Yearly Traffic Safety Analysis

98 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Calhoun County, total crashes decreased by 30% from 140 in 2021 to 98 in 2022. Despite the overall reduction in collisions and injuries, the most notable year-over-year change was the registration of one fatal crash in 2022, whereas none were recorded in the prior year.

98

▼ -30.0%was 140

Total Crash Events

1

Persons Killed

21

▼ -50.0%was 42

Persons Injured

1

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

Traffic crashes in Calhoun County showed a significant downward trend, with total incidents falling by 30% from 140 in 2021 to 98 in 2022. The number of injuries was halved, decreasing from 42 to 21. However, this positive trend was offset by the occurrence of one fatality in 2022, compared to zero in 2021.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 0→%

1

Pedestrians Injured

Prior: 0→%

20

Motorists Injured

Prior: 41↓-51.2%

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, Monday was the distinct peak day with 23 crashes, whereas 2021 had a three-way tie for the peak day with 25 crashes each on Monday, Wednesday, and Friday. Peak crash times also changed, moving from several daytime peaks in 2021 (10 crashes each at 8 AM, 12 PM, 3 PM, and 6 PM) to a dual peak in 2022 at 9 AM and 9 PM (9 crashes each).

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 saw a mixed change year-over-year. A fatal crash occurred in 2022, raising the fatal crash rate from 0% to 1.02%. Conversely, the overall proportion of crashes resulting in any level of injury decreased, from 26.4% of all crashes in 2021 to 20.4% in 2022. This included a notable drop in the share of serious injury crashes, which fell from 5% to 1% of the total.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
Serious Injury1serious injury crashes1%
↓-85.7%prior 7
Minor Injury8minor injury crashes8.2%
↓-38.5%prior 13
Possible Injury11possible injury crashes11.2%
↓-35.3%prior 17
No Injury77no injury crashes78.6%
↓-25.2%prior 103

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, though the count of these incidents decreased by 24% from 41 in 2021 to 31 in 2022. The second most common factor shifted from "Lost Control" in 2021 (15 crashes) to "Ran off road - straight" in 2022 (9 crashes). Crashes attributed to "Lost Control" saw a substantial 73% reduction in count, falling from 15 to 4 year-over-year.

Officer-Reported Primary Contributing Cause

Animal31 (31.6%)↓-24.4%prior 41
Ran off road - straight9 (9.2%)↑28.6%prior 7
Driving too fast for conditions7 (7.1%)↑40.0%prior 5
Followed too close6 (6.1%)
Other (explain in narrative): Other5 (5.1%)↓-50.0%prior 10
FTYROW: From stop sign4 (4.1%)
Driver Distraction: Other interior distraction4 (4.1%)
Lost Control4 (4.1%)↓-73.3%prior 15
Ran off road - left3 (3.1%)
FTYROW: From driveway2 (2%)

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 prevailing conditions during crashes were largely consistent year-over-year, with a majority of incidents in both periods occurring in clear weather, during daylight, and on dry roads. One notable shift was in lighting conditions; the proportion of crashes that occurred on unlit dark roadways increased from 20.7% of all incidents in 2021 to 27.6% in 2022. The share of crashes on adverse surfaces like ice, snow, or wet pavement remained stable.

Weather

Clear51 (64.6%)
↓-28.2%prior 71
Cloudy16 (20.3%)
↓-20.0%prior 20
Snow7 (8.9%)
Rain4 (5.1%)
↓-42.9%prior 7
Freezing rain/drizzle1 (1.3%)

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

Lighting

Daylight46 (57.5%)
↓-30.3%prior 66
Dark - roadway not lighted27 (33.8%)
↓-6.9%prior 29
Dark - roadway lighted6 (7.5%)
↓-25.0%prior 8
Dawn1 (1.3%)
↓-80.0%prior 5

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

Road Surface

Dry55 (68.8%)
↓-28.6%prior 77
Gravel8 (10.0%)
↓-27.3%prior 11
Ice/frost6 (7.5%)
↓-25.0%prior 8
Snow6 (7.5%)
↑20.0%prior 5
Wet5 (6.3%)
↓-37.5%prior 8

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

Vehicles & Demographics

Chevrolet and Ford vehicles were the two most common makes involved in crashes in both 2021 and 2022. The age demographics of persons involved in crashes shifted notably; involvement for the 16-20 and 26-34 age groups decreased from 42 individuals each in 2021 to 26 and 19, respectively, in 2022. The 35-44 age group became the most represented in 2022, with 29 individuals involved.

Top Vehicle Makes (137 vehicles)

1
CHEV24 (17.5%)
↓-20.0%prior 30
2
FORD18 (13.1%)
↓-18.2%prior 22
3
GMC10 (7.3%)
↑25.0%prior 8
4
DODG8 (5.8%)
↑14.3%prior 7
5
CHEVROLET7 (5.1%)
↓-50.0%prior 14
6
NR6 (4.4%)
7
PONT5 (3.6%)
8
MACK4 (2.9%)
↓-20.0%prior 5
9
TOYO4 (2.9%)
10
CHRY4 (2.9%)
↓-33.3%prior 6

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

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

Sex Distribution (121 persons with recorded sex)

Male85 (70.2%)
↑1.2%prior 84
Female36 (29.8%)
↓-42.9%prior 63

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: 98
  • Total persons involved: 187
  • Total vehicles involved: 137

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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