ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · IOWA, IA · NOVEMBER 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/iowa/statewide/november-2022-report
Monthly Traffic Safety Analysis
5,621 CRASHES IN
IOWA, IA
NOVEMBER 2022
In November 2022, Iowa recorded 5,621 vehicle crashes, a 7.6% increase from the 5,223 crashes reported in November 2021. While total crashes and injuries rose, the number of fatalities decreased from 29 to 26 year-over-year. The most significant shift in contributing factors was a 258% increase in the count of crashes attributed to 'Driving too fast for conditions', which rose from 103 incidents in the prior period to 369 in the current period.
5,621
▲ 7.6%was 5,223
Total Crash Events
26
▼ -10.3%was 29
Persons Killed
1,403
▲ 6.9%was 1,312
Persons Injured
20
▼ -23.1%was 26
Fatal Crash Events
Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Iowa showed an upward trend in November 2022 compared to the same month in the previous year. The total number of crashes increased by 398, from 5,223 to 5,621, representing a 7.6% rise. Similarly, the number of people injured in these incidents grew by 6.9%, from 1,312 to 1,403, while fatalities saw a slight decrease from 29 to 26.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
25
Motorists Killed
0
Other Killed
38
Pedestrians Injured
17
Cyclists Injured
1,347
Motorists Injured
1
Other Injured
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year, with Tuesday being the peak day for crashes in both November 2022 (1,115 crashes) and November 2021 (924 crashes). The 5 PM hour was the peak time for collisions in both periods, accounting for 633 crashes in the current period and 607 in the prior. A notable change was a substantial increase in crashes occurring on both Tuesday (up from 924 to 1,115) and Wednesday (up from 733 to 1,100) in November 2022.
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the severity of crashes decreased slightly year-over-year. The fatal crash rate fell from 0.5% of all crashes in November 2021 to 0.4% in November 2022, with the absolute count of fatal crashes dropping from 26 to 20. The count of serious injury crashes also decreased from 88 to 79. However, crashes resulting in possible injuries increased from 714 to 775, and those with minor injuries rose from 391 to 402.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 26 persons killed.
Outcome by Severity (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record
Top Contributing Factors
Collisions involving animals remained the top contributing factor in both periods, though the count decreased by 2.0% from 1,619 to 1,587. The most dramatic year-over-year change was for 'Driving too fast for conditions,' which surged by 258% from 103 crashes to 369, moving it from the 11th-ranked factor to the 3rd. 'Ran off road - left' also saw a significant 42.5% increase in count, from 219 to 312 incidents. Conversely, crashes attributed to 'Followed too close' decreased by 4.6% in count, from 460 to 439.
Officer-Reported Primary Contributing Cause
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather and road conditions were substantially more prevalent in crashes during November 2022 compared to November 2021. Crashes occurring in snow increased from 38 to 455, and those in rain rose from 121 to 297. This corresponds with a sharp rise in crashes on adverse road surfaces, with incidents on icy or frosty roads increasing from 87 to 354 and on snowy roads from 4 to 309. Consequently, crashes on dry roads decreased from 3,469 to 3,035.
Weather
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash
Lighting
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field
Road Surface
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes, Ford and Chevrolet, maintained their positions in both periods, with both seeing an increase in crash involvement counts year-over-year. The number of Ford vehicles in crashes grew from 1,357 to 1,464. A significant demographic shift was observed in the age of persons involved in crashes; there was a notable increase in the 16-20 age group (from 1,058 to 1,385), the 21-25 age group (from 946 to 1,293), and the 26-34 age group (from 1,428 to 1,938).
Top Vehicle Makes (8,868 vehicles)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records
1,214 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (8,149 persons with recorded sex)
Source: Iowa Crash Data · ArcGIS Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
- Report generated: September 9, 2026
Data Coverage
- Reporting period: 2022-11-01 through 2022-11-30 (30 days)
- Geographic scope: iowa, IA
- Total crash records analyzed: 5,621
- Total persons involved: 12,108
- Total vehicles involved: 8,868
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: November 2022." Published September 9, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/november-2022-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Iowa Crash Data · ArcGIS
Period: 2022-11-01 – 2022-11-30
Generated: September 9, 2026 · All rights reserved