Yearly Traffic Safety Analysis

224 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Washington County, total traffic crashes increased by 12.6% from 199 in 2020 to 224 in 2021. While total fatalities remained stable at two, the number of crashes involving serious injuries increased. The most notable year-over-year shift was in contributing factors, where crashes attributed to failure to yield from a stop sign surged from 7 incidents to 26.

224

▲ 12.6%was 199

Total Crash Events

2

Persons Killed

96

▲ 10.3%was 87

Persons Injured

2

▲ 100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 data for Washington County indicates a rising trend in collisions. The total number of crashes increased from 199 in 2020 to 224 in 2021, a 12.6% year-over-year rise. This increase was mirrored by a 10.3% growth in total injuries, which climbed from 87 to 96 over the same period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

0

Pedestrians Injured

Prior: 1↓-100.0%

1

Cyclists Injured

Prior: 2↓-50.0%

95

Motorists Injured

Prior: 84↑13.1%

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 shifted between the two years. In 2021, the peak day for crashes was Friday with 44 incidents, a change from 2020 when Wednesday was the peak day with 37 crashes. The peak hour also moved from the 5 p.m. slot in 2020 (20 crashes) to the 10 a.m. hour in 2021 (22 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 crash outcomes worsened in 2021 compared to the prior year. The number of fatal crashes doubled from one to two, and the count of serious injury crashes increased from 10 to 14. Crashes resulting in possible injuries decreased from 33 to 29, while no-injury crashes increased from 123 to 147.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.9%
↑100.0%prior 1
Serious Injury14serious injury crashes6.3%
↑40.0%prior 10
Minor Injury32minor injury crashes14.3%
→0.0%prior 32
Possible Injury29possible injury crashes12.9%
↓-12.1%prior 33
No Injury147no injury crashes65.6%
↑19.5%prior 123

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

There was a significant change in the leading contributing factors for crashes year-over-year. The factor 'FTYROW: From stop sign' saw its crash count increase from 7 in 2020 to 26 in 2021, a 271% rise that made it the top factor. In contrast, crashes involving animals, which was the top factor in 2020 with 25 incidents, decreased by 60% to 10 incidents in 2021.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign26 (11.6%)↑271.4%prior 7
Driving too fast for conditions21 (9.4%)↑16.7%prior 18
Ran Stop Sign20 (8.9%)↑17.6%prior 17
Lost Control20 (8.9%)↑33.3%prior 15
Followed too close15 (6.7%)↑7.1%prior 14
Other (explain in narrative): Other10 (4.5%)
Animal10 (4.5%)↓-60.0%prior 25
Driver Distraction: Other interior distraction9 (4%)↓-25.0%prior 12
Ran off road - straight9 (4%)↑80.0%prior 5
FTYROW: Making left turn8 (3.6%)↑60.0%prior 5

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

Road & Environmental Conditions

Compared to the previous year, a greater proportion of crashes in 2021 occurred in clear conditions. Crashes during daylight hours increased from representing 58.3% of the total in 2020 to 70.1% in 2021. Similarly, the share of crashes on dry road surfaces rose from 68.3% to 73.7%, while the proportion of crashes in adverse weather remained stable at approximately 28%.

Weather

Clear162 (73.0%)
↑13.3%prior 143
Cloudy27 (12.2%)
↑35.0%prior 20
Snow9 (4.1%)
→0.0%prior 9
Blowing Snow6 (2.7%)
Fog, smoke, smog6 (2.7%)
Rain6 (2.7%)
↓-45.5%prior 11
Freezing rain/drizzle5 (2.3%)
↓-16.7%prior 6
Severe Winds1 (0.5%)

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

Lighting

Daylight157 (71.0%)
↑35.3%prior 116
Dark - roadway not lighted28 (12.7%)
↓-36.4%prior 44
Dark - roadway lighted23 (10.4%)
↑76.9%prior 13
Dawn7 (3.2%)
↓-12.5%prior 8
Dusk4 (1.8%)
↓-50.0%prior 8
Dark - unknown roadway lighting2 (0.9%)

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

Road Surface

Dry165 (74.3%)
↑21.3%prior 136
Wet18 (8.1%)
→0.0%prior 18
Ice/frost15 (6.8%)
→0.0%prior 15
Snow13 (5.9%)
Slush6 (2.7%)
→0.0%prior 6
Gravel5 (2.3%)
↓-64.3%prior 14

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

Vehicles & Demographics

The age distribution of individuals involved in crashes showed notable changes. The number of persons in the 65+ age group increased from 50 in 2020 to 74 in 2021, and involvement for the 21-25 age group grew from 31 to 53 persons. The top vehicle makes involved in collisions, led by Chevrolet and Ford, remained consistent in ranking across both periods, with their counts increasing in line with the overall rise in crashes.

Top Vehicle Makes (382 vehicles)

1
FORD62 (16.2%)
↑40.9%prior 44
2
CHEV56 (14.7%)
↑55.6%prior 36
3
CHEVROLET40 (10.5%)
↑66.7%prior 24
4
GMC21 (5.5%)
↑110.0%prior 10
5
DODG12 (3.1%)
↓-14.3%prior 14
6
HOND12 (3.1%)
↑33.3%prior 9
7
TOYT11 (2.9%)
→0.0%prior 11
8
TOYOTA10 (2.6%)
↑42.9%prior 7
9
DODGE9 (2.4%)
↓-25.0%prior 12
10
JEEP8 (2.1%)
↑33.3%prior 6

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

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

Sex Distribution (316 persons with recorded sex)

Male188 (59.5%)
↑0.5%prior 187
Female128 (40.5%)
↑37.6%prior 93

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: 224
  • Total persons involved: 465
  • Total vehicles involved: 382

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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