Yearly Traffic Safety Analysis

89 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In the most recent period, Ida County recorded 89 total crashes, a 9.2% decrease from the 98 crashes in the same period a year prior. While overall crashes and fatalities declined, the number of crashes involving injuries increased. The most notable year-over-year shift was a decrease in DUI-related crashes from 3 to 1.

89

▼ -9.2%was 98

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

29

▲ 7.4%was 27

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Ida County showed a downward trend, decreasing from 98 incidents in the prior year to 89 in the current year. Fatalities were halved, dropping from 2 to 1. However, the total number of individuals injured in crashes saw a slight increase from 27 to 29.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

27

Motorists Injured

Prior: 27→0.0%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal pattern of crashes shifted year-over-year. The peak day for crashes moved from Wednesday (22 crashes) in the prior period to Friday (21 crashes) in the current period. The peak hour also changed, with the prior period's single peak at 4 p.m. (10 crashes) being replaced by multiple peaks in the current period, including 5 a.m., 4 p.m., and 9 p.m., each with 7 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted, with the fatal crash count decreasing from 2 to 1 year-over-year. While crashes resulting in serious injuries also decreased from 2 to 1, the number of minor injury crashes quadrupled from 2 to 8. Consequently, the overall proportion of crashes involving any type of injury rose from 18.4% in the prior period to 25.8% in the current period.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.1%
↓-50.0%prior 2
Serious Injury1serious injury crashes1.1%
↓-50.0%prior 2
Minor Injury8minor injury crashes9%
↑300.0%prior 2
Possible Injury14possible injury crashes15.7%
→0.0%prior 14
No Injury65no injury crashes73%
↓-16.7%prior 78

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, with the count increasing slightly from 29 to 30. There were significant shifts in other factors; crashes attributed to 'Driving too fast for conditions' and 'Ran off road - straight' both increased from 2 to 7 incidents. Conversely, crashes where 'FTYROW: Making left turn' was a factor decreased from 7 to 2, and 'Lost Control' incidents also fell from 7 to 2.

Officer-Reported Primary Contributing Cause

Animal30 (33.7%)↑3.4%prior 29
Ran off road - straight7 (7.9%)
Driving too fast for conditions7 (7.9%)
FTYROW: From stop sign4 (4.5%)↓-33.3%prior 6
FTYROW: From driveway3 (3.4%)
Ran off road - left3 (3.4%)
Driver Distraction: Other interior distraction3 (3.4%)
FTYROW: Making left turn2 (2.2%)↓-71.4%prior 7
Failed to keep in proper lane2 (2.2%)
FTYROW: At uncontrolled intersection2 (2.2%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While clear weather and daylight conditions remained the most common setting for crashes in both periods, there was a notable shift in road surface conditions. In the prior year, 57.1% of crashes occurred on dry roads, compared to only 41.6% in the current year. Correspondingly, the number of crashes on roads with ice, frost, or snow increased from a combined 5 incidents to 14 incidents year-over-year.

Weather

Clear44 (71.0%)
↓-15.4%prior 52
Cloudy11 (17.7%)
↑22.2%prior 9
Fog, smoke, smog2 (3.2%)
Snow2 (3.2%)
Freezing rain/drizzle1 (1.6%)
Rain1 (1.6%)
Sleet, hail1 (1.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight43 (67.2%)
↓-15.7%prior 51
Dark - roadway not lighted9 (14.1%)
↑50.0%prior 6
Dark - roadway lighted5 (7.8%)
↓-44.4%prior 9
Dark - unknown roadway lighting3 (4.7%)
Dawn2 (3.1%)
Dusk2 (3.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry37 (59.7%)
↓-33.9%prior 56
Ice/frost7 (11.3%)
Snow7 (11.3%)
Wet5 (8.1%)
Gravel5 (8.1%)
→0.0%prior 5
Mud, dirt1 (1.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet leading in both periods with similar counts. An analysis of persons involved shows the 16-20 age group's representation increased, accounting for 20.5% of all persons in the current period compared to 15.3% in the prior period, despite a drop in their absolute count from 31 to 27.

Top Vehicle Makes (127 vehicles)

1
FORD27 (21.3%)
↑3.8%prior 26
2
CHEV26 (20.5%)
↑18.2%prior 22
3
GMC11 (8.7%)
↑22.2%prior 9
4
CHEVROLET10 (7.9%)
↑11.1%prior 9
5
DODG6 (4.7%)
→0.0%prior 6
6
FREIGHTLINER4 (3.1%)
7
NISS4 (3.1%)
↓-20.0%prior 5
8
HOND4 (3.1%)
↓-33.3%prior 6
9
JEEP4 (3.1%)
10
PETERBILT3 (2.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (62 persons with recorded sex)

Male45 (72.6%)
↓-45.1%prior 82
Female17 (27.4%)
↓-66.0%prior 50

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 89
  • Total persons involved: 132
  • Total vehicles involved: 127

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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