Yearly Traffic Safety Analysis

47,894 CRASHES IN
IOWA, IA
2020

All metrics benchmarked against2019

In 2020, Iowa recorded 47,894 total traffic crashes, a significant 18.2% decrease from the 58,565 crashes documented in 2019. This overall reduction in collisions was accompanied by an 18.1% drop in injuries. The most notable year-over-year shift was a divergence in lethality: despite the sharp decline in total crashes, the number of fatalities increased slightly from 337 in 2019 to 343 in 2020.

47,894

▼ -18.2%was 58,565

Total Crash Events

343

▲ 1.8%was 337

Persons Killed

15,239

▼ -18.1%was 18,605

Persons Injured

310

▼ -1.3%was 314

Fatal Crash Events

Note: "Persons Killed" (343) counts individual fatalities across all crash events. "Fatal" in the severity table below (310) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Statewide crash data indicates a clear downward trend in the overall volume of collisions. Total crashes fell by 18.2% from 58,565 in 2019 to 47,894 in 2020. Similarly, the number of people injured in these incidents decreased by 18.1%, from 18,605 to 15,239. However, this trend did not extend to fatalities, which saw a 1.8% increase from 337 to 343 deaths year-over-year.

Vulnerable Road User Casualties

30

Pedestrians Killed

Prior: 21↑42.9%

10

Cyclists Killed

Prior: 10→0.0%

303

Motorists Killed

Prior: 305↓-0.7%

0

Other Killed

Prior: 1↓-100.0%

322

Pedestrians Injured

Prior: 333↓-3.3%

216

Cyclists Injured

Prior: 329↓-34.3%

14,667

Motorists Injured

Prior: 17,914↓-18.1%

34

Other Injured

Prior: 29↑17.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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 between the two periods, with Friday serving as the peak day for crashes and the 5 p.m. hour as the peak time in both 2019 and 2020. While the peak times did not shift, the volume of crashes during these peaks decreased, with Friday crashes falling from 9,659 to 8,147. A notable seasonal change occurred in the spring of 2020, with crash counts in March (2,989) and April (2,368) being substantially lower than in March (4,049) and April (4,026) of 2019.

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the absolute number of crashes decreased across nearly all severity levels, the overall severity of crashes that did occur increased in 2020. The proportion of crashes resulting in a fatality grew from 0.5% of all crashes in 2019 to 0.6% in 2020. Similarly, the share of crashes involving serious injuries increased from 1.9% to 2.3% year-over-year. Conversely, the proportion of crashes with no injuries decreased from 73.1% in 2019 to 71.8% in 2020.

Severity is per crash event (most severe injury). 310 fatal crash events resulted in 343 persons killed.

Outcome by Severity (Crash Events)

Fatal310fatal crashes0.6%
↓-1.3%prior 314
Serious Injury1,100serious injury crashes2.3%
↓-1.9%prior 1,121
Minor Injury4,485minor injury crashes9.4%
↓-12.6%prior 5,132
Possible Injury7,631possible injury crashes15.9%
↓-17.1%prior 9,203
No Injury34,368no injury crashes71.8%
↓-19.7%prior 42,795

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors saw changes in volume and ranking year-over-year. Collisions involving an "Animal" remained the top factor in both periods, though the count decreased from 7,898 in 2019 to 7,277 in 2020. Significant reductions were seen in crashes attributed to "Followed too close," which fell from 6,049 to 4,187 incidents, and "Driving too fast for conditions," with a count that dropped from 4,100 to 2,585. As a result of this drop, "Driving too fast for conditions" fell from the third-ranked factor in 2019 to the sixth in 2020.

Officer-Reported Primary Contributing Cause

Animal7,277 (15.2%)↓-7.9%prior 7,898
Followed too close4,187 (8.7%)↓-30.8%prior 6,049
Ran off road - left3,132 (6.5%)↓-20.4%prior 3,937
Lost Control2,753 (5.7%)↓-11.4%prior 3,108
Other (explain in narrative): Other2,634 (5.5%)↓-27.0%prior 3,606
Driving too fast for conditions2,585 (5.4%)↓-37.0%prior 4,100
FTYROW: From stop sign2,279 (4.8%)↓-23.6%prior 2,984
FTYROW: Making left turn1,832 (3.8%)↓-24.8%prior 2,436
Ran off road - straight1,728 (3.6%)↓-13.6%prior 1,999
Ran Traffic Signal1,633 (3.4%)↓-11.0%prior 1,834

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The conditions under which crashes occurred shifted between the two periods. In 2020, a smaller proportion of crashes happened on adverse road surfaces like wet, snowy, or icy roads (20.6% of total) compared to 2019 (27.9%). Conversely, the share of crashes occurring in dark conditions (including both lighted and unlighted roadways) increased from 22.8% in 2019 to 25.0% in 2020. Crashes on dry roads also made up a larger share of the total, rising from 59.6% in 2019 to 65.1% in 2020.

