Yearly Traffic Safety Analysis

2,255 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Woodbury County recorded 2,255 total crashes, an increase of 3.9% from the 2,170 crashes documented in 2020. While total collisions and injuries (754, up from 708) rose, the number of fatalities decreased from 10 to 8 year-over-year. The most notable shift in contributing factors was a 40.5% increase in crashes attributed to 'Followed too close,' which grew from 195 incidents in 2020 to 274 in 2021.

2,255

▲ 3.9%was 2,170

Total Crash Events

8

▼ -20.0%was 10

Persons Killed

754

▲ 6.5%was 708

Persons Injured

8

▼ -11.1%was 9

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 safety metrics in Woodbury County showed a mixed but generally worsening trend in 2021 compared to the prior year. Total collisions increased by 3.9% from 2,170 to 2,255, and the number of people injured rose by 6.5% from 708 to 754. However, the number of fatalities resulting from these crashes declined from 10 in 2020 to 8 in 2021.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

0

Cyclists Killed

Prior: 0→0.0%

7

Motorists Killed

Prior: 9↓-22.2%

15

Pedestrians Injured

Prior: 16↓-6.3%

13

Cyclists Injured

Prior: 6↑116.7%

726

Motorists Injured

Prior: 685↑6.0%

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 timing of crashes in Woodbury County showed strong consistency year-over-year. Friday remained the peak day for collisions in both periods, with 373 crashes in 2021 compared to 379 in 2020. The 3 PM hour was also the consistent peak time for crashes, though the volume during that hour decreased from 240 incidents in 2020 to 196 in 2021.

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

While the total number of crashes increased, the overall severity profile saw a slight improvement. The fatal crash rate decreased from 0.41% in 2020 to 0.35% in 2021, with one fewer fatal crash (8 vs. 9). Crashes resulting in serious injuries also declined from 36 to 28. Conversely, the number and proportion of crashes involving 'possible' injuries increased from 447 (20.6% of total) to 494 (21.9% of total).

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.4%
↓-11.1%prior 9
Serious Injury28serious injury crashes1.2%
↓-22.2%prior 36
Minor Injury200minor injury crashes8.9%
↑2.0%prior 196
Possible Injury494possible injury crashes21.9%
↑10.5%prior 447
No Injury1,525no injury crashes67.6%
↑2.9%prior 1,482

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 primary causes of crashes shifted between 2020 and 2021. 'Followed too close' remained the top factor, with its count increasing by 40.5% from 195 to 274 incidents. Crashes from a vehicle running off the road to the left increased from 145 to 186, moving this factor from fourth to second place. Meanwhile, incidents attributed to 'Ran Traffic Signal' decreased by 24.7%, from 146 to 110, and 'FTYROW: From stop sign' dropped from 166 to 144.

Officer-Reported Primary Contributing Cause

Followed too close274 (12.2%)↑40.5%prior 195
Ran off road - left186 (8.2%)↑28.3%prior 145
Other (explain in narrative): Other159 (7.1%)↑20.5%prior 132
Animal149 (6.6%)↑10.4%prior 135
FTYROW: From stop sign144 (6.4%)↓-13.3%prior 166
FTYROW: Making left turn119 (5.3%)↑14.4%prior 104
Lost Control111 (4.9%)↑0.9%prior 110
Ran Traffic Signal110 (4.9%)↓-24.7%prior 146
Driving too fast for conditions95 (4.2%)↓-18.1%prior 116
Ran Stop Sign90 (4%)↑2.3%prior 88

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

Road & Environmental Conditions

Crashes were more likely to occur in clear weather and on dry roads in 2021 compared to 2020. Collisions in clear conditions rose from 1,366 to 1,528, while those on dry surfaces increased from 1,528 to 1,681. Correspondingly, crashes on roads with snow, ice, or slush decreased from 287 to 231. There was a notable increase in crashes occurring after dark on lighted roadways, which grew from 369 incidents to 431.

Weather

Clear1,528 (71.3%)
↑11.9%prior 1,366
Cloudy391 (18.3%)
↓-11.3%prior 441
Snow102 (4.8%)
↓-4.7%prior 107
Rain76 (3.5%)
↑24.6%prior 61
Blowing Snow17 (0.8%)
↓-29.2%prior 24
Freezing rain/drizzle14 (0.7%)
↓-62.2%prior 37
Fog, smoke, smog11 (0.5%)
↑120.0%prior 5
Other (explain in narrative)1 (0.0%)
Severe Winds1 (0.0%)
Sleet, hail1 (0.0%)

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

Lighting

Daylight1,453 (67.8%)
↑0.8%prior 1,442
Dark - roadway lighted431 (20.1%)
↑16.8%prior 369
Dark - roadway not lighted145 (6.8%)
↑5.8%prior 137
Dusk54 (2.5%)
↓-8.5%prior 59
Dawn50 (2.3%)
↑22.0%prior 41
Dark - unknown roadway lighting11 (0.5%)
↑22.2%prior 9

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

Road Surface

Dry1,681 (78.6%)
↑10.0%prior 1,528
Wet214 (10.0%)
↓-2.3%prior 219
Snow136 (6.4%)
↓-12.8%prior 156
Ice/frost66 (3.1%)
↓-29.8%prior 94
Slush29 (1.4%)
↓-21.6%prior 37
Gravel10 (0.5%)
→0.0%prior 10
Other (explain in narrative)2 (0.1%)
Mud, dirt2 (0.1%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes, such as Ford and Chevrolet, remained consistent between 2020 and 2021. Analysis of persons involved reveals a shift in age demographics, with a decrease in the 21-25 age group (from 610 to 528) and a notable increase in the 0-15 age group (from 64 to 106). The proportion of males involved in collisions saw a slight decrease from 57.3% in 2020 to 55.0% in 2021.

Top Vehicle Makes (4,184 vehicles)

1
FORD614 (14.7%)
↑4.2%prior 589
2
CHEVROLET377 (9%)
↑18.2%prior 319
3
CHEV355 (8.5%)
↓-15.1%prior 418
4
JEEP192 (4.6%)
↓-3.5%prior 199
5
GMC181 (4.3%)
↑13.1%prior 160
6
NR168 (4%)
↑1.8%prior 165
7
DODGE144 (3.4%)
↑24.1%prior 116
8
TOYT140 (3.3%)
↑12.0%prior 125
9
KIA137 (3.3%)
↑3.0%prior 133
10
TOYOTA125 (3%)
↑15.7%prior 108

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

1,120 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (3,216 persons with recorded sex)

Male1,770 (55.0%)
↓-9.1%prior 1,947
Female1,446 (45.0%)
↓-0.3%prior 1,450

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: 2,255
  • Total persons involved: 5,250
  • Total vehicles involved: 4,184

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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