Yearly Traffic Safety Analysis

69 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In Pocahontas County, total traffic crashes decreased by 21.6% from 88 in 2021 to 69 in 2022. Despite the overall reduction in collisions, the period saw an increase in total injuries from 31 to 34. The most significant year-over-year change was the occurrence of one fatal crash in 2022, whereas there were no fatal crashes in the prior year.

69

▼ -21.6%was 88

Total Crash Events

1

Persons Killed

34

▲ 9.7%was 31

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

The overall trend shows a decrease in the total number of crashes, which fell from 88 in 2021 to 69 in 2022. However, the severity of crashes increased, with total injuries rising from 31 to 34 and one fatality recorded in 2022 compared to zero in the previous year. This suggests that while fewer crashes occurred, they resulted in more severe outcomes.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0→%

34

Motorists Injured

Prior: 30↑13.3%

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 year-over-year. In 2022, the peak day for crashes was Thursday with 18 incidents, a change from 2021 when Tuesday was the peak day with 16 crashes. The peak hour also shifted slightly earlier, from 6 p.m. (7 crashes) in 2021 to 5 p.m. (8 crashes) in 2022. Both years saw a concentration of crashes in the final two months, with November and December accounting for 36% of crashes in 2022 and 27% in 2021.

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 increased in 2022 compared to the prior year. The county recorded one fatal crash, resulting in a fatality rate of 1.45 per 100 crashes, up from zero fatal crashes in 2021. While the number of serious injury crashes remained stable at six for both periods, the total number of injuries increased from 31 to 34. The proportion of crashes resulting in any injury (fatal, serious, minor, or possible) rose from 28.4% in 2021 to 33.3% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.4%
Serious Injury6serious injury crashes8.7%
→0.0%prior 6
Minor Injury9minor injury crashes13%
↓-35.7%prior 14
Possible Injury7possible injury crashes10.1%
↑40.0%prior 5
No Injury46no injury crashes66.7%
↓-27.0%prior 63

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

The top three contributing factors remained consistent across both periods, though their counts changed. Collisions involving an animal were the leading factor in both years but saw a 41.7% decrease in count, falling from 24 crashes in 2021 to 14 in 2022. Crashes attributed to 'Lost Control' also decreased from 11 to 6. Conversely, incidents where a driver 'Ran off road - straight' held steady at 9 crashes in both 2021 and 2022.

Officer-Reported Primary Contributing Cause

Animal14 (20.3%)↓-41.7%prior 24
Ran off road - straight9 (13%)→0.0%prior 9
Lost Control6 (8.7%)↓-45.5%prior 11
Driving too fast for conditions6 (8.7%)
Driver Distraction: Other interior distraction5 (7.2%)
Ran Stop Sign4 (5.8%)↓-33.3%prior 6
FTYROW: From stop sign4 (5.8%)
Followed too close3 (4.3%)
FTYROW: Making left turn3 (4.3%)
Passing: Other passing (explain in narrative)2 (2.9%)

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

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. While the proportion of crashes on dry roads was similar in both years (58% in 2022 vs. 60% in 2021), the number of crashes on roads with ice or frost more than tripled, increasing from 2 in 2021 to 7 in 2022. Correspondingly, the share of crashes happening in daylight increased from 45.5% to 55.1%, while crashes in unlit, dark conditions decreased from 23.9% to 15.9% of the total.

Weather

Clear39 (66.1%)
↓-26.4%prior 53
Cloudy13 (22.0%)
↑30.0%prior 10
Fog, smoke, smog2 (3.4%)
Snow2 (3.4%)
Freezing rain/drizzle1 (1.7%)
Rain1 (1.7%)
Severe Winds1 (1.7%)

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

Lighting

Daylight38 (64.4%)
↓-5.0%prior 40
Dark - roadway not lighted11 (18.6%)
↓-47.6%prior 21
Dark - roadway lighted4 (6.8%)
Dawn4 (6.8%)
Dusk2 (3.4%)

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

Road Surface

Dry40 (67.8%)
↓-24.5%prior 53
Ice/frost7 (11.9%)
Snow4 (6.8%)
↓-20.0%prior 5
Wet4 (6.8%)
Gravel3 (5.1%)
↓-57.1%prior 7
Other (explain in narrative)1 (1.7%)

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

Vehicles & Demographics

The demographics of persons involved in crashes shifted, with the 16-20 age group becoming the most represented group in 2022 with 27 individuals, a notable increase from 18 in 2021. Regarding vehicle makes, Chevrolet and Ford remained the top two most-involved makes in both years, though their crash counts decreased. The most significant change was for Buick vehicles, which were involved in 9 crashes in 2022, a substantial increase from just one in 2021.

Top Vehicle Makes (107 vehicles)

1
CHEV22 (20.6%)
↓-15.4%prior 26
2
FORD17 (15.9%)
↓-10.5%prior 19
3
BUIC9 (8.4%)
4
DODG7 (6.5%)
→0.0%prior 7
5
GMC7 (6.5%)
6
PETERBILT5 (4.7%)
7
DODGE4 (3.7%)
8
TOYO3 (2.8%)
9
FREI3 (2.8%)
10
FREIGHTLINER3 (2.8%)

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

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

Sex Distribution (103 persons with recorded sex)

Male82 (79.6%)
↑36.7%prior 60
Female21 (20.4%)
↓-8.7%prior 23

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: 69
  • Total persons involved: 155
  • Total vehicles involved: 107

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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