Weather

Clear28,435 (67.8%)
↓-11.5%prior 32,137
Cloudy7,506 (17.9%)
↓-33.7%prior 11,325
Rain2,095 (5.0%)
↓-27.5%prior 2,890
Snow2,073 (4.9%)
↓-31.3%prior 3,016
Freezing rain/drizzle911 (2.2%)
↓-19.4%prior 1,130
Blowing Snow370 (0.9%)
↓-59.9%prior 923
Fog, smoke, smog257 (0.6%)
↓-20.2%prior 322
Severe Winds145 (0.3%)
↓-19.4%prior 180
Other (explain in narrative)71 (0.2%)
↓-11.3%prior 80
Sleet, hail63 (0.2%)
↓-27.6%prior 87

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Weather condition at time of crash

Lighting

Daylight28,064 (66.7%)
↓-23.1%prior 36,487
Dark - roadway lighted6,593 (15.7%)
↓-10.7%prior 7,386
Dark - roadway not lighted5,184 (12.3%)
↓-10.3%prior 5,781
Dusk1,159 (2.8%)
↓-12.1%prior 1,319
Dawn889 (2.1%)
↓-20.4%prior 1,117
Dark - unknown roadway lighting198 (0.5%)
↓-2.0%prior 202

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Lighting condition field

Road Surface

Dry31,175 (74.2%)
↓-10.7%prior 34,925
Wet4,710 (11.2%)
↓-30.6%prior 6,790
Snow2,318 (5.5%)
↓-49.3%prior 4,574
Ice/frost2,292 (5.5%)
↓-45.8%prior 4,229
Gravel831 (2.0%)
↑16.2%prior 715
Slush541 (1.3%)
↓-26.5%prior 736
Mud, dirt71 (0.2%)
↓-16.5%prior 85
Other (explain in narrative)58 (0.1%)
↓-19.4%prior 72
Sand15 (0.0%)
↓-50.0%prior 30
Water (standing or moving)8 (0.0%)
↓-20.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Road surface condition field

Vehicles & Demographics

The types of vehicles most frequently involved in crashes remained consistent, with Ford and Chevrolet models topping the list in both 2019 and 2020, though the counts for each make decreased in line with the overall trend. The demographic profile of persons involved in crashes also showed little change. The proportional involvement of different age groups, such as the 16-20 and 21-25 age brackets, was stable year-over-year. There was a slight increase in the proportion of males involved, from 56.6% of persons with known gender in 2019 to 58.9% in 2020.

Top Vehicle Makes (80,167 vehicles)

1
FORD12,845 (16%)
↓-21.7%prior 16,407
2
CHEV10,060 (12.5%)
↓-23.9%prior 13,212
3
CHEVROLET5,896 (7.4%)
↓-10.8%prior 6,613
4
TOYT3,175 (4%)
↓-31.8%prior 4,658
5
DODG3,060 (3.8%)
↓-24.1%prior 4,033
6
JEEP3,052 (3.8%)
↓-14.4%prior 3,565
7
GMC2,659 (3.3%)
↓-15.5%prior 3,145
8
NR2,450 (3.1%)
↓-15.5%prior 2,901
9
HOND2,438 (3%)
↓-25.5%prior 3,274
10
DODGE2,092 (2.6%)
↓-10.7%prior 2,343

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · Vehicle unit records

15,027 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (71,350 persons with recorded sex)

Male42,041 (58.9%)
↓-18.1%prior 51,340
Female29,309 (41.1%)
↓-25.5%prior 39,331

Source: Iowa Crash Data · ArcGIS Open Data · 2020-01-01 to 2020-12-31 · 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: 2020-01-01 through 2020-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 47,894
  • Total persons involved: 109,099
  • Total vehicles involved: 80,167

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: 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2020-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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