Monthly Traffic Safety Analysis

3,733 CRASHES IN
IOWA, IA
MARCH 2024

All metrics benchmarked againstMarch 2023

In March 2024, there were 3,733 traffic crashes, a slight decrease of 0.9% from the 3,766 crashes recorded in March 2023. While the total number of crashes and fatalities (26 in both periods) remained stable, the most notable year-over-year shift was a 24.6% increase in the number of crashes resulting in serious injuries, which rose from 65 to 81.

3,733

▼ -0.9%was 3,766

Total Crash Events

26

Persons Killed

1,134

▲ 2.5%was 1,106

Persons Injured

25

▲ 19.0%was 21

Fatal Crash Events

Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (25) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume remained relatively stable, decreasing by less than 1% from 3,766 incidents in March 2023 to 3,733 in March 2024. Despite this stability, total injuries rose by 2.5% from 1,106 to 1,134, while fatalities held constant at 26, suggesting a slight increase in the average severity of crashes.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 2↑100.0%

0

Cyclists Killed

Prior: 0→0.0%

22

Motorists Killed

Prior: 24↓-8.3%

0

Other Killed

Prior: 0→0.0%

26

Pedestrians Injured

Prior: 29↓-10.3%

15

Cyclists Injured

Prior: 6↑150.0%

1,091

Motorists Injured

Prior: 1,067↑2.2%

2

Other Injured

Prior: 4↓-50.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday (724 crashes) in March 2023 to Friday (917 crashes) in March 2024. The afternoon commute remained the most hazardous time, with the 3 p.m. hour being the peak for both periods, although the crash count during this hour decreased from 332 to 300.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes intensified year-over-year. Fatal crashes increased from 21 to 25, raising the fatal crash rate from 0.56% to 0.67%. The number of serious injury crashes saw a more significant jump, increasing by 24.6% from 65 to 81. Consequently, the share of crashes involving a serious injury grew from 1.7% to 2.2% of all incidents.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 26 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.7%
↑19.0%prior 21
Serious Injury81serious injury crashes2.2%
↑24.6%prior 65
Minor Injury361minor injury crashes9.7%
↑18.8%prior 304
Possible Injury568possible injury crashes15.2%
↓-4.9%prior 597
No Injury2,698no injury crashes72.3%
↓-2.9%prior 2,779

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the top contributing factor in both periods, though the count of such incidents decreased by 19.5% from 548 to 441. The top three factors remained the same, with "Followed too close" (317 crashes) and "Ran off road - left" (253 crashes) following. A significant year-over-year increase was seen in crashes due to "Improper or erratic lane changing," with the count rising 57.1% from 63 to 99 incidents.

Officer-Reported Primary Contributing Cause

Animal441 (11.8%)↓-19.5%prior 548
Followed too close317 (8.5%)↑3.9%prior 305
Ran off road - left253 (6.8%)↓-3.4%prior 262
Other (explain in narrative): Other205 (5.5%)↑1.5%prior 202
Driving too fast for conditions200 (5.4%)↓-5.7%prior 212
Lost Control188 (5%)↓-13.8%prior 218
FTYROW: From stop sign186 (5%)↑5.1%prior 177
FTYROW: Making left turn168 (4.5%)↑18.3%prior 142
Ran off road - straight158 (4.2%)↓-5.4%prior 167
Ran Traffic Signal152 (4.1%)↑22.6%prior 124

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Road conditions were generally more favorable in March 2024 compared to the prior year. Crashes on dry road surfaces accounted for 69.0% of the total, up from 63.4% in March 2023. Correspondingly, incidents on roads affected by snow, ice, or slush dropped from 15.7% to 9.3% of all crashes. Crashes in clear weather increased from 52.5% to 59.7% of the total, while snow-related crashes decreased from 9.2% to 4.2%.

Weather

Clear2,228 (66.8%)
↑12.7%prior 1,977
Cloudy597 (17.9%)
↓-13.4%prior 689
Rain192 (5.8%)
↑182.4%prior 68
Snow157 (4.7%)
↓-54.9%prior 348
Freezing rain/drizzle95 (2.8%)
↑9.2%prior 87
Sleet, hail33 (1.0%)
↑57.1%prior 21
Blowing Snow14 (0.4%)
↓-71.4%prior 49
Other (explain in narrative)9 (0.3%)
↑80.0%prior 5
Severe Winds7 (0.2%)
↓-61.1%prior 18
Fog, smoke, smog2 (0.1%)
↓-90.0%prior 20

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash

Lighting

Daylight2,369 (70.7%)
↑0.5%prior 2,357
Dark - roadway lighted459 (13.7%)
↑7.0%prior 429
Dark - roadway not lighted352 (10.5%)
↑1.1%prior 348
Dawn79 (2.4%)
↓-10.2%prior 88
Dusk65 (1.9%)
↓-3.0%prior 67
Dark - unknown roadway lighting28 (0.8%)
↑75.0%prior 16

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field

Road Surface

Dry2,575 (76.9%)
↑7.9%prior 2,386
Wet371 (11.1%)
↑39.5%prior 266
Snow138 (4.1%)
↓-50.9%prior 281
Ice/frost107 (3.2%)
↓-33.5%prior 161
Slush104 (3.1%)
↓-29.7%prior 148
Gravel46 (1.4%)
↑24.3%prior 37
Mud, dirt5 (0.1%)
↓-37.5%prior 8
Other (explain in narrative)1 (0.0%)
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (6,353 vehicles)

1
FORD988 (15.6%)
↑2.3%prior 966
2
CHEV882 (13.9%)
↑0.5%prior 878
3
CHEVROLET336 (5.3%)
↑4.7%prior 321
4
TOYT314 (4.9%)
↑6.1%prior 296
5
JEEP304 (4.8%)
↑17.4%prior 259
6
HOND276 (4.3%)
↑26.0%prior 219
7
DODG251 (4%)
↑9.6%prior 229
8
GMC225 (3.5%)
↓-11.4%prior 254
9
NISS189 (3%)
↓-14.1%prior 220
10
KIA176 (2.8%)
↓-12.0%prior 200

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records

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

Sex Distribution (4,219 persons with recorded sex)

Male2,431 (57.6%)
↓-24.8%prior 3,232
Female1,788 (42.4%)
↓-26.6%prior 2,435

Source: Iowa Crash Data · ArcGIS Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-03-01 through 2024-03-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,733
  • Total persons involved: 6,592
  • Total vehicles involved: 6,353

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: March 2024." Published September 9, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/march-2024-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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