Yearly Traffic Safety Analysis

226 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Washington County recorded 226 total crashes, a marginal increase from the 224 crashes documented in 2021. While overall crash volume remained stable, the number of fatalities rose from 2 to 3. A notable year-over-year shift occurred in crashes involving animals, which increased by 160% from 10 incidents in 2021 to 26 in 2022, becoming the leading contributing factor.

226

▲ 0.9%was 224

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

80

▼ -16.7%was 96

Persons Injured

3

▲ 50.0%was 2

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Washington County remained relatively stable, increasing by just under 1% from 224 incidents in 2021 to 226 in 2022. However, the outcomes of these crashes shifted, with total injuries decreasing by 16.7% from 96 to 80. In contrast, the number of fatalities increased from 2 in 2021 to 3 in 2022.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

2

Cyclists Injured

Prior: 1↑100.0%

78

Motorists Injured

Prior: 95↓-17.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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 a distinct shift in the peak hour of activity between the two periods. In 2022, the most crashes occurred during the 5 PM hour with 26 incidents, moving from the 10 AM peak (22 crashes) observed in 2021. The peak day for crashes remained consistent, with Friday being the most frequent day for collisions in both 2022 (40 crashes) and 2021 (44 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted year-over-year, with an increase in both fatal and no-injury collisions. In 2022, there were 3 fatal crashes, up from 2 in 2021, representing a rise in the fatal crash share from 0.9% to 1.3%. While fatal crashes increased, the proportion of serious injury crashes decreased from 6.3% to 4.0%. Conversely, crashes resulting in no injury became more common, increasing their share of all incidents from 65.6% in 2021 to 71.7% in 2022.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.3%
↑50.0%prior 2
Serious Injury9serious injury crashes4%
↓-35.7%prior 14
Minor Injury36minor injury crashes15.9%
↑12.5%prior 32
Possible Injury16possible injury crashes7.1%
↓-44.8%prior 29
No Injury162no injury crashes71.7%
↑10.2%prior 147

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes changed significantly between 2021 and 2022. Collisions involving an animal became the top factor in 2022, with the count of such incidents increasing by 160% from 10 to 26. In contrast, 'Failure to yield from a stop sign,' the top factor in 2021 with 26 crashes, saw its count decrease by 26.9% to 19 crashes in 2022. Similarly, crashes attributed to 'Driving too fast for conditions' fell from 21 to 13, while incidents of 'Ran Stop Sign' increased from 20 to 23.

Officer-Reported Primary Contributing Cause

Animal26 (11.5%)↑160.0%prior 10
Ran Stop Sign23 (10.2%)↑15.0%prior 20
FTYROW: From stop sign19 (8.4%)↓-26.9%prior 26
Followed too close18 (8%)↑20.0%prior 15
Operating vehicle in an reckless, erratic, careless, negligent manner13 (5.8%)
Other (explain in narrative): Other13 (5.8%)↑30.0%prior 10
Driving too fast for conditions13 (5.8%)↓-38.1%prior 21
Lost Control13 (5.8%)↓-35.0%prior 20
Driver Distraction: Other interior distraction9 (4%)→0.0%prior 9
Ran off road - left8 (3.5%)↑14.3%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and daylight on dry roads. However, there was a shift in the proportion of crashes under these ideal conditions, with daylight crashes decreasing from 70.1% of the total in 2021 to 65.0% in 2022. Correspondingly, crashes on dark, unlit roadways increased their share from 12.5% to 14.2%. The share of crashes on adverse road surfaces like wet or icy roads saw a slight decrease.

Weather

Clear147 (70.0%)
↓-9.3%prior 162
Cloudy37 (17.6%)
↑37.0%prior 27
Snow9 (4.3%)
→0.0%prior 9
Rain6 (2.9%)
→0.0%prior 6
Freezing rain/drizzle5 (2.4%)
→0.0%prior 5
Blowing Snow4 (1.9%)
↓-33.3%prior 6
Severe Winds1 (0.5%)
Fog, smoke, smog1 (0.5%)
↓-83.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight147 (70.0%)
↓-6.4%prior 157
Dark - roadway not lighted32 (15.2%)
↑14.3%prior 28
Dark - roadway lighted20 (9.5%)
↓-13.0%prior 23
Dusk8 (3.8%)
Dawn2 (1.0%)
↓-71.4%prior 7
Dark - unknown roadway lighting1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry165 (78.2%)
→0.0%prior 165
Snow13 (6.2%)
→0.0%prior 13
Wet13 (6.2%)
↓-27.8%prior 18
Ice/frost12 (5.7%)
↓-20.0%prior 15
Gravel5 (2.4%)
→0.0%prior 5
Slush2 (0.9%)
↓-66.7%prior 6
Mud, dirt1 (0.5%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

An analysis of vehicles involved in crashes shows that Chevrolet and Ford were the top two makes in both 2022 and 2021, though both saw a slight decrease in their total crash involvement. The most significant change was for RAM vehicles, which were involved in 14 crashes in 2022, up from 5 in the prior year. When examining the age of persons involved, there was a notable increase in the 26-34 age group, which grew from 51 individuals in 2021 to 84 in 2022. The 65+ age group also saw an increase in involvement, from 74 to 86 persons.

Top Vehicle Makes (385 vehicles)

1
CHEV69 (17.9%)
↑23.2%prior 56
2
FORD56 (14.5%)
↓-9.7%prior 62
3
CHEVROLET24 (6.2%)
↓-40.0%prior 40
4
GMC18 (4.7%)
↓-14.3%prior 21
5
HOND15 (3.9%)
↑25.0%prior 12
6
BUIC15 (3.9%)
↑87.5%prior 8
7
TOYT14 (3.6%)
↑27.3%prior 11
8
RAM14 (3.6%)
↑180.0%prior 5
9
DODG12 (3.1%)
→0.0%prior 12
10
CHRY11 (2.9%)
↑120.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (352 persons with recorded sex)

Male203 (57.7%)
↑8.0%prior 188
Female149 (42.3%)
↑16.4%prior 128

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 226
  • Total persons involved: 508
  • Total vehicles involved: 385

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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

ThatCarHitMe.com · An Injuria.ai Company