Yearly Traffic Safety Analysis

1,620 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Story County, total crashes increased by 34.0% from 1,209 in 2020 to 1,620 in 2021. This rise was accompanied by a 41.0% increase in total injuries, from 310 to 437, and a doubling of fatalities from 2 to 4. The most notable shift was the 56.6% increase in crashes attributed to 'Followed too close', which became the leading contributing factor in 2021.

1,620

▲ 34.0%was 1,209

Total Crash Events

4

▲ 100.0%was 2

Persons Killed

437

▲ 41.0%was 310

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (4) 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 · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Story County showed a significant upward trend, increasing 34.0% from 1,209 incidents in 2020 to 1,620 in 2021. This increase in crash volume corresponded with a rise in severity, as total injuries grew by 41.0% from 310 to 437, and fatalities doubled from 2 to 4 year-over-year.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 2→0.0%

0

Other Killed

Prior: 0→0.0%

12

Pedestrians Injured

Prior: 12→0.0%

17

Cyclists Injured

Prior: 8↑112.5%

407

Motorists Injured

Prior: 290↑40.3%

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 distribution of crashes remained consistent year-over-year. Friday was the day with the most crashes in both 2020 (263 crashes) and 2021 (321 crashes). Similarly, the 5 PM hour remained the peak time for incidents in both periods, with counts rising from 121 to 143. The overall pattern of crashes did not shift, though the volume at peak times increased.

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 number of fatal crashes increased from 2 in 2020 to 3 in 2021, and the number of persons killed doubled from 2 to 4. While the rate of fatal crashes as a share of all incidents was stable at 0.2%, the proportion of crashes involving any injury rose from 22.0% in 2020 to 23.7% in 2021. The count of serious injury crashes increased from 27 to 30, and minor injury crashes grew from 88 to 137.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.2%
↑50.0%prior 2
Serious Injury30serious injury crashes1.9%
↑11.1%prior 27
Minor Injury137minor injury crashes8.5%
↑55.7%prior 88
Possible Injury213possible injury crashes13.1%
↑43.9%prior 148
No Injury1,237no injury crashes76.4%
↑31.0%prior 944

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

In 2021, 'Followed too close' became the primary contributing factor, displacing 'Animal' from the top position. Crashes attributed to following too closely increased by 56.6% from 159 to 249 incidents. While crashes involving an animal also rose in count from 187 to 204, their rank dropped to second. Failure to yield while making a left turn also saw a notable increase, with related crashes growing 53.4% from 73 to 112.

Officer-Reported Primary Contributing Cause

Followed too close249 (15.4%)↑56.6%prior 159
Animal204 (12.6%)↑9.1%prior 187
FTYROW: Making left turn112 (6.9%)↑53.4%prior 73
Other (explain in narrative): Other98 (6%)↑42.0%prior 69
Driving too fast for conditions95 (5.9%)↑5.6%prior 90
FTYROW: From stop sign67 (4.1%)↑39.6%prior 48
Ran off road - left65 (4%)↑51.2%prior 43
Lost Control62 (3.8%)↑21.6%prior 51
Improper or erratic lane changing60 (3.7%)↑57.9%prior 38
Made improper turn46 (2.8%)↑24.3%prior 37

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 under ideal driving conditions, and this trend was more pronounced in 2021. The proportion of crashes happening on dry road surfaces increased from 61.9% in 2020 to 69.8% in 2021. Similarly, crashes during daylight hours grew from 58.6% to 62.7% of the total, indicating the year-over-year increase in crashes was not primarily driven by a rise in adverse conditions.

Weather

Clear1,023 (70.8%)
↑50.4%prior 680
Cloudy211 (14.6%)
↑22.0%prior 173
Rain66 (4.6%)
↑22.2%prior 54
Snow57 (3.9%)
↓-30.5%prior 82
Freezing rain/drizzle52 (3.6%)
↑108.0%prior 25
Blowing Snow18 (1.2%)
↑12.5%prior 16
Fog, smoke, smog8 (0.6%)
Severe Winds5 (0.3%)
→0.0%prior 5
Other (explain in narrative)4 (0.3%)
Sleet, hail1 (0.1%)

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

Lighting

Daylight1,015 (70.0%)
↑43.4%prior 708
Dark - roadway lighted238 (16.4%)
↑22.1%prior 195
Dark - roadway not lighted137 (9.4%)
↑42.7%prior 96
Dusk32 (2.2%)
↑33.3%prior 24
Dawn22 (1.5%)
↑10.0%prior 20
Dark - unknown roadway lighting7 (0.5%)

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

Road Surface

Dry1,130 (78.1%)
↑51.1%prior 748
Wet125 (8.6%)
↑6.8%prior 117
Ice/frost100 (6.9%)
↑31.6%prior 76
Snow69 (4.8%)
↓-4.2%prior 72
Gravel13 (0.9%)
↓-23.5%prior 17
Slush8 (0.6%)
↓-46.7%prior 15
Other (explain in narrative)1 (0.1%)
Water (standing or moving)1 (0.1%)

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

Vehicles & Demographics

The composition of vehicles involved in crashes remained stable, with Chevrolet, Ford, and Toyota being the top three makes in both 2020 and 2021. The demographic profile of persons involved also showed little change year-over-year. For example, the 16-20 age group represented 17.4% of individuals in both periods, while the 21-25 age group's share increased slightly from 17.2% to 18.6%.

Top Vehicle Makes (2,856 vehicles)

1
FORD474 (16.6%)
↑56.4%prior 303
2
CHEV330 (11.6%)
↑44.7%prior 228
3
TOYT205 (7.2%)
↑29.7%prior 158
4
CHEVROLET192 (6.7%)
↑41.2%prior 136
5
HOND125 (4.4%)
↑8.7%prior 115
6
TOYOTA117 (4.1%)
↑80.0%prior 65
7
JEEP97 (3.4%)
↑2.1%prior 95
8
DODG89 (3.1%)
↑71.2%prior 52
9
NISS82 (2.9%)
↑32.3%prior 62
10
HONDA81 (2.8%)
↑47.3%prior 55

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

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

Sex Distribution (2,391 persons with recorded sex)

Male1,368 (57.2%)
↑28.2%prior 1,067
Female1,023 (42.8%)
↑20.9%prior 846

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: 1,620
  • Total persons involved: 3,401
  • Total vehicles involved: 2,856

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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