Yearly Traffic Safety Analysis

201 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Madison County, total crashes remained relatively stable, increasing slightly from 198 in 2023 to 201 in 2024, a change of 1.5%. While total fatalities and injuries saw a minor decrease, one of the most notable shifts was a 150% increase in crashes involving driving under the influence (DUI), which rose from 2 to 5 incidents year-over-year.

201

▲ 1.5%was 198

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

61

▼ -7.6%was 66

Persons Injured

3

▼ -25.0%was 4

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 crash trends in Madison County were largely stable between 2023 and 2024, with total collisions rising by just 1.5% from 198 to 201. Despite the slight increase in total crashes, outcomes became marginally less severe, as total fatalities fell from 4 to 3 and total injuries decreased from 66 to 61.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

2

Motorists Killed

Prior: 4↓-50.0%

0

Pedestrians Injured

Prior: 0→0.0%

61

Motorists Injured

Prior: 65↓-6.2%

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 timing of crashes shifted year-over-year, with the peak day for collisions moving from Friday (35 crashes) in 2023 to Monday (42 crashes) in 2024. The daily peak hour also shifted slightly earlier from 5 p.m. in the prior period to 4 p.m. in the current period, though the crash volume during this hour was similar (21 vs. 20 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 saw a slight decrease in 2024 compared to the prior year. The number of fatal crashes dropped from 4 to 3, and the fatality rate per 100 crashes fell from 2.02 to 1.49. While the count of serious injury crashes decreased from 8 to 5, crashes resulting in minor injuries increased from 19 in 2023 to 27 in 2024.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.5%
↓-25.0%prior 4
Serious Injury5serious injury crashes2.5%
↓-37.5%prior 8
Minor Injury27minor injury crashes13.4%
↑42.1%prior 19
Possible Injury17possible injury crashes8.5%
↓-19.0%prior 21
No Injury149no injury crashes74.1%
↑2.1%prior 146

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, though the count of such incidents decreased by 26.5% from 68 in 2023 to 50 in 2024. Conversely, crashes attributed to 'Lost Control' increased by 29.4%, from 17 to 22 incidents. The most significant percentage change was seen in crashes due to 'Failure to Yield Right of Way from a stop sign,' which saw its count increase by 150% from 6 to 15 incidents.

Officer-Reported Primary Contributing Cause

Animal50 (24.9%)↓-26.5%prior 68
Lost Control22 (10.9%)↑29.4%prior 17
FTYROW: From stop sign15 (7.5%)↑150.0%prior 6
Driver Distraction: Other interior distraction9 (4.5%)↑80.0%prior 5
Ran off road - straight9 (4.5%)↓-10.0%prior 10
Other (explain in narrative): Other9 (4.5%)↓-10.0%prior 10
Ran off road - left7 (3.5%)↓-41.7%prior 12
Driving too fast for conditions7 (3.5%)↑40.0%prior 5
FTYROW: From yield sign6 (3%)↓-25.0%prior 8
Followed too close5 (2.5%)↓-44.4%prior 9

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 were more likely to occur in clear weather and daylight in 2024 compared to 2023. Crashes in daylight increased from 93 to 116, and those in clear weather rose from 103 to 126. A notable shift in road surface conditions occurred, with crashes on icy or frosty roads increasing significantly from 3 incidents in 2023 to 13 in 2024.

Weather

Clear126 (80.8%)
↑22.3%prior 103
Cloudy15 (9.6%)
↓-25.0%prior 20
Snow5 (3.2%)
↓-50.0%prior 10
Rain4 (2.6%)
↓-33.3%prior 6
Freezing rain/drizzle2 (1.3%)
Other (explain in narrative)2 (1.3%)
Sleet, hail1 (0.6%)
Fog, smoke, smog1 (0.6%)

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

Lighting

Daylight116 (69.5%)
↑24.7%prior 93
Dark - roadway not lighted30 (18.0%)
↓-11.8%prior 34
Dark - roadway lighted9 (5.4%)
↓-10.0%prior 10
Dawn6 (3.6%)
↓-14.3%prior 7
Dusk5 (3.0%)
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry117 (71.8%)
↑7.3%prior 109
Gravel15 (9.2%)
↑25.0%prior 12
Ice/frost13 (8.0%)
Wet9 (5.5%)
↑50.0%prior 6
Snow8 (4.9%)
↓-20.0%prior 10
Mud, dirt1 (0.6%)

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, Ford and Chevrolet, remained consistent year-over-year, with both makes seeing an increase in involvement. The number of Ford vehicles in crashes rose from 48 to 67, while combined Chevrolet models rose from 64 to 67. An analysis of persons involved shows the 35-44 age group was the most represented in both years, while the proportion of people in the 16-20 age group increased from 11.2% of all persons in 2023 to 13.3% in 2024.

Top Vehicle Makes (291 vehicles)

1
FORD67 (23%)
↑39.6%prior 48
2
CHEV48 (16.5%)
↓-5.9%prior 51
3
CHEVROLET19 (6.5%)
↑46.2%prior 13
4
DODG15 (5.2%)
↑36.4%prior 11
5
TOYT13 (4.5%)
↑18.2%prior 11
6
NISS10 (3.4%)
↑11.1%prior 9
7
HOND9 (3.1%)
↑28.6%prior 7
8
JEEP9 (3.1%)
→0.0%prior 9
9
KIA8 (2.7%)
→0.0%prior 8
10
GMC8 (2.7%)
↓-27.3%prior 11

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

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

Sex Distribution (178 persons with recorded sex)

Male105 (59.0%)
↓-23.4%prior 137
Female73 (41.0%)
↓-38.1%prior 118

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: 201
  • Total persons involved: 302
  • Total vehicles involved: 291

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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