Yearly Traffic Safety Analysis

186 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Crawford County recorded 186 total crashes, a 15.1% decrease from the 219 crashes documented in 2021. This overall reduction in collisions was accompanied by a 20.9% drop in total injuries, from 67 to 53, while fatalities remained constant at two. The most significant year-over-year change was the overall decline in crash frequency across the county.

186

▼ -15.1%was 219

Total Crash Events

2

Persons Killed

53

▼ -20.9%was 67

Persons Injured

2

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

Trend Summary

Crash data for Crawford County indicates a downward trend year-over-year. Total collisions fell by 15.1%, from 219 in 2021 to 186 in 2022. The number of people injured in these incidents also decreased by 20.9% from 67 to 53, while the number of fatalities held steady at two for both periods.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 2→0.0%

0

Other Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

51

Motorists Injured

Prior: 67↓-23.9%

1

Other Injured

Prior: 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

The temporal patterns of crashes shifted between the two periods. In 2022, the peak day for crashes was Tuesday with 34 incidents, a change from 2021 when Friday was the peak day with 44 incidents. The most frequent time for crashes also moved later in the day, from the 3 p.m. hour in 2021 (21 crashes) to the 5 p.m. hour in 2022 (19 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

While the total number of fatal crashes remained at two in both 2022 and 2021, the fatal crash rate saw a slight increase from 0.91% to 1.08% due to the lower overall crash volume in 2022. The proportion of crashes resulting in any injury was slightly higher in the recent period, at 25.3% compared to 23.7% in the prior year. This was driven by an increase in the share of minor injury crashes, which rose from 7.3% of all crashes in 2021 to 10.2% in 2022.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
→0.0%prior 2
Serious Injury7serious injury crashes3.8%
↓-22.2%prior 9
Minor Injury19minor injury crashes10.2%
↑18.8%prior 16
Possible Injury21possible injury crashes11.3%
↓-22.2%prior 27
No Injury137no injury crashes73.7%
↓-17.0%prior 165

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 animals remained the leading contributing factor in both years, though the count of these incidents decreased by 24.3% from 37 in 2021 to 28 in 2022. Crashes attributed to 'Lost Control' increased by 28.6% from 14 to 18 incidents, and those due to 'Followed too close' rose from 14 to 17. Conversely, crashes where a driver failed to yield the right-of-way from a stop sign dropped by 40%, from 15 incidents in 2021 to 9 in 2022.

Officer-Reported Primary Contributing Cause

Animal28 (15.1%)↓-24.3%prior 37
Other (explain in narrative): Other19 (10.2%)↓-5.0%prior 20
Lost Control18 (9.7%)↑28.6%prior 14
Followed too close17 (9.1%)↑21.4%prior 14
Driver Distraction: Other interior distraction10 (5.4%)↓-28.6%prior 14
FTYROW: From stop sign9 (4.8%)↓-40.0%prior 15
Ran off road - left9 (4.8%)↓-18.2%prior 11
FTYROW: Making left turn6 (3.2%)
Made improper turn5 (2.7%)↓-16.7%prior 6
Ran off road - straight4 (2.2%)↓-55.6%prior 9

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 broadly similar year-over-year, with the majority of incidents in both periods occurring in daylight on dry roads. The proportion of crashes on dry surfaces increased from 62.6% in 2021 to 67.7% in 2022. Notably, crashes on roads with ice or frost saw a significant reduction, falling from 18 incidents in 2021 to just 6 in 2022.

Weather

Clear123 (74.5%)
↓-1.6%prior 125
Cloudy19 (11.5%)
↓-50.0%prior 38
Snow11 (6.7%)
↑120.0%prior 5
Rain6 (3.6%)
Blowing Snow2 (1.2%)
Freezing rain/drizzle1 (0.6%)
↓-83.3%prior 6
Fog, smoke, smog1 (0.6%)
Blowing sand, soil, dirt1 (0.6%)
Severe Winds1 (0.6%)

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

Lighting

Daylight110 (65.9%)
↓-17.3%prior 133
Dark - roadway lighted25 (15.0%)
↑47.1%prior 17
Dark - roadway not lighted22 (13.2%)
→0.0%prior 22
Dusk5 (3.0%)
↓-16.7%prior 6
Dawn4 (2.4%)
↓-20.0%prior 5
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry126 (75.4%)
↓-8.0%prior 137
Snow15 (9.0%)
↑7.1%prior 14
Wet10 (6.0%)
↑25.0%prior 8
Gravel7 (4.2%)
↑16.7%prior 6
Ice/frost6 (3.6%)
↓-66.7%prior 18
Other (explain in narrative)2 (1.2%)
Slush1 (0.6%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved makes in both 2021 and 2022, although the count of Fords in crashes decreased from 80 to 54. A significant shift occurred in the age distribution of persons involved in crashes. In 2022, the 16-20 age group was the most represented with 63 individuals, a change from 2021 when the 26-34 age group was largest with 85 individuals.

Top Vehicle Makes (310 vehicles)

1
FORD54 (17.4%)
↓-32.5%prior 80
2
CHEV52 (16.8%)
↑15.6%prior 45
3
CHEVROLET22 (7.1%)
↓-38.9%prior 36
4
TOYT16 (5.2%)
↑100.0%prior 8
5
GMC15 (4.8%)
↓-40.0%prior 25
6
NISS11 (3.5%)
↑83.3%prior 6
7
HOND10 (3.2%)
8
JEEP10 (3.2%)
→0.0%prior 10
9
DODG9 (2.9%)
↓-57.1%prior 21
10
BUIC7 (2.3%)

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 (277 persons with recorded sex)

Male183 (66.1%)
↓-1.1%prior 185
Female94 (33.9%)
↓-21.7%prior 120

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: 186
  • Total persons involved: 409
  • Total vehicles involved: 310

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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