Yearly Traffic Safety Analysis

58,565 CRASHES IN
IOWA, IA
2019

All metrics benchmarked against2018

In 2019, Iowa recorded 58,565 total traffic crashes, an increase of 2.9% from the 56,895 crashes documented in 2018. This rise was accompanied by increases in both injuries and fatalities. The most significant year-over-year shift was an 7.9% increase in the number of fatal crashes, which rose from 291 in 2018 to 314 in 2019.

58,565

▲ 2.9%was 56,895

Total Crash Events

337

▲ 5.6%was 319

Persons Killed

18,605

▲ 2.3%was 18,178

Persons Injured

314

▲ 7.9%was 291

Fatal Crash Events

Note: "Persons Killed" (337) counts individual fatalities across all crash events. "Fatal" in the severity table below (314) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Iowa worsened from 2018 to 2019. Total crashes increased by 2.9%, from 56,895 to 58,565. This upward trend was also reflected in crash outcomes, with total fatalities rising 5.6% from 319 to 337 and total injuries increasing 2.4% from 18,178 to 18,605.

Vulnerable Road User Casualties

21

Pedestrians Killed

Prior: 22↓-4.5%

10

Cyclists Killed

Prior: 7↑42.9%

305

Motorists Killed

Prior: 290↑5.2%

1

Other Killed

Prior: 0→%

333

Pedestrians Injured

Prior: 375↓-11.2%

329

Cyclists Injured

Prior: 329→0.0%

17,914

Motorists Injured

Prior: 17,437↑2.7%

29

Other Injured

Prior: 37↓-21.6%

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained consistent year-over-year. Friday was the peak day for crashes in both 2019 (9,659 crashes) and 2018 (9,502 crashes), and the 5 PM hour was the peak hour in both periods. However, 2019 saw a notable increase in crashes occurring on Thursdays (from 8,128 to 8,798) and Mondays (from 8,765 to 9,027) compared to the prior year.

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased slightly from 2018 to 2019. The number of fatal crashes rose from 291 to 314, pushing the fatal crash rate up from 0.51% to 0.54% of all collisions. The counts of serious injury crashes (1,094 to 1,121) and minor injury crashes (4,957 to 5,132) also increased, though their proportional share of total crashes remained relatively stable.

Severity is per crash event (most severe injury). 314 fatal crash events resulted in 337 persons killed.

Outcome by Severity (Crash Events)

Fatal314fatal crashes0.5%
↑7.9%prior 291
Serious Injury1,121serious injury crashes1.9%
↑2.5%prior 1,094
Minor Injury5,132minor injury crashes8.8%
↑3.5%prior 4,957
Possible Injury9,203possible injury crashes15.7%
↑1.8%prior 9,042
No Injury42,795no injury crashes73.1%
↑3.1%prior 41,511

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors for crashes were consistent across both years, with 'Animal' and 'Followed too close' ranking as the top two causes. However, the count of crashes attributed to 'Driving too fast for conditions' increased by 11.8%, from 3,667 incidents in 2018 to 4,100 in 2019. Similarly, 'Ran off road - left' crashes grew by 9.9% in count, from 3,582 to 3,937. In contrast, crashes involving animals, the leading factor, decreased from 8,156 to 7,898.

Officer-Reported Primary Contributing Cause

Animal7,898 (13.5%)↓-3.2%prior 8,156
Followed too close6,049 (10.3%)↑0.4%prior 6,023
Driving too fast for conditions4,100 (7%)↑11.8%prior 3,667
Ran off road - left3,937 (6.7%)↑9.9%prior 3,582
Other (explain in narrative): Other3,606 (6.2%)↑3.6%prior 3,481
Lost Control3,108 (5.3%)↓-2.4%prior 3,184
FTYROW: From stop sign2,984 (5.1%)↑0.5%prior 2,968
FTYROW: Making left turn2,436 (4.2%)↑1.8%prior 2,393
Ran off road - straight1,999 (3.4%)↓-2.7%prior 2,054
Ran Traffic Signal1,834 (3.1%)↓-0.1%prior 1,835

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While the proportion of crashes in different lighting conditions remained stable, there was a significant shift in crashes occurring on adverse road surfaces. Crashes on snowy roads increased from 3,615 to 4,574 year-over-year, and incidents on icy or frosty surfaces rose from 3,049 to 4,229. Conversely, crashes on wet roads decreased from 7,096 to 6,790. This aligns with an 18% increase in crashes reported during snowy weather conditions.

