Yearly Traffic Safety Analysis

3,178 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Linn County, total traffic crashes decreased by 4.7% from 3,334 in 2021 to 3,178 in 2022. This overall reduction in crashes was accompanied by a 7.0% drop in total injuries, from 1,037 to 965. Despite these decreases, the number of fatalities recorded rose slightly from 13 to 14 year-over-year.

3,178

▼ -4.7%was 3,334

Total Crash Events

14

▲ 7.7%was 13

Persons Killed

965

▼ -6.9%was 1,037

Persons Injured

14

▲ 16.7%was 12

Fatal Crash Events

Note: "Persons Killed" (14) counts individual fatalities across all crash events. "Fatal" in the severity table below (14) 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

The overall trend in traffic incidents in Linn County shows a year-over-year decrease. Total crashes fell from 3,334 in 2021 to 3,178 in 2022, representing a 4.7% reduction. Similarly, the number of people injured in these incidents declined by 7.0% from 1,037 to 965, while total fatalities saw a slight increase from 13 to 14.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

14

Motorists Killed

Prior: 12↑16.7%

0

Other Killed

Prior: 0→0.0%

25

Pedestrians Injured

Prior: 29↓-13.8%

25

Cyclists Injured

Prior: 14↑78.6%

912

Motorists Injured

Prior: 989↓-7.8%

3

Other Injured

Prior: 5↓-40.0%

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

Temporal crash patterns remained highly consistent between 2021 and 2022. Friday was the peak day for crashes in both periods, with 568 incidents in 2022 compared to 602 in 2021. The 4 PM hour was also the consistent peak hour for crashes, accounting for 282 incidents in 2022 and 292 in the prior year, indicating no significant shift in when crashes occurred.

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 proportion of fatal crashes was unchanged, accounting for 0.4% of all incidents in both 2021 and 2022, though the absolute number of fatalities increased from 13 to 14. The share of crashes resulting in serious injuries increased slightly from 1.6% (55 crashes) to 1.9% (61 crashes). Conversely, the proportion of minor injury crashes decreased from 9.4% (312 crashes) in 2021 to 8.3% (263 crashes) in 2022.

Outcome by Severity (Crash Events)

Fatal14fatal crashes0.4%
↑16.7%prior 12
Serious Injury61serious injury crashes1.9%
↑10.9%prior 55
Minor Injury263minor injury crashes8.3%
↓-15.7%prior 312
Possible Injury477possible injury crashes15%
↓-6.8%prior 512
No Injury2,363no injury crashes74.4%
↓-3.3%prior 2,443

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 top three contributing factors remained the same across both years: "Followed too close," "Animal," and "Ran off road - left." The leading factor, "Followed too close," saw its incident count decrease from 429 to 402. A notable year-over-year increase in count was observed for "Driver Distraction: Other interior distraction," which grew from 81 incidents in 2021 to 129 in 2022.

Officer-Reported Primary Contributing Cause

Followed too close402 (12.6%)↓-6.3%prior 429
Animal283 (8.9%)↑0.4%prior 282
Ran off road - left227 (7.1%)↓-19.2%prior 281
FTYROW: Making left turn212 (6.7%)↓-0.9%prior 214
Other (explain in narrative): Other207 (6.5%)↑2.5%prior 202
FTYROW: From stop sign200 (6.3%)↓-4.8%prior 210
Ran Traffic Signal157 (4.9%)↓-3.1%prior 162
Driving too fast for conditions131 (4.1%)↓-16.6%prior 157
Driver Distraction: Other interior distraction129 (4.1%)↑59.3%prior 81
Ran Stop Sign103 (3.2%)→0.0%prior 103

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 distribution of crashes by environmental conditions showed general stability year-over-year. Crashes in daylight (67.5% in 2022 vs. 68.5% in 2021) and on dry roads (72.0% vs. 70.3%) made up the vast majority in both periods. There was a notable decrease in crashes on roads with ice or frost, which fell from 165 incidents in 2021 to 93 in 2022, while crashes on snowy surfaces increased from 131 to 151.

Weather

Clear1,944 (65.9%)
↓-5.2%prior 2,051
Cloudy636 (21.6%)
↓-7.4%prior 687
Rain160 (5.4%)
↓-14.0%prior 186
Snow115 (3.9%)
↑51.3%prior 76
Freezing rain/drizzle40 (1.4%)
↓-11.1%prior 45
Blowing Snow34 (1.2%)
↑70.0%prior 20
Severe Winds11 (0.4%)
↑83.3%prior 6
Other (explain in narrative)4 (0.1%)
↓-50.0%prior 8
Fog, smoke, smog4 (0.1%)
↓-60.0%prior 10
Sleet, hail2 (0.1%)
↓-60.0%prior 5

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

Lighting

Daylight2,144 (72.7%)
↓-6.2%prior 2,285
Dark - roadway lighted499 (16.9%)
↓-0.4%prior 501
Dark - roadway not lighted192 (6.5%)
↑11.0%prior 173
Dusk72 (2.4%)
↓-16.3%prior 86
Dawn38 (1.3%)
↓-13.6%prior 44
Dark - unknown roadway lighting4 (0.1%)
↓-50.0%prior 8

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

Road Surface

Dry2,285 (77.3%)
↓-2.5%prior 2,343
Wet372 (12.6%)
↓-5.3%prior 393
Snow151 (5.1%)
↑15.3%prior 131
Ice/frost93 (3.1%)
↓-43.6%prior 165
Slush29 (1.0%)
↓-6.5%prior 31
Gravel20 (0.7%)
↑17.6%prior 17
Sand3 (0.1%)
↓-62.5%prior 8
Other (explain in narrative)2 (0.1%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes during both periods; Ford-involved incidents decreased from 1,023 to 936 year-over-year. Regarding persons involved, the 65+ age group saw a notable increase in representation, growing from 770 individuals in 2021 to 880 in 2022. In contrast, the number of individuals in the 26-34 age group involved in crashes decreased from 1,210 to 1,148.

Top Vehicle Makes (5,810 vehicles)

1
FORD936 (16.1%)
↓-8.5%prior 1,023
2
CHEV760 (13.1%)
↑9.4%prior 695
3
TOYT514 (8.8%)
↑34.9%prior 381
4
HOND304 (5.2%)
↑28.8%prior 236
5
JEEP242 (4.2%)
↑6.6%prior 227
6
CHEVROLET211 (3.6%)
↓-44.9%prior 383
7
DODG208 (3.6%)
↑14.9%prior 181
8
NISS201 (3.5%)
↑9.8%prior 183
9
GMC184 (3.2%)
↑8.2%prior 170
10
KIA175 (3%)
↓-17.1%prior 211

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

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

Sex Distribution (5,454 persons with recorded sex)

Male3,044 (55.8%)
↑6.2%prior 2,865
Female2,410 (44.2%)
↑2.4%prior 2,354

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: 3,178
  • Total persons involved: 7,337
  • Total vehicles involved: 5,810

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

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