Yearly Traffic Safety Analysis

652 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Jasper County recorded 652 total crashes, a 5.8% decrease from the 692 crashes documented in 2021. While overall crashes, injuries, and fatalities declined, the most significant year-over-year change was a 30.6% reduction in crashes involving driving under the influence, which fell from 36 in 2021 to 25 in 2022.

652

▼ -5.8%was 692

Total Crash Events

3

▼ -25.0%was 4

Persons Killed

203

▼ -7.3%was 219

Persons Injured

2

▼ -50.0%was 4

Fatal Crash Events

Note: "Persons Killed" (3) 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

Overall traffic incidents in Jasper County showed a downward trend from 2021 to 2022. The total number of crashes decreased by 5.8%, from 692 to 652. This decline was also reflected in the number of people injured, which fell from 219 to 203, and total fatalities, which dropped from 4 to 3.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 1↓-100.0%

3

Motorists Killed

Prior: 3→0.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 3↓-66.7%

1

Cyclists Injured

Prior: 3↓-66.7%

199

Motorists Injured

Prior: 213↓-6.6%

2

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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Friday with 109 incidents, a change from 2021 when Thursday was the peak day with 123 incidents. The peak hour for crashes also moved, shifting from 7 p.m. in 2021 (44 crashes) to 3 p.m. in 2022 (55 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

The severity of crashes decreased from 2021 to 2022. The number of fatal crashes was halved, dropping from 4 to 2, and the fatal crash rate fell from 0.6% to 0.3% of all crashes. The proportion of crashes resulting in serious injuries also declined from 3.5% to 2.9%, while the share of crashes with no injuries increased from 72.0% in 2021 to 73.9% in 2022.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
↓-50.0%prior 4
Serious Injury19serious injury crashes2.9%
↓-20.8%prior 24
Minor Injury83minor injury crashes12.7%
↑20.3%prior 69
Possible Injury66possible injury crashes10.1%
↓-32.0%prior 97
No Injury482no injury crashes73.9%
↓-3.2%prior 498

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 leading contributing factor in both periods, with the count of such incidents increasing by 14.3% from 126 in 2021 to 144 in 2022. The second and third most common factors swapped places; crashes attributed to 'Driving too fast for conditions' decreased in count from 59 to 54, while 'Lost Control' incidents saw a more substantial drop in count from 72 to 53. Crashes involving 'Followed too close' also declined from 34 to 29.

Officer-Reported Primary Contributing Cause

Animal144 (22.1%)↑14.3%prior 126
Driving too fast for conditions54 (8.3%)↓-8.5%prior 59
Lost Control53 (8.1%)↓-26.4%prior 72
Ran off road - straight43 (6.6%)↓-17.3%prior 52
Other (explain in narrative): Other39 (6%)↑2.6%prior 38
Ran off road - left36 (5.5%)↓-12.2%prior 41
Followed too close29 (4.4%)↓-14.7%prior 34
Driver Distraction: Other interior distraction23 (3.5%)↑9.5%prior 21
Ran Stop Sign20 (3.1%)↑25.0%prior 16
FTYROW: From stop sign19 (2.9%)↑11.8%prior 17

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 majority of crashes in both 2022 and 2021 occurred in clear weather and on dry roads. The proportion of crashes occurring in adverse weather conditions like snow or rain decreased from 17.0% in 2021 to 14.1% in 2022. Similarly, crashes in dark or low-light conditions fell from representing 29.2% of the total in 2021 to 26.7% in 2022. The percentage of crashes on wet, icy, or snowy road surfaces remained nearly constant at approximately 23% in both years.

Weather

Clear371 (69.0%)
↓-10.0%prior 412
Cloudy65 (12.1%)
↑4.8%prior 62
Snow42 (7.8%)
↓-2.3%prior 43
Rain26 (4.8%)
↑62.5%prior 16
Blowing Snow14 (2.6%)
↓-64.1%prior 39
Freezing rain/drizzle7 (1.3%)
↓-41.7%prior 12
Other (explain in narrative)5 (0.9%)
Fog, smoke, smog5 (0.9%)
Severe Winds2 (0.4%)
Sleet, hail1 (0.2%)

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

Lighting

Daylight334 (62.0%)
↓-10.0%prior 371
Dark - roadway not lighted128 (23.7%)
↓-8.6%prior 140
Dark - roadway lighted40 (7.4%)
↓-29.8%prior 57
Dusk18 (3.3%)
↑20.0%prior 15
Dawn13 (2.4%)
→0.0%prior 13
Dark - unknown roadway lighting6 (1.1%)
↑20.0%prior 5

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

Road Surface

Dry373 (69.2%)
↓-11.8%prior 423
Wet53 (9.8%)
↑29.3%prior 41
Ice/frost50 (9.3%)
↓-16.7%prior 60
Snow42 (7.8%)
↓-26.3%prior 57
Gravel11 (2.0%)
↓-15.4%prior 13
Slush5 (0.9%)
→0.0%prior 5
Mud, dirt3 (0.6%)
Other (explain in narrative)1 (0.2%)
Water (standing or moving)1 (0.2%)

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 in crashes in both years. In 2022, 147 Ford and 194 Chevrolet vehicles (combining 'CHEV' and 'CHEVROLET' entries) were involved, compared to 145 and 207, respectively, in 2021. An analysis of persons involved in crashes shows a shift in age demographics; the number of people aged 65 and older increased from 120 to 163, while the 26-34 age group saw a decrease from 223 to 186.

Top Vehicle Makes (975 vehicles)

1
FORD147 (15.1%)
↑1.4%prior 145
2
CHEV147 (15.1%)
↑28.9%prior 114
3
CHEVROLET47 (4.8%)
↓-49.5%prior 93
4
TOYT44 (4.5%)
↑51.7%prior 29
5
GMC43 (4.4%)
→0.0%prior 43
6
DODG38 (3.9%)
↑26.7%prior 30
7
FREIGHTLINER30 (3.1%)
↓-42.3%prior 52
8
JEEP28 (2.9%)
↓-9.7%prior 31
9
NISS26 (2.7%)
↑136.4%prior 11
10
HOND24 (2.5%)
↑9.1%prior 22

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

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

Sex Distribution (892 persons with recorded sex)

Male547 (61.3%)
↓-1.1%prior 553
Female345 (38.7%)
↑8.8%prior 317

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: 652
  • Total persons involved: 1,347
  • Total vehicles involved: 975

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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