Yearly Traffic Safety Analysis

147 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Palo Alto County, the total number of traffic crashes remained unchanged at 147 in 2024 compared to 2023. Despite the stable overall volume, the number of persons injured increased by 14.3% from 42 to 48. A notable year-over-year change was the doubling of crashes involving a driver under the influence (DUI), which rose from 4 in 2023 to 8 in 2024.

147

Total Crash Events

1

Persons Killed

48

▲ 14.3%was 42

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

Overall crash trends in Palo Alto County were stable year-over-year, with the total number of crashes holding steady at 147 for both 2024 and 2023. The number of fatalities also remained unchanged at one death in each period. However, the number of people injured in crashes saw an increase of 14.3%, rising from 42 in 2023 to 48 in 2024.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Pedestrians Injured

Prior: 0→%

2

Cyclists Injured

Prior: 2→0.0%

45

Motorists Injured

Prior: 40↑12.5%

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 both consistency and change year-over-year. The peak day for crashes remained Thursday in both 2024 (30 crashes) and 2023 (34 crashes), and the peak hour was also consistent at 7 a.m. in both periods. However, the distribution of crashes by day shifted, with Tuesday crashes increasing from 16 to 26, while Friday crashes decreased from 25 to 15.

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 number of fatal crashes remained unchanged with one fatal crash recorded in both 2024 and 2023. While the total number of crashes resulting in any level of injury was the same at 34 in both years, the severity of those injuries shifted. The count of serious injury crashes increased from 3 to 5, and minor injury crashes rose from 16 to 25, offset by a decrease in possible injury crashes from 15 to 4.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
→0.0%prior 1
Serious Injury5serious injury crashes3.4%
↑66.7%prior 3
Minor Injury25minor injury crashes17%
↑56.3%prior 16
Possible Injury4possible injury crashes2.7%
↓-73.3%prior 15
No Injury112no injury crashes76.2%
→0.0%prior 112

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 from 50 crashes in 2023 to 56 in 2024. The ranking of other top factors shifted notably; crashes attributed to a driver operating their vehicle in a reckless or careless manner doubled in count from 4 to 8, becoming a top-three factor in 2024. Incidents involving a driver losing control also increased from 6 to 8.

Officer-Reported Primary Contributing Cause

Animal56 (38.1%)↑12.0%prior 50
Operating vehicle in an reckless, erratic, careless, negligent manner8 (5.4%)
Lost Control8 (5.4%)↑33.3%prior 6
Followed too close6 (4.1%)↓-14.3%prior 7
Improper Backing5 (3.4%)
Driver Distraction: Other interior distraction5 (3.4%)
FTYROW: From stop sign5 (3.4%)↓-16.7%prior 6
FTYROW: Making left turn5 (3.4%)
Ran Stop Sign4 (2.7%)
Ran off road - straight4 (2.7%)

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 number of crashes occurring on dry road surfaces was identical in both years at 65. There was a significant shift in crashes related to winter conditions, as incidents on snowy roads decreased from 15 in 2023 to 3 in 2024. In contrast, crashes on wet roads increased from 7 to 11, and those occurring in rainy conditions rose from 1 to 5. Crashes in daylight decreased from 78 to 68, while those in dark, unlighted conditions remained stable at 14.

Weather

Clear67 (73.6%)
↓-4.3%prior 70
Cloudy11 (12.1%)
↓-35.3%prior 17
Rain5 (5.5%)
Fog, smoke, smog3 (3.3%)
Snow3 (3.3%)
↓-62.5%prior 8
Freezing rain/drizzle2 (2.2%)

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

Lighting

Daylight68 (70.8%)
↓-12.8%prior 78
Dark - roadway not lighted14 (14.6%)
→0.0%prior 14
Dawn4 (4.2%)
Dark - unknown roadway lighting4 (4.2%)
Dusk3 (3.1%)
↓-40.0%prior 5
Dark - roadway lighted3 (3.1%)
↓-40.0%prior 5

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

Road Surface

Dry65 (70.7%)
→0.0%prior 65
Wet11 (12.0%)
↑57.1%prior 7
Ice/frost6 (6.5%)
↑20.0%prior 5
Gravel6 (6.5%)
↑20.0%prior 5
Snow3 (3.3%)
↓-80.0%prior 15
Other (explain in narrative)1 (1.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained similar year-over-year, with Ford (53 vehicles) and Chevrolet (43 vehicles) being the most frequently involved in 2024, consistent with the prior year. Analysis of persons involved shows a notable demographic shift. The proportion of individuals aged 65 and older involved in crashes increased from 12.4% of all persons in 2023 to 19.2% in 2024, while the share of those in the 16-20 age group saw a slight decrease.

Top Vehicle Makes (204 vehicles)

1
FORD53 (26%)
↑3.9%prior 51
2
CHEV40 (19.6%)
↑5.3%prior 38
3
GMC13 (6.4%)
↑8.3%prior 12
4
JEEP10 (4.9%)
↑42.9%prior 7
5
TOYT9 (4.4%)
6
DODG9 (4.4%)
↓-10.0%prior 10
7
PETERBILT6 (2.9%)
8
DODGE6 (2.9%)
9
NISS5 (2.5%)
10
KIA5 (2.5%)

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

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

Sex Distribution (98 persons with recorded sex)

Male64 (65.3%)
↓-51.1%prior 131
Female34 (34.7%)
↓-57.0%prior 79

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: 147
  • Total persons involved: 219
  • Total vehicles involved: 204

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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