Yearly Traffic Safety Analysis

115 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Calhoun County recorded 115 total crashes, a 6.5% increase from the 108 crashes reported in 2023. The total number of injuries remained unchanged at 30 across both years. The most notable year-over-year shift was the occurrence of one fatal crash resulting in one fatality in 2024, whereas no fatal crashes were recorded in the prior year.

115

▲ 6.5%was 108

Total Crash Events

1

Persons Killed

30

Persons Injured

1

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

Crash volume in Calhoun County experienced a slight year-over-year increase, rising by 6.5% from 108 incidents in 2023 to 115 in 2024. While the number of people injured held steady at 30, the county recorded one fatality in 2024 after having none in 2023.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0→%

30

Motorists Injured

Prior: 30→0.0%

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 timing of crashes shifted between the two periods. In 2024, the peak days for crashes were Tuesday and Friday, each with 22 incidents, a change from 2023 when Wednesday was the peak day with 23 crashes. The peak hour for collisions also moved from the afternoon (3 p.m. with 10 crashes) in 2023 to the evening (9 p.m. with 11 crashes) in 2024.

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

In 2024, Calhoun County recorded one fatal crash, which accounted for 0.9% of all incidents, compared to zero fatal crashes in 2023. The count of serious injury crashes decreased from 5 in 2023 to 3 in 2024. Conversely, the number of minor injury crashes increased from 7 to 10, and possible injury crashes rose from 8 to 12 year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.9%
Serious Injury3serious injury crashes2.6%
↓-40.0%prior 5
Minor Injury10minor injury crashes8.7%
↑42.9%prior 7
Possible Injury12possible injury crashes10.4%
↑50.0%prior 8
No Injury89no injury crashes77.4%
↑1.1%prior 88

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 involving an animal remained the leading contributing factor in both years, with the count increasing from 31 crashes in 2023 to 35 in 2024. 'Ran off road - left' became the second-most cited factor in 2024, with its count increasing from 4 to 11 incidents. In contrast, crashes attributed to 'Lost Control' decreased from 10 to 8, and incidents of 'Ran Stop Sign' fell from 8 to 5.

Officer-Reported Primary Contributing Cause

Animal35 (30.4%)↑12.9%prior 31
Ran off road - left11 (9.6%)
Lost Control8 (7%)↓-20.0%prior 10
Ran off road - straight7 (6.1%)
Improper Backing5 (4.3%)
Ran Stop Sign5 (4.3%)↓-37.5%prior 8
FTYROW: From stop sign4 (3.5%)
Exceeded authorized speed4 (3.5%)
Driving too fast for conditions3 (2.6%)↓-50.0%prior 6
Made improper turn3 (2.6%)

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

Road & Environmental Conditions

The majority of crashes in both years occurred in clear weather and during daylight. However, the proportion of crashes under these ideal conditions was lower in 2024 compared to 2023. For example, crashes on dry roads constituted 49.6% of the total in 2024 (57 crashes), down from a 60.2% share in 2023 (65 crashes). The number of crashes on roads with ice or frost decreased from 13 to 11.

Weather

Clear50 (54.9%)
↓-12.3%prior 57
Cloudy22 (24.2%)
↑15.8%prior 19
Snow5 (5.5%)
↓-16.7%prior 6
Fog, smoke, smog4 (4.4%)
Severe Winds4 (4.4%)
Rain3 (3.3%)
Freezing rain/drizzle2 (2.2%)
Blowing Snow1 (1.1%)

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

Lighting

Daylight52 (57.1%)
→0.0%prior 52
Dark - roadway not lighted29 (31.9%)
↓-3.3%prior 30
Dark - roadway lighted4 (4.4%)
Dawn3 (3.3%)
Dusk3 (3.3%)

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

Road Surface

Dry57 (62.6%)
↓-12.3%prior 65
Wet11 (12.1%)
↑83.3%prior 6
Ice/frost11 (12.1%)
↓-15.4%prior 13
Snow8 (8.8%)
↑60.0%prior 5
Gravel2 (2.2%)
Slush1 (1.1%)
Water (standing or moving)1 (1.1%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both periods, swapping the top two positions year-over-year; the count for Ford vehicles increased from 22 to 29, while Chevrolet vehicles decreased from 29 to 25. An analysis of persons involved shows a demographic shift, with a notable increase in the 16-20 age group (from 21 to 31 persons) and the 26-34 age group (from 20 to 32 persons). Conversely, the number of persons in the 35-44 and 45-54 age groups decreased from 33 each in 2023 to 19 and 14, respectively, in 2024.

Top Vehicle Makes (158 vehicles)

1
FORD29 (18.4%)
↑31.8%prior 22
2
CHEV25 (15.8%)
↓-13.8%prior 29
3
BUIC12 (7.6%)
↑9.1%prior 11
4
DODG11 (7%)
↑83.3%prior 6
5
CHEVROLET8 (5.1%)
↓-20.0%prior 10
6
GMC7 (4.4%)
→0.0%prior 7
7
CHRY6 (3.8%)
8
JEEP6 (3.8%)
9
DODGE4 (2.5%)
10
NISS4 (2.5%)

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

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

Sex Distribution (98 persons with recorded sex)

Male60 (61.2%)
↓-27.7%prior 83
Female38 (38.8%)
↓-40.6%prior 64

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 10, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 115
  • Total persons involved: 163
  • Total vehicles involved: 158

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 10, 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

ThatCarHitMe.com · An Injuria.ai Company