Yearly Traffic Safety Analysis

159 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Fremont County recorded 159 total crashes, an increase of 12.8% from the 141 crashes reported in 2023. Despite the rise in total collisions, the number of fatalities decreased from 5 in the prior period to 2 in the current period. Crashes suspected to involve driving under the influence also saw a notable decrease, falling by 50% from 8 to 4 incidents.

159

▲ 12.8%was 141

Total Crash Events

2

▼ -60.0%was 5

Persons Killed

56

▼ -1.8%was 57

Persons Injured

2

▼ -60.0%was 5

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

Trend Summary

Overall, traffic crashes in Fremont County increased by 12.8% from 2023 to 2024, rising from 141 to 159 incidents. While the total number of crashes went up, the number of resulting injuries remained stable at 56 compared to 57 the previous year. Notably, fatalities saw a significant reduction, dropping from 5 in 2023 to 2 in 2024.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

1

Motorists Killed

Prior: 4↓-75.0%

0

Pedestrians Injured

Prior: 0→0.0%

56

Motorists Injured

Prior: 57↓-1.8%

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 patterns of crashes shifted between the two periods. In 2024, the peak day for crashes was Friday with 32 incidents, a change from Wednesday in 2023 which saw 31 crashes. The peak hour also moved significantly later into the evening, from 1 p.m. in the prior year (11 crashes) to 8 p.m. in the current year (15 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

Crash severity improved year-over-year, with the fatal crash rate falling from 3.55% in 2023 to 1.26% in 2024, corresponding to a drop from 5 fatal crashes to 2. While fatal crashes declined, the number of serious injury crashes increased from 4 to 7. The proportion of crashes resulting in no injury remained the largest category in both periods, accounting for 69.2% of crashes in 2024 compared to 68.1% in 2023.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.3%
↓-60.0%prior 5
Serious Injury7serious injury crashes4.4%
↑75.0%prior 4
Minor Injury23minor injury crashes14.5%
↑15.0%prior 20
Possible Injury17possible injury crashes10.7%
↑6.3%prior 16
No Injury110no injury crashes69.2%
↑14.6%prior 96

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 periods, with the count of such incidents increasing from 38 in 2023 to 47 in 2024. The second-ranked factor from the prior year, 'Lost Control,' saw a notable decrease in count from 26 crashes to 17. Conversely, crashes attributed to 'Followed too close' increased in count from 10 to 14, becoming the third most common factor in the current period.

Officer-Reported Primary Contributing Cause

Animal47 (29.6%)↑23.7%prior 38
Lost Control17 (10.7%)↓-34.6%prior 26
Followed too close14 (8.8%)↑40.0%prior 10
Ran off road - straight13 (8.2%)↑18.2%prior 11
Driving too fast for conditions8 (5%)↑14.3%prior 7
Driver Distraction: Other interior distraction8 (5%)
Ran off road - left6 (3.8%)
Operating vehicle in an reckless, erratic, careless, negligent manner5 (3.1%)↓-16.7%prior 6
FTYROW: From stop sign5 (3.1%)
Other (explain in narrative): Other4 (2.5%)

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 distribution of crashes across environmental conditions remained largely consistent year-over-year, with crashes on dry roads accounting for 54.7% of incidents in 2024 compared to 52.5% in 2023. The proportion of crashes occurring in daylight decreased slightly from 50.4% to 46.5%. Notably, crashes on roads with ice or frost decreased from 13 incidents in the prior period to 7 in the current period.

Weather

Clear83 (69.7%)
↑13.7%prior 73
Cloudy17 (14.3%)
→0.0%prior 17
Rain6 (5.0%)
Freezing rain/drizzle4 (3.4%)
↓-20.0%prior 5
Snow3 (2.5%)
↓-57.1%prior 7
Fog, smoke, smog2 (1.7%)
Blowing Snow2 (1.7%)
Severe Winds1 (0.8%)
Blowing sand, soil, dirt1 (0.8%)

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

Lighting

Daylight74 (58.7%)
↑4.2%prior 71
Dark - roadway not lighted28 (22.2%)
↑21.7%prior 23
Dusk9 (7.1%)
↑80.0%prior 5
Dark - unknown roadway lighting6 (4.8%)
Dark - roadway lighted5 (4.0%)
Dawn4 (3.2%)

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

Road Surface

Dry87 (72.5%)
↑17.6%prior 74
Wet10 (8.3%)
↓-9.1%prior 11
Gravel7 (5.8%)
Ice/frost7 (5.8%)
↓-46.2%prior 13
Snow6 (5.0%)
↑20.0%prior 5
Other (explain in narrative)1 (0.8%)
Mud, dirt1 (0.8%)
Water (standing or moving)1 (0.8%)

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

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in crashes in both periods, with the count for Ford-made vehicles increasing from 27 to 36. A significant demographic shift occurred among persons involved in crashes; the 16-20 age group's involvement dropped from 54 individuals in 2023 to 26 in 2024. In the current period, the 35-44 age group was the most frequently involved, with 41 persons.

Top Vehicle Makes (221 vehicles)

1
FORD36 (16.3%)
↑33.3%prior 27
2
CHEVROLET22 (10%)
↓-15.4%prior 26
3
CHEV19 (8.6%)
↑46.2%prior 13
4
DODGE14 (6.3%)
↑180.0%prior 5
5
FREIGHTLINER11 (5%)
↑37.5%prior 8
6
KIA9 (4.1%)
↑50.0%prior 6
7
GMC8 (3.6%)
↓-27.3%prior 11
8
NISS6 (2.7%)
9
NISSAN6 (2.7%)
10
HONDA6 (2.7%)
↑20.0%prior 5

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

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

Sex Distribution (112 persons with recorded sex)

Male78 (69.6%)
↓-38.6%prior 127
Female34 (30.4%)
↓-35.8%prior 53

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: 159
  • Total persons involved: 228
  • Total vehicles involved: 221

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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