Yearly Traffic Safety Analysis

263 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Buchanan County recorded 263 total crashes, a 4.4% decrease from the 275 crashes reported in 2021. The most significant year-over-year change was a reduction in crash severity, with total fatalities decreasing from four to one and total injuries declining from 85 to 66.

263

▼ -4.4%was 275

Total Crash Events

1

▼ -75.0%was 4

Persons Killed

66

▼ -22.4%was 85

Persons Injured

1

▼ -66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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, traffic crashes in Buchanan County saw a downward trend in 2022 compared to the previous year. The total number of crashes decreased by 4.4%, from 275 in 2021 to 263 in 2022. This trend was also reflected in crash outcomes, with total injuries falling by 22.4% and the number of fatalities decreasing from four to one.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 4↓-75.0%

1

Pedestrians Injured

Prior: 0→%

1

Cyclists Injured

Prior: 1→0.0%

64

Motorists Injured

Prior: 84↓-23.8%

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 showed some shifts between the two periods. In 2022, the peak day for crashes was Saturday with 49 incidents, whereas in 2021, Wednesday was the peak day with 53 incidents. The peak hour for crashes remained consistent at 6 p.m. in both years, although the number of crashes during that hour decreased from 24 in 2021 to 19 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

Crash severity decreased in 2022 compared to 2021. The number of fatal crashes fell from three to one, causing the fatal crash rate to drop from 1.09% to 0.38%. The proportion of crashes resulting in any level of injury also declined, from 24.4% of all crashes in 2021 to 19.8% in 2022. This was driven by a drop in minor injury crashes, which accounted for 7.2% of crashes in 2022 compared to 11.6% in the prior year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-66.7%prior 3
Serious Injury6serious injury crashes2.3%
↓-14.3%prior 7
Minor Injury19minor injury crashes7.2%
↓-40.6%prior 32
Possible Injury27possible injury crashes10.3%
↓-3.6%prior 28
No Injury210no injury crashes79.8%
↑2.4%prior 205

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 involving an animal remained the leading contributing factor in both periods, with a slight decrease in count from 90 crashes in 2021 to 88 in 2022. The ranking of other top factors shifted year-over-year. Crashes attributed to 'Followed too close' decreased from 18 to 12, while those involving 'Driving too fast for conditions' increased from 14 to 17. Incidents where a driver 'Lost Control' also saw a reduction in count from 19 in 2021 to 15 in 2022.

Officer-Reported Primary Contributing Cause

Animal88 (33.5%)↓-2.2%prior 90
Driving too fast for conditions17 (6.5%)↑21.4%prior 14
Lost Control15 (5.7%)↓-21.1%prior 19
Ran off road - straight15 (5.7%)↑7.1%prior 14
Other (explain in narrative): Other13 (4.9%)↑44.4%prior 9
Followed too close12 (4.6%)↓-33.3%prior 18
FTYROW: From stop sign10 (3.8%)↓-9.1%prior 11
Operating vehicle in an reckless, erratic, careless, negligent manner8 (3%)↓-11.1%prior 9
Ran off road - left8 (3%)↓-46.7%prior 15
Improper Backing6 (2.3%)↑20.0%prior 5

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

Road & Environmental Conditions

Crashes in clear weather and daylight conditions were the most frequent scenarios in both years, though their combined share of total crashes decreased slightly in 2022. In 2022, 47.9% of crashes occurred in clear weather, down from 51.3% in 2021. There was a corresponding small increase in the proportion of crashes occurring during adverse weather (from 18.5% to 21.3%) and on adverse road surfaces like snow, ice, or water (from 18.2% to 20.5%).

Weather

Clear126 (69.2%)
↓-10.6%prior 141
Cloudy26 (14.3%)
↓-10.3%prior 29
Snow13 (7.1%)
↑8.3%prior 12
Blowing Snow7 (3.8%)
↑40.0%prior 5
Freezing rain/drizzle5 (2.7%)
Rain3 (1.6%)
Fog, smoke, smog1 (0.5%)
Blowing sand, soil, dirt1 (0.5%)

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

Lighting

Daylight127 (69.0%)
↓-9.9%prior 141
Dark - roadway not lighted36 (19.6%)
↑2.9%prior 35
Dark - roadway lighted14 (7.6%)
↑100.0%prior 7
Dawn4 (2.2%)
↓-20.0%prior 5
Dusk3 (1.6%)
↓-40.0%prior 5

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

Road Surface

Dry128 (70.3%)
↓-9.2%prior 141
Ice/frost22 (12.1%)
↑144.4%prior 9
Snow17 (9.3%)
↑13.3%prior 15
Wet9 (4.9%)
↓-18.2%prior 11
Gravel6 (3.3%)
↓-53.8%prior 13

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained broadly similar, with Ford and Chevrolet being the top two in both years. The number of Chevrolet vehicles involved decreased from 96 in 2021 to 88 in 2022, and Dodge vehicles dropped from 33 to 21. The age demographics of persons involved in crashes also shifted; the proportion of individuals aged 16-20 decreased from 13.9% in 2021 to 9.8% in 2022. Conversely, the representation of the 26-34 and 55-64 age groups increased from 12.4% to 18.2% and 9.4% to 14.3%, respectively.

Top Vehicle Makes (378 vehicles)

1
FORD81 (21.4%)
↑2.5%prior 79
2
CHEV68 (18%)
↓-5.6%prior 72
3
CHEVROLET20 (5.3%)
↓-16.7%prior 24
4
GMC17 (4.5%)
↑70.0%prior 10
5
DODG17 (4.5%)
↓-19.0%prior 21
6
HOND14 (3.7%)
↑75.0%prior 8
7
BUIC12 (3.2%)
↓-20.0%prior 15
8
RAM11 (2.9%)
9
NR11 (2.9%)
10
JEEP9 (2.4%)
→0.0%prior 9

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

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

Sex Distribution (353 persons with recorded sex)

Male216 (61.2%)
↑13.1%prior 191
Female137 (38.8%)
↑11.4%prior 123

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 10, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 263
  • Total persons involved: 538
  • Total vehicles involved: 378

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 10, 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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