ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/2024-annual-report
Yearly Traffic Safety Analysis
367 CRASHES IN
IOWA, IA
2024
In Mahaska County, total traffic crashes increased by 38.5% year-over-year, rising from 265 incidents in 2023 to 367 in 2024. While the number of injuries saw a modest rise from 102 to 110, fatalities decreased from 4 to 2. The single most notable shift was a 410% increase in the count of crashes attributed to animals, which grew from 20 to 102 incidents.
367
▲ 38.5%was 265
Total Crash Events
2
▼ -50.0%was 4
Persons Killed
110
▲ 7.8%was 102
Persons Injured
1
▼ -66.7%was 3
Fatal Crash Events
Note: "Persons Killed" (2) 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, Mahaska County experienced a rising trend in traffic collisions, with total crashes increasing by 38.5% from 265 in 2023 to 367 in 2024. This increase was accompanied by a 7.8% rise in total injuries, from 102 to 110. In contrast, the number of fatalities resulting from these crashes decreased by half, from 4 to 2.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
4
Pedestrians Injured
1
Cyclists Injured
100
Motorists Injured
5
Other Injured
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 the two periods. Friday remained the peak day for crashes in both years, though the volume on Friday increased from 46 incidents in 2023 to 67 in 2024. The evening commute hours continued to be the most frequent time for crashes, but the peak hour shifted later, from the 4 p.m. hour in 2023 (24 crashes) to the 5 p.m. hour in 2024 (38 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 year-over-year, with a lower proportion of incidents resulting in death or injury. The number of fatal crashes decreased from 3 to 1, causing the fatal crash rate to fall from 1.13% to 0.27%. Although the absolute count of injury-producing crashes rose from 75 to 83, their share of all crashes declined from 28.3% to 22.5%. Consequently, the proportion of non-injury crashes increased from 70.6% of all incidents in 2023 to 77.1% in 2024.
Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.
Outcome by Severity (Crash Events)
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 ranking of contributing factors changed significantly, driven by a dramatic increase in animal-related incidents. Crashes involving an 'Animal' surged from 20 in 2023 to 102 in 2024, a 410% increase in count, making it the leading factor. 'Followed too close' remained a top factor, with its count increasing from 28 to 37 incidents. Conversely, crashes where drivers failed to yield the right-of-way from a stop sign ('FTYROW: From stop sign') decreased in count from 23 to 11.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A larger proportion of crashes occurred under adverse conditions in 2024 compared to the previous year. The share of crashes happening on dry road surfaces decreased from 75.1% in 2023 to 56.4% in 2024. Similarly, the proportion of crashes occurring in daylight dropped from 64.2% to 53.4%, and those in clear weather fell from 63.4% to 51.2% of the annual total.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
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 saw a shift in ranking, while the age distribution of persons involved also changed. Ford and Chevrolet remained the top two makes, but Ford-involved vehicles increased from 86 to 118, surpassing Chevrolet (87 to 112) for the top spot. For persons involved, the 16-20 age group's representation decreased from 100 individuals to 73, while the 45-54 and 65+ age groups became the most frequently involved, each with 86 individuals.
Top Vehicle Makes (582 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
47 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (355 persons with recorded sex)
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: 367
- Total persons involved: 615
- Total vehicles involved: 582
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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2024-01-01 – 2024-12-31
Generated: September 9, 2026 · All rights reserved