Weather

Clear32,137 (61.7%)
↑2.7%prior 31,305
Cloudy11,325 (21.7%)
↑4.5%prior 10,842
Snow3,016 (5.8%)
↑17.9%prior 2,559
Rain2,890 (5.5%)
↓-6.9%prior 3,104
Freezing rain/drizzle1,130 (2.2%)
↓-11.2%prior 1,273
Blowing Snow923 (1.8%)
↑105.6%prior 449
Fog, smoke, smog322 (0.6%)
↓-6.4%prior 344
Severe Winds180 (0.3%)
↑104.5%prior 88
Sleet, hail87 (0.2%)
↓-34.1%prior 132
Other (explain in narrative)80 (0.2%)
↑15.9%prior 69

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash

Lighting

Daylight36,487 (69.8%)
↑4.3%prior 34,978
Dark - roadway lighted7,386 (14.1%)
↑2.9%prior 7,177
Dark - roadway not lighted5,781 (11.1%)
↑5.3%prior 5,490
Dusk1,319 (2.5%)
↓-0.2%prior 1,322
Dawn1,117 (2.1%)
↓-0.6%prior 1,124
Dark - unknown roadway lighting202 (0.4%)
↓-8.6%prior 221

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field

Road Surface

Dry34,925 (66.9%)
↑0.8%prior 34,650
Wet6,790 (13.0%)
↓-4.3%prior 7,096
Snow4,574 (8.8%)
↑26.5%prior 3,615
Ice/frost4,229 (8.1%)
↑38.7%prior 3,049
Slush736 (1.4%)
↓-5.3%prior 777
Gravel715 (1.4%)
↓-15.5%prior 846
Mud, dirt85 (0.2%)
↑3.7%prior 82
Other (explain in narrative)72 (0.1%)
↑24.1%prior 58
Sand30 (0.1%)
↓-6.3%prior 32
Water (standing or moving)10 (0.0%)
↓-58.3%prior 24

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Road surface condition field

Vehicles & Demographics

The vehicle makes most frequently involved in crashes, led by Ford and Chevrolet, showed little change in their rankings between 2018 and 2019. The demographic profile of persons involved in crashes also remained consistent. The 26-34 age group constituted the largest share of individuals in both years, and there were no significant shifts in the proportional representation of any specific age group.

Top Vehicle Makes (100,828 vehicles)

1
FORD16,407 (16.3%)
↑3.3%prior 15,882
2
CHEV13,212 (13.1%)
↓-0.1%prior 13,230
3
CHEVROLET6,613 (6.6%)
↑12.8%prior 5,863
4
TOYT4,658 (4.6%)
↓-3.5%prior 4,825
5
DODG4,033 (4%)
↓-7.4%prior 4,357
6
JEEP3,565 (3.5%)
↑10.3%prior 3,233
7
HOND3,274 (3.2%)
↓-2.0%prior 3,340
8
GMC3,145 (3.1%)
↑8.4%prior 2,901
9
NR2,901 (2.9%)
↑18.0%prior 2,459
10
NISS2,598 (2.6%)
↑0.4%prior 2,587

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · Vehicle unit records

17,229 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (90,671 persons with recorded sex)

Male51,340 (56.6%)
↑18.8%prior 43,231
Female39,331 (43.4%)
↑17.4%prior 33,512

Source: Iowa Crash Data · ArcGIS Open Data · 2019-01-01 to 2019-12-31 · 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: 2019-01-01 through 2019-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2019-01-01 through 2019-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 58,565
  • Total persons involved: 134,330
  • Total vehicles involved: 100,828

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: 2019." Published September 9, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2019-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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