Yearly Traffic Safety Analysis

254 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Jones County, total vehicle crashes decreased by 14.2%, from 296 incidents in 2021 to 254 in 2022. This overall reduction in crashes was accompanied by a significant year-over-year drop in traffic fatalities, which fell from 7 in the prior period to 3 in the current period.

254

▼ -14.2%was 296

Total Crash Events

3

▼ -57.1%was 7

Persons Killed

65

▼ -8.5%was 71

Persons Injured

3

▼ -57.1%was 7

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

Traffic safety trends in Jones County showed improvement year-over-year. Total crashes fell by 14.2% from 296 to 254. Concurrently, the number of persons killed in crashes decreased from 7 to 3, and the total number of injuries declined from 71 to 65.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 7↓-57.1%

2

Pedestrians Injured

Prior: 0→%

63

Motorists Injured

Prior: 69↓-8.7%

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 46 incidents, a change from 2021 when Friday was the peak day with 60 crashes. The peak hour also moved from the evening to the morning, with 6 a.m. seeing the most crashes (20) in 2022, compared to multiple evening and commuter peaks in 2021, including 20 crashes at 8 p.m.

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 notably from 2021 to 2022. The number of fatal crashes fell from 7 to 3, and the fatal crash rate was halved, dropping from 2.36% to 1.18% of all crashes. Crashes resulting in serious injuries also decreased from 6 to 4. Conversely, the count of minor injury crashes increased from 21 to 26, representing 10.2% of crashes in 2022 compared to 7.1% in 2021.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.2%
↓-57.1%prior 7
Serious Injury4serious injury crashes1.6%
↓-33.3%prior 6
Minor Injury26minor injury crashes10.2%
↑23.8%prior 21
Possible Injury23possible injury crashes9.1%
↓-20.7%prior 29
No Injury198no injury crashes78%
↓-15.0%prior 233

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 periods, though the count of these incidents decreased by 9.8% from 122 in 2021 to 110 in 2022. Several other major factors saw significant reductions in count, including crashes attributed to 'Ran off road - straight' (from 16 to 7) and 'FTYROW: From stop sign' (from 14 to 6). In contrast, crashes where 'Driving too fast for conditions' was a factor more than doubled, increasing from 5 incidents in 2021 to 11 in 2022.

Officer-Reported Primary Contributing Cause

Animal110 (43.3%)↓-9.8%prior 122
Lost Control25 (9.8%)↓-13.8%prior 29
Driving too fast for conditions11 (4.3%)↑120.0%prior 5
Other (explain in narrative): Other10 (3.9%)↑11.1%prior 9
Driver Distraction: Other interior distraction9 (3.5%)↑50.0%prior 6
Ran off road - left9 (3.5%)→0.0%prior 9
Ran off road - straight7 (2.8%)↓-56.3%prior 16
Made improper turn7 (2.8%)
FTYROW: From stop sign6 (2.4%)↓-57.1%prior 14
Followed too close6 (2.4%)↓-50.0%prior 12

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

Road & Environmental Conditions

While total crashes decreased, the number of incidents occurring on adverse road surfaces increased. Crashes on roads with snow or ice rose from a combined 22 incidents in 2021 to 29 in 2022. This occurred even as crashes on dry roads fell from 135 to 108. The distribution of crashes by lighting condition remained relatively stable, with most incidents in both years happening during daylight (114 in 2022 vs. 122 in 2021).

Weather

Clear92 (58.2%)
↓-24.0%prior 121
Cloudy34 (21.5%)
↓-8.1%prior 37
Snow13 (8.2%)
↑30.0%prior 10
Rain9 (5.7%)
↓-35.7%prior 14
Freezing rain/drizzle4 (2.5%)
Blowing Snow3 (1.9%)
Other (explain in narrative)2 (1.3%)
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

Daylight114 (71.7%)
↓-6.6%prior 122
Dark - roadway not lighted28 (17.6%)
↓-28.2%prior 39
Dark - roadway lighted10 (6.3%)
↓-28.6%prior 14
Dusk4 (2.5%)
↓-60.0%prior 10
Dawn2 (1.3%)
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

Dry108 (67.5%)
↓-20.0%prior 135
Wet19 (11.9%)
↓-20.8%prior 24
Ice/frost15 (9.4%)
↑15.4%prior 13
Snow14 (8.8%)
↑55.6%prior 9
Gravel2 (1.3%)
↓-60.0%prior 5
Mud, dirt1 (0.6%)
Slush1 (0.6%)

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 consistent, with Ford and Chevrolet being the most common in both years. However, the number of Dodge vehicles involved decreased from 38 in 2021 to 27 in 2022, and Toyota vehicles dropped from 37 to 26. Analysis of person age distribution shows a significant decrease in crash involvement for the 16-20 age group, which fell from 69 persons in 2021 to 44 in 2022. Conversely, involvement for persons aged 26-34 and 35-44 increased from 70 to 81 and 83 to 97, respectively.

Top Vehicle Makes (348 vehicles)

1
FORD68 (19.5%)
↑1.5%prior 67
2
CHEV49 (14.1%)
↑8.9%prior 45
3
CHEVROLET24 (6.9%)
→0.0%prior 24
4
GMC18 (5.2%)
↓-21.7%prior 23
5
DODG17 (4.9%)
↓-26.1%prior 23
6
TOYO13 (3.7%)
↓-43.5%prior 23
7
HOND11 (3.2%)
→0.0%prior 11
8
DODGE10 (2.9%)
↓-33.3%prior 15
9
CHRY9 (2.6%)
↑50.0%prior 6
10
NISS9 (2.6%)
↑28.6%prior 7

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

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

Sex Distribution (323 persons with recorded sex)

Male197 (61.0%)
↑13.9%prior 173
Female126 (39.0%)
↓-5.3%prior 133

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: 254
  • Total persons involved: 528
  • Total vehicles involved: 348

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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