Yearly Traffic Safety Analysis

2,138 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Pottawattamie County recorded 2,138 total crashes, a 12.9% increase from the 1,894 crashes reported in 2020. Despite the rise in total incidents, the number of fatalities decreased from 12 to 10 year-over-year. A notable shift occurred in the primary contributing factors, where crashes attributed to 'Followed too close' increased by 34.7% from 216 incidents in 2020 to 291 in 2021.

2,138

▲ 12.9%was 1,894

Total Crash Events

10

▼ -16.7%was 12

Persons Killed

694

▲ 3.4%was 671

Persons Injured

10

▼ -16.7%was 12

Fatal Crash Events

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Pottawattamie County increased by 12.9% from 2020 to 2021, rising from 1,894 to 2,138 incidents. Total injuries saw a slight increase of 3.4% (from 671 to 694). However, fatalities declined from 12 in the prior period to 10 in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 3↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

10

Motorists Killed

Prior: 9↑11.1%

0

Other Killed

Prior: 0→0.0%

17

Pedestrians Injured

Prior: 14↑21.4%

6

Cyclists Injured

Prior: 12↓-50.0%

670

Motorists Injured

Prior: 645↑3.9%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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 broadly consistent year-over-year. Friday continued to be the peak day for crashes in both 2021 (431 incidents) and 2020 (300 incidents). The peak hour for crashes shifted slightly from the 3 p.m. hour in 2020 (152 crashes) to the 4 p.m. hour in 2021 (169 crashes), with the afternoon commute hours consistently showing the highest crash volumes in both periods.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted between the two periods, with a decrease in the most severe outcomes. The number of fatal crashes decreased from 12 in 2020 to 10 in 2021, and the share of crashes resulting in serious injuries fell from 2.9% to 1.6%. Consequently, the proportion of crashes resulting in no injuries increased from 67.5% in the prior year to 70.0% in the current year.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.5%
↓-16.7%prior 12
Serious Injury35serious injury crashes1.6%
↓-35.2%prior 54
Minor Injury175minor injury crashes8.2%
↑10.8%prior 158
Possible Injury421possible injury crashes19.7%
↑7.7%prior 391
No Injury1,497no injury crashes70%
↑17.0%prior 1,279

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw shifts in volume and ranking year-over-year. 'Followed too close' remained the top factor, with its count increasing by 34.7% from 216 in 2020 to 291 in 2021. 'Ran off road - left' moved from the third to the second-ranked factor, with its count increasing from 148 to 190. Conversely, collisions involving an 'Animal' decreased from 157 to 143 incidents, dropping this factor from second to third place in the rankings.

Officer-Reported Primary Contributing Cause

Followed too close291 (13.6%)↑34.7%prior 216
Ran off road - left190 (8.9%)↑28.4%prior 148
Animal143 (6.7%)↓-8.9%prior 157
Lost Control119 (5.6%)↓-7.8%prior 129
FTYROW: From stop sign101 (4.7%)↑31.2%prior 77
Ran off road - straight98 (4.6%)→0.0%prior 98
Driving too fast for conditions95 (4.4%)↑28.4%prior 74
Ran Stop Sign91 (4.3%)↓-6.2%prior 97
Ran Traffic Signal89 (4.2%)↑9.9%prior 81
Made improper turn77 (3.6%)↑37.5%prior 56

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both years occurred in ideal driving conditions. In 2021, the proportion of crashes on dry roads increased to 74.9% from 72.3% in 2020, and the share of crashes in daylight rose to 63.2% from 61.8%. Correspondingly, the proportion of incidents taking place in adverse weather conditions like rain or snow saw a slight decrease, as did crashes on wet or icy surfaces.

Weather

Clear1,495 (74.4%)
↑19.1%prior 1,255
Cloudy278 (13.8%)
↑5.3%prior 264
Rain91 (4.5%)
↑13.8%prior 80
Snow76 (3.8%)
↓-2.6%prior 78
Freezing rain/drizzle30 (1.5%)
↓-11.8%prior 34
Blowing Snow22 (1.1%)
↑22.2%prior 18
Severe Winds9 (0.4%)
↑80.0%prior 5
Fog, smoke, smog5 (0.2%)
↓-44.4%prior 9
Other (explain in narrative)2 (0.1%)
Blowing sand, soil, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight1,352 (66.7%)
↑15.5%prior 1,171
Dark - roadway lighted372 (18.4%)
↑20.8%prior 308
Dark - roadway not lighted178 (8.8%)
↓-3.8%prior 185
Dusk75 (3.7%)
↑44.2%prior 52
Dawn37 (1.8%)
↑8.8%prior 34
Dark - unknown roadway lighting12 (0.6%)
↑50.0%prior 8

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry1,601 (79.5%)
↑16.9%prior 1,370
Wet193 (9.6%)
↓-1.5%prior 196
Ice/frost103 (5.1%)
↑41.1%prior 73
Snow87 (4.3%)
↑8.8%prior 80
Gravel18 (0.9%)
↑20.0%prior 15
Slush5 (0.2%)
↓-72.2%prior 18
Mud, dirt2 (0.1%)
Sand1 (0.0%)
Other (explain in narrative)1 (0.0%)
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

The demographic profile of persons involved in crashes showed some changes, with the 16-20 age group increasing from 458 to 548 individuals and the 26-34 age group increasing from 619 to 720. The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models representing the highest volumes in both 2020 and 2021. The number of vehicles from these top makes involved in crashes increased, in line with the overall rise in total incidents.

Top Vehicle Makes (3,729 vehicles)

1
FORD566 (15.2%)
↑17.7%prior 481
2
CHEVROLET367 (9.8%)
↑23.2%prior 298
3
CHEV281 (7.5%)
↓-1.1%prior 284
4
NR172 (4.6%)
↑19.4%prior 144
5
JEEP157 (4.2%)
↑36.5%prior 115
6
NISSAN148 (4%)
↑52.6%prior 97
7
KIA136 (3.6%)
↑9.7%prior 124
8
DODGE125 (3.4%)
↑16.8%prior 107
9
TOYOTA122 (3.3%)
↑29.8%prior 94
10
HONDA105 (2.8%)
↑32.9%prior 79

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (2,947 persons with recorded sex)

Male1,730 (58.7%)
↑5.2%prior 1,644
Female1,217 (41.3%)
↑12.4%prior 1,083

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 2,138
  • Total persons involved: 4,612
  • Total vehicles involved: 3,729

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-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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