, with collisions on dark, unlighted roadways falling from 17 in 2022 to 6 in 2023. Crashes on snow or ice-covered surfaces also decreased from 9 incidents in the prior year to 5 in the current year.

Weather

Clear52 (74.3%)
↓-18.8%prior 64
Cloudy9 (12.9%)
→0.0%prior 9
Fog, smoke, smog4 (5.7%)
Snow4 (5.7%)
Rain1 (1.4%)

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

Lighting

Daylight51 (70.8%)
↓-1.9%prior 52
Dark - roadway lighted9 (12.5%)
↑28.6%prior 7
Dark - roadway not lighted6 (8.3%)
↓-64.7%prior 17
Dusk3 (4.2%)
Dawn2 (2.8%)
Dark - unknown roadway lighting1 (1.4%)

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

Road Surface

Dry56 (80.0%)
↓-9.7%prior 62
Gravel5 (7.1%)
Snow4 (5.7%)
↓-33.3%prior 6
Wet4 (5.7%)
↓-20.0%prior 5
Ice/frost1 (1.4%)

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 Chevrolet and Ford ranking first and second in both years, though involvement for both makes decreased in 2023. The age distribution of people involved in collisions shifted notably; the 45-54 age group, which was the most represented in 2022 with 47 individuals, saw its involvement drop to 19 in 2023. In the current year, the 16-20 and 55-64 age groups were most frequently involved, each with 31 individuals.

Top Vehicle Makes (139 vehicles)

1
FORD26 (18.7%)
↓-18.8%prior 32
2
CHEV22 (15.8%)
↓-37.1%prior 35
3
GMC9 (6.5%)
↓-25.0%prior 12
4
CHEVROLET9 (6.5%)
↑80.0%prior 5
5
BUIC8 (5.8%)
6
DODG6 (4.3%)
↓-25.0%prior 8
7
HOND6 (4.3%)
8
NISS5 (3.6%)
9
PETERBILT4 (2.9%)
10
INTERNATIONA4 (2.9%)

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

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

Sex Distribution (132 persons with recorded sex)

Male82 (62.1%)
↓-12.8%prior 94
Female50 (37.9%)
↓-18.0%prior 61

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: 202
  • Total vehicles involved: 139

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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