Yearly Traffic Safety Analysis

165 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Allamakee County, total traffic crashes decreased slightly from 170 in 2021 to 165 in 2022, a 2.9% reduction. While the number of fatalities remained unchanged at three, total injuries fell by 8.6% from 58 to 53. The most notable year-over-year shift was in crash causation, where incidents involving animals, the leading factor in both years, decreased by over 31% from 57 to 39 crashes.

165

▼ -2.9%was 170

Total Crash Events

3

Persons Killed

53

▼ -8.6%was 58

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

Trend Summary

The overall crash trend in Allamakee County shows a slight decline year-over-year. Total crashes fell by 2.9% from 170 to 165. This trend included an 8.6% decrease in persons injured (from 58 to 53), while the number of fatalities held steady at three for both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 3→0.0%

1

Pedestrians Injured

Prior: 1→0.0%

52

Motorists Injured

Prior: 56↓-7.1%

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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Tuesday with 30 incidents, a change from 2021 when Thursday was the peak day with 38 crashes. The peak hour also shifted slightly, moving from the 3 p.m. hour (15 crashes) in 2021 to the 5 p.m. hour (16 crashes) in 2022.

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

While the number of fatal crashes remained constant at three in both 2021 and 2022, the distribution of injury severity changed significantly. Crashes resulting in serious injuries dropped from 7 to 1, and minor injury crashes fell from 13 to 8. Conversely, crashes with possible injuries more than doubled, increasing from 19 in 2021 to 39 in 2022.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.8%
→0.0%prior 3
Serious Injury1serious injury crashes0.6%
↓-85.7%prior 7
Minor Injury8minor injury crashes4.8%
↓-38.5%prior 13
Possible Injury39possible injury crashes23.6%
↑105.3%prior 19
No Injury114no injury crashes69.1%
↓-10.9%prior 128

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

Collisions with animals remained the top contributing factor in both years, though the count of such incidents fell by 31.6%, from 57 crashes in 2021 to 39 in 2022. 'Lost Control' was the second-most cited factor in both periods, with a nearly identical count of 26 in 2021 and 25 in 2022. Crashes attributed to 'Ran off road - straight' increased from 6 to 14, becoming the third-most common factor in 2022.

Officer-Reported Primary Contributing Cause

Animal39 (23.6%)↓-31.6%prior 57
Lost Control25 (15.2%)↓-3.8%prior 26
Ran off road - straight14 (8.5%)↑133.3%prior 6
Other (explain in narrative): Other12 (7.3%)↑140.0%prior 5
Driving too fast for conditions8 (4.8%)↓-20.0%prior 10
Driver Distraction: Other interior distraction7 (4.2%)
Driver Distraction: Inattentive/lost in thought6 (3.6%)↓-14.3%prior 7
Ran Stop Sign5 (3%)
Exceeded authorized speed5 (3%)
FTYROW: From stop sign4 (2.4%)

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

Road & Environmental Conditions

Crash conditions remained largely consistent year-over-year, with the majority of incidents in both periods occurring in daylight, during clear weather, and on dry roads. In 2022, 86 crashes (52.1%) happened in daylight, compared to 92 (54.1%) in 2021. Crashes on dry roads accounted for 106 incidents (64.2%) in 2022 versus 109 (64.1%) in 2021, showing no significant shift in the proportion of adverse-condition crashes.

Weather

Clear112 (75.2%)
↓-0.9%prior 113
Cloudy21 (14.1%)
↓-4.5%prior 22
Snow4 (2.7%)
↓-50.0%prior 8
Fog, smoke, smog3 (2.0%)
Freezing rain/drizzle3 (2.0%)
Rain3 (2.0%)
Blowing Snow2 (1.3%)
Other (explain in narrative)1 (0.7%)

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

Lighting

Daylight86 (57.7%)
↓-6.5%prior 92
Dark - roadway not lighted37 (24.8%)
↓-2.6%prior 38
Dark - roadway lighted13 (8.7%)
↑116.7%prior 6
Dawn6 (4.0%)
Dusk4 (2.7%)
↓-42.9%prior 7
Dark - unknown roadway lighting3 (2.0%)

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

Road Surface

Dry106 (70.7%)
↓-2.8%prior 109
Wet14 (9.3%)
↑7.7%prior 13
Ice/frost11 (7.3%)
↑57.1%prior 7
Gravel8 (5.3%)
↓-27.3%prior 11
Snow8 (5.3%)
↓-27.3%prior 11
Sand2 (1.3%)
Slush1 (0.7%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes, Ford and Chevrolet, remained consistent across both years. A more significant shift occurred in the age distribution of persons involved in crashes. The 16-20 age group saw its involvement decrease from 49 individuals in 2021 to 37 in 2022. In contrast, involvement increased for several other age groups, most notably the 26-34 group (from 29 to 47 people) and the 45-54 group (from 34 to 46 people).

Top Vehicle Makes (227 vehicles)

1
FORD42 (18.5%)
→0.0%prior 42
2
CHEV39 (17.2%)
↑34.5%prior 29
3
CHEVROLET18 (7.9%)
↓-28.0%prior 25
4
DODG15 (6.6%)
↑66.7%prior 9
5
GMC10 (4.4%)
↑66.7%prior 6
6
JEEP9 (4%)
↓-30.8%prior 13
7
TOYOTA8 (3.5%)
8
DODGE7 (3.1%)
↓-36.4%prior 11
9
HOND5 (2.2%)
10
NR5 (2.2%)

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

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

Sex Distribution (201 persons with recorded sex)

Male134 (66.7%)
↑32.7%prior 101
Female67 (33.3%)
↓-1.5%prior 68

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: 165
  • Total persons involved: 323
  • Total vehicles involved: 227

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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