Yearly Traffic Safety Analysis

490 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Sioux County recorded 490 total crashes, a 10.6% increase from the 443 crashes documented in 2020. While the number of fatalities remained stable at 3, the number of persons injured rose by 29.7%, from 158 in 2020 to 205 in 2021. The most significant change was a 55.6% increase in crashes resulting in serious injuries.

490

▲ 10.6%was 443

Total Crash Events

3

Persons Killed

205

▲ 29.7%was 158

Persons Injured

3

Fatal Crash Events

Note: "Persons Killed" (3) 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

Crash trends in Sioux County showed an upward movement year-over-year. Total crashes increased by 10.6%, rising from 443 in 2020 to 490 in 2021. This was accompanied by a more significant 29.7% rise in total injuries, from 158 to 205, while fatalities held steady at 3 for both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

1

Cyclists Killed

Prior: 0→%

2

Motorists Killed

Prior: 2→0.0%

2

Pedestrians Injured

Prior: 2→0.0%

0

Cyclists Injured

Prior: 2↓-100.0%

203

Motorists Injured

Prior: 154↑31.8%

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 showed some shifts between the two years. While Friday remained the peak day for crashes in both 2021 (91 crashes) and 2020 (85 crashes), the peak hour moved earlier. In 2021, the highest number of crashes occurred during the 3 p.m. hour (45 crashes), a shift from the 5 p.m. peak observed in 2020 (46 crashes).

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 toward more serious outcomes in 2021. While the number of fatal crashes was unchanged at 3, the count of serious injury crashes increased from 9 to 14, and their share of all crashes grew from 2.0% to 2.9%. Minor injury crashes also increased in both count (from 55 to 73) and proportion (from 12.4% to 14.9%). Conversely, crashes involving only possible injuries decreased from 70 to 63 incidents.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
→0.0%prior 3
Serious Injury14serious injury crashes2.9%
↑55.6%prior 9
Minor Injury73minor injury crashes14.9%
↑32.7%prior 55
Possible Injury63possible injury crashes12.9%
↓-10.0%prior 70
No Injury337no injury crashes68.8%
↑10.1%prior 306

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

Collisions involving an animal remained the leading contributing factor in both periods, with counts rising from 90 in 2020 to 100 in 2021. The most significant change was in crashes attributed to 'Followed too close,' which increased in count by 73.3% from 45 incidents to 78, raising its share of all crashes from 10.2% to 15.9%. Conversely, crashes due to 'Driving too fast for conditions' decreased in count by 31.7%, falling from 41 to 28 incidents.

Officer-Reported Primary Contributing Cause

Animal100 (20.4%)↑11.1%prior 90
Followed too close78 (15.9%)↑73.3%prior 45
FTYROW: From stop sign42 (8.6%)↑27.3%prior 33
Driving too fast for conditions28 (5.7%)↓-31.7%prior 41
Ran off road - left27 (5.5%)↑35.0%prior 20
Lost Control22 (4.5%)↓-21.4%prior 28
Ran off road - straight19 (3.9%)↓-9.5%prior 21
FTYROW: At uncontrolled intersection16 (3.3%)↓-5.9%prior 17
Ran Stop Sign15 (3.1%)↑15.4%prior 13
Other (explain in narrative): Other13 (2.7%)↑62.5%prior 8

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 conditions under which crashes occurred varied between the two periods. In 2021, a larger proportion of crashes happened on dry roads (58.8%) compared to 2020 (48.5%). Correspondingly, the share of crashes on roads with snow or ice decreased from 19.6% in 2020 to 11.8% in 2021. Crashes in daylight conditions made up a slightly larger share of the total in 2021 (58.2%) than in the prior year (56.4%).

Weather

Clear266 (67.2%)
↑26.7%prior 210
Cloudy85 (21.5%)
↑2.4%prior 83
Rain14 (3.5%)
↓-22.2%prior 18
Snow11 (2.8%)
↓-42.1%prior 19
Blowing Snow7 (1.8%)
↓-30.0%prior 10
Freezing rain/drizzle4 (1.0%)
↓-69.2%prior 13
Severe Winds4 (1.0%)
Fog, smoke, smog4 (1.0%)
Other (explain in narrative)1 (0.3%)

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

Lighting

Daylight285 (72.0%)
↑14.0%prior 250
Dark - roadway not lighted54 (13.6%)
↓-8.5%prior 59
Dark - roadway lighted36 (9.1%)
↑12.5%prior 32
Dawn11 (2.8%)
↑57.1%prior 7
Dusk9 (2.3%)
↓-18.2%prior 11
Dark - unknown roadway lighting1 (0.3%)

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

Road Surface

Dry288 (72.5%)
↑34.0%prior 215
Snow29 (7.3%)
↓-38.3%prior 47
Ice/frost29 (7.3%)
↓-27.5%prior 40
Wet25 (6.3%)
↓-26.5%prior 34
Gravel20 (5.0%)
↑11.1%prior 18
Slush5 (1.3%)
Other (explain in narrative)1 (0.3%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, including Ford and Chevrolet, maintained their leading positions in both years, with counts increasing in line with the overall rise in crashes. A notable demographic shift occurred among persons involved in collisions. The 16-20 age group saw its involvement increase from 176 individuals in 2020 to 215 in 2021, making it the most represented age bracket. In contrast, the 35-44 age group's count decreased from 130 to 118.

Top Vehicle Makes (780 vehicles)

1
FORD151 (19.4%)
↑20.8%prior 125
2
CHEV110 (14.1%)
↑5.8%prior 104
3
CHEVROLET81 (10.4%)
↑28.6%prior 63
4
GMC35 (4.5%)
↑2.9%prior 34
5
DODG31 (4%)
↑6.9%prior 29
6
JEEP24 (3.1%)
→0.0%prior 24
7
BUIC21 (2.7%)
↑10.5%prior 19
8
HOND20 (2.6%)
↑17.6%prior 17
9
DODGE20 (2.6%)
↑25.0%prior 16
10
TOYT17 (2.2%)
↓-5.6%prior 18

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

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

Sex Distribution (631 persons with recorded sex)

Male373 (59.1%)
↓-9.5%prior 412
Female258 (40.9%)
↑7.5%prior 240

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: 490
  • Total persons involved: 1,009
  • Total vehicles involved: 780

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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