Yearly Traffic Safety Analysis

334 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Buena Vista County recorded 334 traffic crashes, a 12.5% increase from the 297 crashes reported in 2023. While the number of fatalities remained stable at three for both years, total injuries rose from 96 to 105. The most significant year-over-year change was a 44.9% increase in the count of crashes attributed to animals, which rose from 49 incidents in 2023 to 71 in 2024.

334

▲ 12.5%was 297

Total Crash Events

3

Persons Killed

105

▲ 9.4%was 96

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (3) 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 Buena Vista County are trending upward year-over-year. The total number of crashes increased by 12.5%, from 297 in 2023 to 334 in 2024. This rise was accompanied by a 9.4% increase in total injuries, although fatalities held constant at three persons killed in both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 3→0.0%

1

Pedestrians Injured

Prior: 3↓-66.7%

1

Cyclists Injured

Prior: 2↓-50.0%

103

Motorists Injured

Prior: 91↑13.2%

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 showed some shifts between 2023 and 2024. The most frequent day for crashes moved from Tuesday (51 crashes) in the prior year to Friday (57 crashes) in the current year. While 2023 had dual peak hours for collisions at 3 p.m. and 5 p.m. (28 crashes each), 2024 saw a more defined peak hour at 3 p.m. with 31 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 distribution of crash severity saw a notable shift toward more serious outcomes, despite a stable overall injury crash rate. The fatal crash rate decreased slightly from 0.7% in 2023 to 0.6% in 2024, with two fatal crashes recorded in each year. However, the number of serious injury crashes increased tenfold from just one in 2023 to 10 in 2024. Consequently, the proportion of all crashes resulting in serious injury rose from 0.3% to 3.0%.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
→0.0%prior 2
Serious Injury10serious injury crashes3%
↑900.0%prior 1
Minor Injury37minor injury crashes11.1%
↓-11.9%prior 42
Possible Injury44possible injury crashes13.2%
↑15.8%prior 38
No Injury241no injury crashes72.2%
↑12.6%prior 214

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

The leading contributing factors to crashes shifted significantly year-over-year. Collisions involving an animal remained the top factor, increasing in count by 44.9% from 49 incidents in 2023 to 71 in 2024. Crashes attributed to 'Driving too fast for conditions' saw a 300% rise in count, from 6 to 24, while 'Failure to yield from a stop sign' doubled from 12 to 24 incidents. Conversely, crashes caused by 'Followed too close' decreased by 80% in count, from 20 in the prior year to only 4 in the current period.

Officer-Reported Primary Contributing Cause

Animal71 (21.3%)↑44.9%prior 49
Driving too fast for conditions24 (7.2%)↑300.0%prior 6
FTYROW: From stop sign24 (7.2%)↑100.0%prior 12
Ran off road - left17 (5.1%)↑88.9%prior 9
Ran off road - straight16 (4.8%)↑60.0%prior 10
Lost Control16 (4.8%)↑6.7%prior 15
Ran Stop Sign15 (4.5%)↑15.4%prior 13
Made improper turn15 (4.5%)↑15.4%prior 13
Driver Distraction: Other interior distraction14 (4.2%)↓-17.6%prior 17
Improper Backing12 (3.6%)↓-14.3%prior 14

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

Road & Environmental Conditions

Crashes in 2024 occurred under slightly more varied conditions compared to 2023. The proportion of crashes happening in clear weather decreased from 70.7% to 63.8%, while crashes during foggy conditions increased from 1 to 10. Similarly, the share of collisions on dry road surfaces fell from 69.4% to 63.2%. The number of crashes on non-dry surfaces like wet or icy roads remained nearly identical, with 68 incidents in 2024 compared to 67 in 2023.

Weather

Clear213 (76.9%)
↑1.4%prior 210
Cloudy26 (9.4%)
↓-27.8%prior 36
Rain12 (4.3%)
→0.0%prior 12
Fog, smoke, smog10 (3.6%)
Snow6 (2.2%)
→0.0%prior 6
Freezing rain/drizzle5 (1.8%)
Blowing Snow3 (1.1%)
Severe Winds2 (0.7%)

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

Lighting

Daylight185 (65.1%)
↑5.7%prior 175
Dark - roadway not lighted56 (19.7%)
↑9.8%prior 51
Dark - roadway lighted27 (9.5%)
↑3.8%prior 26
Dusk9 (3.2%)
↑12.5%prior 8
Dawn5 (1.8%)
↓-50.0%prior 10
Dark - unknown roadway lighting2 (0.7%)

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

Road Surface

Dry211 (75.6%)
↑2.4%prior 206
Wet27 (9.7%)
↓-15.6%prior 32
Ice/frost20 (7.2%)
↑42.9%prior 14
Snow12 (4.3%)
→0.0%prior 12
Gravel6 (2.2%)
↓-14.3%prior 7
Slush3 (1.1%)

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 saw a shift in ranking between the two periods. In 2024, Ford became the most common make with 91 vehicles involved, up from 73 in the prior year, surpassing Chevrolet, which decreased from 87 to 76 vehicles. The demographic profile of persons involved in crashes showed that the 16-20 and 65+ age groups represented a slightly larger share of the total in 2024 compared to 2023. The total number of persons involved in crashes decreased from 634 to 542 year-over-year.

Top Vehicle Makes (524 vehicles)

1
FORD91 (17.4%)
↑24.7%prior 73
2
CHEV76 (14.5%)
↓-12.6%prior 87
3
DODG33 (6.3%)
↑13.8%prior 29
4
CHEVROLET25 (4.8%)
↓-10.7%prior 28
5
GMC24 (4.6%)
↓-14.3%prior 28
6
HOND20 (3.8%)
↑42.9%prior 14
7
NISS20 (3.8%)
↑33.3%prior 15
8
TOYT19 (3.6%)
↓-5.0%prior 20
9
JEEP19 (3.6%)
↓-24.0%prior 25
10
BUIC16 (3.1%)
↑77.8%prior 9

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

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

Sex Distribution (308 persons with recorded sex)

Male194 (63.0%)
↓-23.9%prior 255
Female114 (37.0%)
↓-32.9%prior 170

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: 334
  • Total persons involved: 542
  • Total vehicles involved: 524

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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