Yearly Traffic Safety Analysis

128 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Page County recorded 128 traffic crashes, a 16.3% decrease from the 153 crashes reported in 2021. While overall crashes and the number of injuries declined, incidents related to failure to yield from a stop sign more than tripled, increasing from 4 in 2021 to 13 in 2022. There were no fatalities recorded in either period.

128

▼ -16.3%was 153

Total Crash Events

0

Persons Killed

36

▼ -29.4%was 51

Persons Injured

0

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 in Page County shows a year-over-year decrease in traffic collisions. Total crashes fell by 16.3%, from 153 in 2021 to 128 in 2022. Similarly, the number of people injured in these incidents decreased by 29.4%, from 51 to 36, while fatalities remained at zero for both years.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

36

Motorists Injured

Prior: 51↓-29.4%

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 in Page County showed a notable shift in the peak time of day. While Friday remained the most frequent day for crashes in both 2022 (25 crashes) and 2021 (28 crashes), the peak hour for incidents moved from 4 p.m. in 2021 (13 crashes) to 7 a.m. in 2022 (11 crashes). This indicates a change from an afternoon peak to a morning peak year-over-year.

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 in Page County improved from 2021 to 2022, with no fatal crashes recorded in either year. The number of serious injury crashes saw a substantial decrease, falling from 8 incidents in 2021 to just 1 in 2022. Consequently, the proportion of crashes resulting in no injuries increased from 70.6% of all crashes in 2021 to 77.3% in 2022.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.8%
↓-87.5%prior 8
Minor Injury8minor injury crashes6.3%
→0.0%prior 8
Possible Injury20possible injury crashes15.6%
↓-31.0%prior 29
No Injury99no injury crashes77.3%
↓-8.3%prior 108

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

While collisions involving an animal remained the top contributing factor in both periods, the count decreased from 27 in 2021 to 21 in 2022. A significant shift occurred in the rankings, with crashes attributed to 'FTYROW: From stop sign' increasing from 4 to 13, making it the second-most common factor in 2022. Conversely, incidents of 'Followed too close' dropped sharply from 17 in 2021 to 5 in 2022, falling from the second-ranked factor to the eighth.

Officer-Reported Primary Contributing Cause

Animal21 (16.4%)↓-22.2%prior 27
FTYROW: From stop sign13 (10.2%)
Lost Control10 (7.8%)→0.0%prior 10
Driving too fast for conditions6 (4.7%)↓-14.3%prior 7
Ran off road - left6 (4.7%)↓-14.3%prior 7
Improper Backing6 (4.7%)
Ran Stop Sign6 (4.7%)↓-14.3%prior 7
Followed too close5 (3.9%)↓-70.6%prior 17
FTYROW: From parked position5 (3.9%)
FTYROW: From driveway4 (3.1%)

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. In 2022, 71.1% of crashes happened on dry surfaces, compared to 67.3% in 2021. However, the share of crashes on wet roads increased from 4.6% (7 incidents) in 2021 to 9.4% (12 incidents) in 2022. Collisions attributed to snowy road conditions saw a notable decrease, dropping from 8 incidents in 2021 to 2 in 2022.

Weather

Clear78 (69.0%)
↓-20.4%prior 98
Cloudy26 (23.0%)
↓-10.3%prior 29
Rain3 (2.7%)
Fog, smoke, smog2 (1.8%)
Freezing rain/drizzle2 (1.8%)
Snow1 (0.9%)
↓-83.3%prior 6
Blowing Snow1 (0.9%)

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

Lighting

Daylight75 (67.0%)
↓-21.9%prior 96
Dark - roadway not lighted20 (17.9%)
↓-16.7%prior 24
Dark - roadway lighted9 (8.0%)
↓-10.0%prior 10
Dusk5 (4.5%)
Dark - unknown roadway lighting2 (1.8%)
Dawn1 (0.9%)

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

Road Surface

Dry91 (80.5%)
↓-11.7%prior 103
Wet12 (10.6%)
↑71.4%prior 7
Ice/frost5 (4.4%)
↓-44.4%prior 9
Gravel2 (1.8%)
↓-66.7%prior 6
Snow2 (1.8%)
↓-75.0%prior 8
Slush1 (0.9%)

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

Vehicles & Demographics

The distribution of vehicle makes involved in crashes remained relatively consistent, with Ford being the most common make in both 2022 (40 vehicles) and 2021 (44 vehicles). More significant changes were observed in the age demographics of persons involved in crashes. The number of individuals in the 35-44 age group dropped from 48 to 25, while the 45-54 age group saw an increase from 24 to 41 persons involved in collisions.

Top Vehicle Makes (201 vehicles)

1
FORD40 (19.9%)
↓-9.1%prior 44
2
CHEV30 (14.9%)
↑7.1%prior 28
3
DODG14 (7%)
↓-17.6%prior 17
4
CHEVROLET13 (6.5%)
↓-58.1%prior 31
5
GMC10 (5%)
↑11.1%prior 9
6
DODGE8 (4%)
↓-11.1%prior 9
7
BUIC8 (4%)
8
NISS6 (3%)
→0.0%prior 6
9
KIA6 (3%)
10
CHRY6 (3%)
↑20.0%prior 5

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

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

Sex Distribution (182 persons with recorded sex)

Male101 (55.5%)
↓-12.2%prior 115
Female81 (44.5%)
↑3.8%prior 78

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: 128
  • Total persons involved: 265
  • Total vehicles involved: 201

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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